Open data maturity report 2024.
Date: 2025-01-16
Institutions: Publications Office of the European Union
Subjects: EFTA countries, EU Member State, activity report, open data

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2024 Open Data Maturity Report 

This study has been prepared as part of data.europa.eu. data.europa.eu is an initiative of the European 
Commission and is the official portal for European open data. The Publications Office of the European 
Union manages data.europa.eu. 

European Commission 

Directorate-General for Communications Networks, Content and Technology 
Unit G.1 – Data Policy and Innovation 
Email: CNECT-G1@ec.europa.eu 

data.europa.eu 
Email: info@data.europa.eu 

Authors – Capgemini Invent 
Martin Page PhD 
Arman Behrooz 
Maddalena Moro 

Last updated: December 2024 

Disclaimer 

The views set out in this publication are those of the authors and do not necessarily reflect the official 
opinion of the Commission. The Commission does not guarantee the accuracy of the data included in 
this study. Neither the Commission nor any person acting on the Commission’s behalf may be held 
responsible for the use that may be made of the information contained therein. 

Luxembourg: Publications Office of the European Union, 2024 

© European Union, 2024 

The  Commission’s  reuse  policy  is  implemented  under  Commission  Decision 2011/833/EU  of 
12 December  2011  on  the  reuse  of  Commission  documents  (OJ  L 330,  14.12.2011,  p. 39,  ELI: 
http://data.europa.eu/eli/dec/2011/833/oj). Unless otherwise noted, the  reuse  of this document is 
authorised  under  the  Creative  Commons  Attribution 4.0 
licence 
(https://creativecommons.org/licences/by/4.0/).  This  means  that  reuse 
is  allowed,  provided 
appropriate credit is given and any changes are indicated. 

International  (CC  BY  4.0) 

ISBN 978-92-78-44708-3 

ISSN 2600-0512  

doi: 10.2830/8656811      OA-01-24-381-EN-N 

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2024 Open Data Maturity Report 

Contents 

Contents ...................................................................................................................................... 3 

Executive summary ...................................................................................................................... 5 

Open data maturity scores in 2024 ..................................................................................................... 5 

Highlights from the four dimensions of the 2024 open data maturity assessment ........................... 8 

Spotlight on high-value datasets ....................................................................................................... 11 

Outlook .............................................................................................................................................. 12 

Chapter 1: Introduction .............................................................................................................. 13 

Background: open data policy in the European Union ..................................................................... 13 

Measuring open data in Europe ........................................................................................................ 13 

The structure of this report ............................................................................................................... 14 

Chapter 2: Methodology ............................................................................................................. 15 

Chapter 3: Overall open data maturity ........................................................................................ 17 

3.1. EU Member State trends ............................................................................................................ 17 

3.2. European Free Trade Association country trends ...................................................................... 17 

3.3. Candidate country trends ........................................................................................................... 17 

Chapter 4: Open data policy........................................................................................................ 19 

4.1. Overall performance on the policy dimension ........................................................................... 21 

4.2. Policy framework ........................................................................................................................ 25 

4.3. Governance of open data ........................................................................................................... 39 

4.4. Open data implementation ........................................................................................................ 47 

Chapter 5: Open data portals ...................................................................................................... 53 

5.1. Overall performance on the portal dimension........................................................................... 55 

5.2. Portal features ............................................................................................................................ 59 

5.3. Portal usage ................................................................................................................................ 68 

5.4. Data provision ............................................................................................................................ 73 

5.5. Portal sustainability .................................................................................................................... 78 

5.6. Pilot indicator: automated tests of portal performance ............................................................ 82 

Chapter 6: Open data quality ...................................................................................................... 84 

6.1. Overall performance on the quality dimension ......................................................................... 86 

6.2. Metadata currency and completeness ....................................................................................... 89 

6.3. Monitoring and measures .......................................................................................................... 94 

6.4. DCAT-AP compliance ................................................................................................................ 101 

6.5. Deployment quality and linked data ........................................................................................ 104 

6.6. Pilot indicator: automated tests of metadata quality .............................................................. 107 

Chapter 7: Open data impact ..................................................................................................... 109 

7.1. Overall performance on the impact dimension ....................................................................... 110 

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2024 Open Data Maturity Report 

7.2. Strategic awareness.................................................................................................................. 114 

7.3. Measuring reuse ....................................................................................................................... 121 

7.4. Created impact ......................................................................................................................... 123 

Chapter 8: Maturity-based clustering and recommendations ...................................................... 141 

8.1. Clustering .................................................................................................................................. 141 

8.2. Recommendations.................................................................................................................... 142 

Chapter 9: Conclusions .............................................................................................................. 148 

Appendix: Methodology ............................................................................................................ 150 

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2024 Open Data Maturity Report 

Executive summary 

The 2024 open data maturity (ODM) assessment evaluated the maturity of countries in the field of 
open data. In particular, the assessment measured the progress of European countries in making public 
sector information available and stimulating its reuse, in line with the open data directive (Directive 
(EU)  2019/1024).  A  total  of  34  countries  participated  in  this  10th  consecutive  annual  assessment, 
including  the  27  EU  Member  States,  3  European  Free  Trade  Association  (EFTA)  countries  (Iceland, 
Norway  and  Switzerland)  and  4  candidate  countries  (Bosnia  and  Herzegovina,  Albania,  Serbia  and 
Ukraine). 

This report aims to help readers better understand the level of ODM of the participating countries, to 
identify areas for improvement and to enable participating countries to learn from one another. As an 
annual publication, the ODM report also captures the progress made by countries over time, with the 
2024  report  providing  the  latest  information.  Moreover,  it  gives  an  overview  of  best  practices 
implemented across Europe that could be transferred to other national and local contexts. 

The assessment methodology defines ODM using four dimensions. 

•  Policy investigates the open data policies and strategies in place in the participating countries, 
the  national  governance  models  for  managing  open  data  and  the  measures  applied  to 
implement policies and strategies. 

•  Portal investigates the functionality of national open data portals, the extent to which users’ 
needs and behaviour are examined to improve the portal, the availability of open data across 
different domains and the approach to ensuring the portal’s sustainability. 

•  Quality  assesses  the  measures  adopted  by  portal  managers  to  ensure  the  systematic 
harvesting of metadata, the monitoring of metadata quality and compliance with the DCAT-
AP metadata standard, and the quality of deployment of the published data on the national 
portal. 
Impact analyses the willingness, preparedness and ability of countries to measure both the 
reuse of open data and the impact created through this reuse. 

• 

Open data maturity scores in 2024 

Figure 1 and Figure 2 show the ODM scores of all 34 participating countries for 2024. Highlights from 
these results include the following points. 

•  A total of 18 countries increased their ODM year-on-year; one country scored the same overall 
as in 2023; and 15 countries experienced a decrease in their maturity score (for 11 countries, 
the decrease was less than 5 percentage points (pp)). 

•  Maturity scores remain concentrated at the higher end of the spectrum, with most countries 

(26 out of 34; 76 %) having a maturity score above 73 %. 

•  The Member States maintained their average maturity score at the same level as in 2023, at 

83 %. 

•  The most mature Member States are France (100 %), Poland (98 %) and Slovakia (96 %). The 
most mature EFTA country is Norway (89 %). The most mature candidate country is Ukraine 
(97 %). 

•  The biggest climbers are Latvia (+ 10 pp), Croatia (+ 9 pp), Serbia (+ 9 pp) and Czechia (+ 6 pp). 

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2024 Open Data Maturity Report 

Figure 1: The average overall maturity score increased from 79 % in 2023 to 80 % in 2024 (YoY: year-
on-year). 

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2024 Open Data Maturity Report 

Figure 2:  The  overall  maturity  score  is  the  average  of  the  scores  for  each  of  the  four  underlying 
dimensions 

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2024 Open Data Maturity Report 

Highlights from the four dimensions of the 2024 open data maturity assessment 

Figure 3 shows the average scores over time on the four maturity dimensions for the Member States. 

1.  The policy dimension remains (as it has been since 2015) the most mature dimension on average 
(91 %) in the EU, with a 2 pp increase since 2023. This growth reflects ongoing improvements in 
the framework for open data policies (+ 2 pp) and the implementation of open data initiatives 
(+ 4 pp). 
•  Compared with 2023, more countries report that their governance structures ensure that local 
and regional open data initiatives are facilitated and supported nationally (up from 20 to 23 
Member  States).  This  suggests  that  there  is  a  growing  commitment  to  cohesive  open  data 
policy and stronger national coordination across multiple levels of government. 

•  More countries report that their national policy/strategy outlines measures to incentivise the 

publication of and access to citizen-generated data (up from 11 to 14). 

•  All Member States report that: 

—  they have an open data policy; 
—  they  are  working  towards applying  the  implementing  regulation  on  high-value datasets 

(HVDs) (Commission Implementing Regulation (EU) 2023/138); 

—  the national open data team and the wider network of open data officers in their countries 

have regular exchanges; 

—  public  sector  bodies  and  open  data  reusers  in  their  countries  regularly  exchange 

knowledge and experiences; 

—  they have plans for publishing open data at the public body level; 
—  they  have  processes  in  place  to ensure that  their open  data  policies  and  strategies  are 

implemented. 

•  Key practices and trends are as follows: 

—  countries  create  structured  training  programmes  to  develop  their  civil  servants’  data 

competencies; 

—  countries’  national  policies  and  strategies  aimed  at  promoting  citizen-generated  data 

often include sector-specific initiatives; 

—  establishing  working  groups  is  a  particularly  common  method  that  countries  use  to 
facilitate exchanges between the national open data team and the wider network of open 
data officers. 

2.  The  portal  dimension  remains  the  second-most-mature  category,  although  the  average  score 
has  declined  compared  with  2023.  This  decrease  is  partly  due  to  the  introduction  of  new 
questions that set higher standards for countries. Overall, while data availability continues to 
improve, advancements in portal features have not kept pace with increased expectations. 
•  This year, 17 Member States (62 %) report allowing the publication of non-official data on their 
portal. This represents a sharp increase from 2023, when only 12 Member States reported that 
non-official providers could contribute data to national portals. Two out of the four candidate 
countries also allow this. 

•  24  Member  States  (88 %;  2  more  than  in  2023),  1  EFTA  country  and  3  out  of  4  candidate 
countries report monitoring the characteristics of the data published on the portal, such as the 
distribution across categories, static versus real-time data and how these change over time. 
•  20 Member States (70 %) report actively promoting HVDs on their national portals. In many 
cases, countries have a specific labelling system or a section to make the HVDs findable for 
users. 

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2024 Open Data Maturity Report 

•  All Member States report: 

—  having a national portal that enables users to search for open datasets and download open 

data; 

—  monitoring  the  portal’s  traffic  (e.g.  the  number  of  unique  visitors,  visitor  profiles,  the 

percentage of machine traffic, the number of downloads for each dataset); 

—  taking  measures  to  optimise  the  searchability  and  discoverability  of  content  (data  and 

editorial); 

—  having metadata available on the portal in clear, plain language to enable both humans 

and machines to read and understand it; 

—  identifying the data providers that are not yet publishing data on the national portal. 

•  Key practices and trends are as follows. 

—  More countries have implemented mechanisms for users to rate datasets on their national 

portals. The rating system is usually star based or grade based. 

—  More  countries report  that  their  national portal showcases  reuse  cases  in a designated 

section. 

—  More countries report monitoring their portal’s traffic and performing other activities to 
better understand the behaviour and needs of portal  users. For instance, countries use 
various analytics tools to monitor the popularity of datasets, and this tracking method is 
used to gain insights into how to improve the quality of datasets. 

3.  The quality dimension is the least mature (79 %). The average score has decreased since 2023 

but is still higher than in 2022. 
•  Compared with 2023, a greater proportion of metadata on Member States’ national portals is 
now  sourced  automatically  rather  than  edited  manually.  Specifically,  more  than  half  of 
Member  States  now  report  that  at  least  50 %  of  the  metadata  on  their  national  portal  is 
automatically sourced (up from 13 to 18 Member States). 

•  More countries (up from 14 to 17 Member States) report that more than 90 % of their datasets 

are provided in an open and machine-readable format. 

•  Key practices and trends are as follows. 

—  Countries report the use of data quality assessment techniques that either combine or go 
beyond  the  widely  used  5-star  open  data  model  or  the  FAIR  principles  (findability, 
accessibility, interoperability and reusability). 

—  Some  countries report  that  their  automatic metadata harvesting process operates on  a 
centralised model, with multiple subportals interconnected under a single catalogue. 
—  Countries  report  that  they  ensure  compliance  with  DCAT-AP  by  leveraging  existing 

technical platforms or plug-ins designed with built-in DCAT-AP support. 

4.  The impact dimension ranked as the third best-performing category this year. It outranked the 
quality dimension for the first time and achieved the greatest year-on-year improvement for the 
second consecutive year. 
•  Nearly all Member States (96 %) – along with the majority of EFTA countries (two out of three) 
and candidate countries (three out of four) – now report having a national definition of open 
data reuse. 

•  Nearly all Member States (92 %) – along with all EFTA countries and three out of four candidate 

countries – report having a definition of open data impact. 

•  Compared with 2023, more Member States (up from 21 to 23) – along with two out of three 
EFTA countries and three out of four candidate countries – report having a methodology in 
place to measure the impact of open data in their country. These efforts are usually integrated 
into a general national strategy on open data. 

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2024 Open Data Maturity Report 

•  Key practices and trends are as follows. 

—  Compared with 2023, there has been an increase in collaboration between government, 

civil society and academia to create open data impact in countries. 

—  Compared  with  2023, more  countries  report  performing  activities  to  understand  which 
open datasets are being reused and how. The activities performed include, among others, 
conducting workshops with reusers, fielding surveys, leveraging web analytics and running 
feedback sessions with portal users. 

—  Awareness of reuse cases in the environmental domain has increased across the EU, EFTA 
and  candidate  countries,  highlighting  the 
importance  of  data  on  biodiversity, 
environmentally  friendly  cities,  climate  change  and  related  disasters,  and  energy 
consumption and renewables. 

Figure 3: Average EU-27 overall maturity score and score on each dimension, 2015–2024 

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2024 Open Data Maturity Report 

Spotlight on high-value datasets 

Member States are progressing towards applying the implementing regulation on HVDs, especially 
by inventorying datasets and preparing statistical, geospatial and meteorological datasets. 

The  implementing  regulation  on  HVDs,  which  entered  into  force  in  June  2024,  is  a  legislative 
framework  established  to  enhance  the  availability  and  usability  of  certain  datasets  with  significant 
value.  Estonia,  Lithuania,  Denmark,  Latvia,  Slovenia  and  Finland  are  leaders  among  the  Member 
States  in  implementing  the  HVD  requirements.  On  average,  Member  States  are  making  the  most 
progress  with  statistical  (80 %),  geospatial  (77 %)  and  meteorological  (75 %)  datasets.  Of  the 
underlying  technical  and  legal  requirements,  identifying  and  inventorying  HVDs  (83 %),  addressing 
legal barriers (77 %) and setting up new roles and workflows (77 %) are the most advanced. In general, 
requirements  related  to  technical  progress,  such  as  metadata  quality  (71 %),  machine-readable 
formats  through  application  programming  interfaces  (69 %)  and  bulk  download  (66 %)  are  less 
advanced. Nonetheless, these are significant increases compared with 2023. 

In 2024, 20 Member States (70 %) reported actively promoting HVDs on their national portals. Portals 
use editorial tools such as labels or tags to promote their visibility and encourage reuse by allowing 
users to select them specifically. Common approaches to promoting HVDs on national portals include 
incorporating filtering options to help users easily locate these datasets and deep-dive into one of the 
six HVD categories. Several countries have also created dedicated sections within their portals to allow 
users to scroll through all available HVD datasets and to inform them about HVDs, their significance 
and the latest developments in the field. 

Moreover, 17 Member States (63 %) report that they have implemented the DCAT-AP HVD tag on their 
open data portals. Countries report integrating existing HVDs in existing geoportals, providing seamless 
access to geospatial data. Furthermore, several countries with advanced geospatial and environmental 
data 
in  Europe  directive 
infrastructure  for  spatial 
(Directive 2007/2/EC) to ensure cross-border interoperability. Those who do not report implementing 
the DCAT-AP HVD tag report challenges regarding compliance across all public bodies and adapting 
their Comprehensive Knowledge Archive Network systems to implement requirements for HVDs. 

initiatives  report  using  the 

information 

In addition, 21 Member States (78 %) report that they have implemented other measures to ensure 
that HVDs are interoperable with datasets from other countries. Member States report communicating 
directly  with  other  countries’  data  providers  and  utilising  standardised  licences  or  data  formats  to 
encourage cross-border reuse. 

Furthermore, 19 Member States (70 %) report having implemented structured processes to monitor 
the reuse of data from HVDs. These monitoring practices generally involve leveraging national data 
portals. Many countries monitor the use of HVDs similarly to that of other datasets, employing usage 
analytics  and  portal  monitoring  frameworks  to  track  engagement  and  access.  Additionally,  several 
Member  States  adopt  more  proactive  measures,  such  as  holding  ad  hoc  meetings  with  public 
institutions to gain insights into HVD use, conducting interactive workshops to better understand user 
needs  and  mapping  various  use  cases,  particularly  those  that  highlight  the  application  of  HVDs  in 
scientific research. 

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2024 Open Data Maturity Report 

Outlook 

The dimensions of ODM are connected and, to some extent, have a sequential order. Policies must be 
in place to initiate the process of making data open and to establish the mandate of national open data 
teams. Portals can then be funded and developed to make the opened data discoverable. As more 
data  is  made  available,  more  robust  requirements  for  interoperability  emerge.  As  the  reuser 
community grows, it expects higher-quality data for more sophisticated reuse cases. These and other 
efforts encourage reuse of the available data. Some reuse cases have an impact on society. 

Regarding open data policy, all Member States have transposed the open data directive (Directive (EU) 
2019/1024)  in national law.  Member  States  have  established governance  structures  for open data, 
assigned  civil servants  specifically  to open  data  topics  and  built  systems  to  assist  data  holders  and 
address policy challenges. In the year ahead, Member States will continue to work to fully implement 
the implementing regulation on HVDs. 

Several Member States continue to modernise their portals or launch new ones with more advanced 
features.  However,  open  data  portal  features  remain  similar  to  those  available  in  2023,  with  the 
decrease  in  the  maturity  score  probably  related  to  the  higher  requirements  set  in  this  year’s 
questionnaire  and  the  removal  of  some  questions  about  high-maturity  features.  The  method 
underwent  a  planned  revision  to  ensure  its  continued  relevance  in  light  of  a  changing  open  data 
ecosystem, and policy and technological developments. 

Member States report having numerous workflows and automated processes for harvesting metadata 
and monitoring its quality on their portals. Nonetheless, the maturity score has decreased on average 
compared  with  2023.  Several  countries  had  lower  metadata  quality  scores  on  the  same  questions 
asked last year, perhaps reflecting more accurate insights from their processes and monitoring tools. 
Nonetheless, computed metrics of metadata quality can objectively assess the metadata. In the first 
attempt to do so, this year’s report used the metadata quality assessment tool of data.europa.eu to 
evaluate the metadata harvested by the initiative. The results are summarised in this report as a pilot 
indicator. 

Finally,  performance  on  the  impact  dimension  continues  to  improve.  Member  States  are  further 
increasing their activities to document  the  reuse of open data, which  has translated  into a greater 
awareness of available reuse cases. Although countries have a fair collection of examples of open data 
being reused for new purposes, systematic assessments of the impact created through this reuse are 
largely unavailable at the country level.

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2024 Open Data Maturity Report 

Chapter 1: Introduction 

Background: open data policy in the European Union 

The open data directive (Directive (EU) 2019/1024) encourages EU Member States to make as much 
publicly  accessible  information  as  possible  available  for  reuse.  The  directive  is  ‘recast’,  meaning  it 
brings together the original directive on public sector information (Directive 2003/98/EC) and all the 
amendments made to it in a single legal act. 

The core principle of the directive is to promote the reuse of information that is already being collected 
for government purposes, thus generating additional value once it is reused for different purposes. 
Therefore, the directive sets out a minimum standard for harmonising national rules and practices, 
aiming to reduce obstacles and promote reuse of public sector information to drive innovation. When 
it entered into force in 2019, the directive also answered the need to update the legislative framework 
in line with the fast-paced evolution of digital technologies, especially artificial intelligence. 

Furthermore, the open data directive embraces the potential to generate important social, economic 
and environmental benefits through innovative applications of generally accessible public information. 
These benefits are pursued in particular by introducing the concept of high-value datasets (HVDs). The 
implementing regulation on HVDs (Commission Implementing Regulation (EU) 2023/138) specifies six 
specific categories of HVDs: geospatial, earth observation and environment, meteorological, statistics, 
companies  and  company  ownership,  and  mobility.  Due  to  the  importance  of  these  datasets,  the 
regulation lays down rules ensuring their accessibility free of charge and in machine-readable formats. 
HVDs must be made available for reuse with minimal legal and technical restrictions. Moreover, public 
sector bodies have the obligation to make them available through application programming interfaces 
and, where relevant, as a bulk download. The implementing regulation entered into force in June 2024, 
and EU Member States will report on their progress in applying it to the European Commission every 
two years starting from February 2025. 

Not  all  public  sector  information  can  be  released  as  open  data.  For  example,  some  information  is 
classified as confidential and sensitive, or the public administration that holds it may not have all the 
necessary  rights  to  permit  others  to  reuse  it.  Other  legislation,  such  as  the  Data  Governance  Act 
(Regulation  (EU)  2022/868)  and  the  Data  Act  (Regulation  (EU)  2023/2854),  includes  measures  to 
stimulate  the  reuse  of  public  sector  information  through  specific  access  regimes.  The  European 
Register for Protected Data held by the Public Sector provides relevant information on what  data is 
held by public authorities in the Member States, and registers are progressively being made available 
at data.europa.eu. 

Measuring open data in Europe 

Under  the  data.europa.eu  initiative,  the  Publications  Office  of  the  European  Union  and  the 
Directorate‑General  for  Communications  Networks,  Content  and  Technology  have  conducted  an 
annual benchmarking exercise, by means of a survey of national representatives, since 2015 to assess 
the maturity of the open data landscape in Europe. The objective of this open data maturity (ODM) 
assessment is to evaluate the development of countries in the field of open data and to document 
their year-on-year progress. The assessment measures each country’s progress in making public sector 
information  available  and  stimulating 
its  reuse.  The  assessment  furthermore  supports  the 
development of open data best practices across Europe, serving as a tool for knowledge sharing. 

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2024 Open Data Maturity Report 

Thirty-four  European  countries  participated  in  the  2024  ODM  assessment.  These  countries  are 
grouped into Member  States  of the  European Union (the  EU-27), European Free  Trade  Association 
(EFTA) countries and candidate countries for EU membership. 

•  The  Member  States  are  Belgium,  Bulgaria,  Czechia,  Denmark,  Germany,  Estonia,  Ireland, 
Greece, Spain, France, Croatia, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, 
the Netherlands, Austria, Poland, Portugal, Romania, Slovenia, Slovakia, Finland and Sweden. 

•  The EFTA countries are Iceland, Norway and Switzerland. 
•  The candidate countries are Bosnia and Herzegovina, Albania, Serbia and Ukraine. 

The structure of this report 

This report provides an analysis of the 2024 survey data. The findings of this analysis are presented in 
several chapters. 

•  Chapter 2 summarises how the assessment measures ODM. 
•  Chapter 3 describes the overall results of the assessment. 
•  Chapters 4–7 discuss the findings of the assessment for each of the four dimensions of ODM: 

—  policy (Chapter 4), 
—  portal (Chapter 5), 
—  quality (Chapter 6), 
—  impact (Chapter 7). 

•  Chapter 8 clusters the participating countries into four groups according to their overall 

performance and outlines recommendations for each cluster. 

•  Chapter 9 concludes with the key messages of the 2024 assessment. 

In  addition  to  this  report  and  the  method  appendix,  the  associated  raw  and  processed  data  are 
published online. Furthermore, factsheets are published giving an overview of the situation in each 
participating country. 

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2024 Open Data Maturity Report 

Chapter 2: Methodology 

The  open  data  maturity  (ODM)  assessment  evaluates  progress  and  effectiveness  of  open  data 
initiatives across four thematic dimensions that are intended to capture the end-to-end value chain of 
open data: policy, portal, quality and impact. The annual assessment was conducted for the first time 
in 2015, and this is the 10th edition. The four dimensions in the current methodology have been used 
since 2018. Over time, the questions asked to assess the four dimensions have been revised to adapt 
to policy changes and the progress of European countries in their ODM. Each of the four dimensions is 
subdivided into indicators, which are subthemes of the dimensions. The definitions of the four open 
data dimensions are summarised in Table 1. 

Table 1: Dimensions of the ODM methodology and their indicators 

Dimension 

Description 

Policy 

Portal 

Quality 

Investigates  the  open  data  policies  and  strategies  in  place  in  the  countries,  the 
national governance models for managing open data, and the measures applied to 
implement  those  policies  and  strategies.  To  evaluate  these  elements,  the 
dimension  comprises  three  indicators:  (a)  policy  framework,  (b)  governance  of 
open data and (c) open data implementation. 

Investigates  the  functionality of  national open  data portals,  the  extent  to  which 
users’ needs and behaviour are examined to improve the portal, the availability of 
open  data  across  different  domains  and  the  approach  to  ensuring  the  portal’s 
sustainability.  To  evaluate  these  elements,  the  dimension  comprises  four 
indicators: (a) portal features, (b) portal usage, (c) data provision and (d) portal 
sustainability. 

Assesses  the  measures  adopted  by  portal  managers  to  ensure  the  systematic 
harvesting of metadata, the monitoring of metadata quality and compliance with 
the  DCAT-AP  metadata  standard,  and  the  quality  of  the  deployment  of  the 
published  data  on  the  national  portal.  This  dimension  provides  an  overarching 
incentive for portal managers and policymakers to ensure that open data on the 
national portal has suitable formats and correct licences, is machine-readable, is 
high  quality  and  is  amenable  to  a  linked  data  approach.  To  evaluate  these 
elements,  the  dimension  comprises  four  indicators:  (a)  metadata  currency  and 
completeness,  (b)  monitoring  and  measures,  (c)  DCAT-AP  compliance  and  (d) 
deployment quality and linked data. 

Impact 

Analyses the willingness, preparedness and ability of countries to measure both the 
reuse of open data and the impact created through this reuse. To evaluate these 
elements,  the  dimension  comprises  three  indicators:  strategic  awareness,  (b) 
measuring reuse  and (c) created impact,  within the areas of (i) government, (ii) 
society, (iii) environment and (iv) economy. 

Data  for  the  assessment  is  collected  through  a  voluntary  questionnaire  sent  to  the  open  data 
representatives of the participating countries, working in collaboration with the European Commission 
and  the  Expert  Group  on  Public  Sector  Information.  Countries  are  asked  questions  about  their 

15 

 
 
2024 Open Data Maturity Report 

processes,  activities,  initiatives and other demonstratable outputs  that  characterise a mature open 
data  ecosystem.  Questions  with  available  data  from  the  previous  year  were  pre-filled  in  the 
questionnaire, allowing respondents to either confirm the validity of last year’s answers or provide 
updated information. This feature was newly introduced in 2024 to support year-on-year consistency 
in responses. 

Once the completed questionnaires are submitted, the research team validates the responses based 
on the explanations and supporting evidence provided by the survey respondents for each question. 
The reviewers assess whether the explanations accompanying the answers are complete, relate to the 
question and sufficiently justify the response selected. A consultation round is held with the survey 
respondents to gain clarifications on the survey data and to give them the opportunity to validate the 
results. 

In 2024, the methodology underwent an update, as it does periodically. The dimensions and indicators 
remain  unchanged  from  the  previous  version of  the  methodology.  However,  some  questions  were 
removed, some questions were revised or the requirements for evidence reformulated, and some new 
questions were added. This was done to ensure that the questions remain relevant, do not overlap 
and reflect the evolution of the open data ecosystem over time. Moreover, the allocation of scores to 
questions within each dimension was rebalanced to ensure that questions are equally weighted, with 
a limited number of exceptions having higher or lower weighting. 

The  following  are  the  main  changes  for  each  dimension.  In  the  policy  dimension,  more  detailed 
explanations were requested regarding the national governance structure, and a question was added 
about  the  processes  in  place  to  update  policies/strategies.  In  the  portal  dimension,  some  mature 
portal  functionalities,  such  as  search  and  download,  were  removed  from  the  questionnaire.  More 
detailed explanations were requested regarding how data about portal usage and user feedback are 
used  to  improve  the  portal.  In  the  quality  dimension,  more  detailed  explanations  were  requested 
regarding the workflows and activities of the portal team to ensure that several aspects of high-quality 
metadata  are  achieved.  Some  questions  about  the  type  of  support offered  to  data  providers were 
merged due to overlapping responses from survey respondents. No major changes were made to the 
impact dimension, except that survey respondents needed to provide only one example of a reuse 
case for each category (instead of a maximum of three) and explain that case in more detail. Questions 
about high-value datasets were added across all dimensions. 

In  addition,  two  automated  pilot  indicators  were  introduced  to complement  the  qualitative  survey 
data with quantitative metrics. One pilot indicator used automated web-based tests to evaluate the 
performance of portals on metrics related to mobile friendliness, speed and performance, security, 
and web content accessibility. The other pilot indicator used calculated metrics from the  metadata 
quality assessment to evaluate the quality of metadata harvested by data.europa.eu. The methodology 
underlying the assessment is undergoing recalibration. However, it is a promising approach that could 
help  in  assessing  metadata  quality  in  an  automated  way.  The  tool  would  need  to  undergo  further 
scrutiny to ensure more objective reporting in the future. These pilot indicators did not contribute to 
countries’ maturity scores. Please refer to the method appendix for full details of the methodology. 

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2024 Open Data Maturity Report 

Chapter 3: Overall open data maturity 

In 2024, countries across Europe continued, on average, to improve their open data maturity (ODM). 
The average score for all participating countries rose by 1 percentage point (pp) from 2023, reaching 
80 % in 2024. The EU-27 average remained the same as in 2023, at 83 %, despite an update to the 
method for the assessment that introduced stricter requirements and some new questions (Figure 4). 
France (100 %), Poland (98 %) and Ukraine (97 %) remain in the top three positions. The fourth spot 
in 2024 is taken by Slovakia (96 %), which increased its score by 4 pp from the previous year. Czechia, 
in eighth position (94 %), is the only new entrant into the top 10 since last year. The maturity scores of 
countries in the top 10 are within a 6 pp range of each other, demonstrating the similarly high levels 
of maturity of these  countries. This narrow  range also arises from countries  continuing to improve 
year-on-year. Overall, 18 participating countries improved their maturity level over the past year, one 
country remained at the same level and 15 countries experienced a drop in their overall maturity score. 

3.1. EU Member State trends 

The stability of the EU average overall maturity score at 83 % is attributed to a mixed performance 
across the dimensions, with some showing increases while others experiencing declines. Specifically, 
increases were  experienced  in  the  impact  (+ 4 pp)  and  policy  (+ 2 pp)  dimensions,  while  decreases 
were experienced in the portal (– 3 pp) and quality (– 3 pp) dimensions. The policy dimension remains 
the most mature dimension (91 %), followed by the portal (82 %) and impact (80 %) dimensions. The 
quality dimension is the least mature dimension on average (79 %). 

The biggest climber is Latvia, which increased its score by 10 pp compared with 2023. Latvia’s rise in 
overall  score  is  driven  by  increases  in  its  scores  on  the  impact  (+ 21 pp)  and  quality  (+ 10 pp) 
dimensions. Latvia also improved in the policy (+ 7 pp) and portal (+ 3 pp) dimensions. The second-
largest climber is Croatia, which increased its score by 9 pp. Croatia improved the most in the impact 
dimension (+ 17 pp), followed by the portal (+ 14 pp) and policy (+ 10 pp) dimensions. The third-largest 
climber is Czechia, which increased its score by 6 pp compared with 2023. There was no change in the 
quality  and  impact  dimensions;  this  increase  in  Czechia’s  score  was  driven  by  a  significant 
improvement in the portal dimension (+ 20 pp) and a 5 pp increase in its score on the policy dimension. 

The largest decreases were experienced by Bulgaria (– 13 pp), Germany (– 10 pp) and Finland (– 5 pp). 
The update to the assessment method could have influenced these decreases in maturity scores. In 
total, 13 Member States experienced decreases in their overall maturity scores. 

3.2. European Free Trade Association country trends 

In this year’s ODM assessment, Switzerland increased its overall score by 1 pp to an overall maturity 
score of 80 % in 2024. This increase in Switzerland’s overall score was driven by its improvement of 
5 pp in the policy dimension, 3 pp in the impact dimension and 1 pp in the quality dimension. Although 
Iceland’s  overall  maturity  score  decreased,  the  country  did  report  increases  in  its  scores  on  the 
underlying policy and impact dimensions. 

3.3. Candidate country trends 

All  four  candidate  countries  participating  in  this  year’s  ODM  assessment  improved  their  overall 
maturity score from the previous year. Ukraine (97 %) remains the most mature candidate country, 
followed  by  Serbia  (84 %).  Among  the  candidate  countries,  Serbia  had  the  most  significant  annual 
increase in overall score  (+ 9 pp). This increase was driven by notable  improvements in the  impact 

17 

 
2024 Open Data Maturity Report 

(+ 16 pp) and quality (+ 17 pp) dimensions. Albania also improved its overall maturity score by 5 pp, 
achieving a maturity score of 47 %. 

Read the analyses by dimension in the following chapters for further details on the factors underlying 
these trends. 

Figure 4: In 2024, the EU average remained at 83 %, and the average for all participating countries 
increased by 1 pp to 80 %. (EFTA: European Free Trade Association; YoY: year-on-year). 

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2024 Open Data Maturity Report 

Chapter 4: Open data policy 

Over the years, the EU has developed a comprehensive policy framework to accelerate the opening of 
data held by the public sector, namely to enhance its accessibility and usability for citizens, businesses 
and researchers. The open data directive (Directive (EU) 2019/1024) is the most recent framework for 
open data policy in the EU. The directive, which had to be transposed into EU Member States’ national 
laws by July 2021, aims to enhance the openness and utility of public sector data through requirements 
such as: 

• 

• 

• 

stimulating  the  publishing  of  dynamic  data  and  the  uptake  of  application  programming 
interfaces (APIs); 
limiting the exceptions under which public bodies may charge more than the marginal costs of 
dissemination for the reuse of their data; 
strengthening the transparency requirements for public–private agreements involving public 
sector information; 

The directive applies to a wide range of information (e.g. written texts, databases and audio files) held 
by Member States’ public sector bodies, public authorities, publicly  owned companies and publicly 
funded research initiatives. 

The  directive  also  introduced  the  concept of  high-value  datasets  (HVDs),  which  are  public  datasets 
associated with important socioeconomic benefits for society, the environment and the economy. The 
related implementing regulation (Commission Implementing Regulation (EU) 2023/138) sets out rules 
to ensure that certain datasets included in the thematic categories defined in the regulation are made 
available free of charge,  in machine-readable formats, through APIs and, where  relevant, as a bulk 
download. 

The  policy  dimension  of  the  open  data  maturity  (ODM)  assessment  is  designed  to  encourage  the 
practical implementation of policy measures. Governance structures, operating models, processes and 
activities are needed to realise the ambitions outlined in policies and strategies. 

In brief, the policy dimension investigates countries’ policies and strategies regarding open data, the 
national governance models for managing open data and the measures deployed to implement the 
policies and strategies. Table 2 summarises the key elements of the policy dimension. 

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2024 Open Data Maturity Report 

Table 2: Indicators of the policy dimension 

Indicator 

Key elements 

Policy framework 

Governance of 
open data 

Open data 
implementation 

An open data policy and strategy are in place at the national level to provide 
a long-term strategic vision and action plan for open data. The strategies 
incentivise open data reuse in both the public and private sectors and access 
to real-time, geospatial and citizen-generated data. Activities regarding 
HVDs are in place. 

Governance models and regular coordination activities across public sector 
bodies are in place to ensure open data publication at all government levels 
and to support local and regional open data initiatives. Regular exchanges 
occur between open data providers and reusers from academia, businesses 
and other non-governmental organisations. 

Data publication plans and implementing processes exist. The number of 
public bodies that charge above the marginal costs of dissemination for the 
reuse of their open data is monitored. Training activities for civil servants 
working with data are organised, as are society-wide open data literacy 
initiatives. 

This  chapter  will  first  present  overall  performance  on  the  policy  dimension  and  then  provide  a 
summary of the results and best practices for each indicator. 

Contents 

4.1. Overall performance on the policy dimension ......................................................................... 21 

4.2. Policy framework ....................................................................................................................... 25 

Open data policies and strategies ................................................................................................. 25 

Open data action plans.................................................................................................................. 28 

Incentives for data publication and access ................................................................................... 30 

Supporting the reuse of open data ............................................................................................... 32 

Data inventories ............................................................................................................................ 34 

Prioritising high-value datasets ..................................................................................................... 36 

4.3. Governance of open data .......................................................................................................... 39 

Governance structures .................................................................................................................. 39 

Local and regional governance structures .................................................................................... 41 

Outlining open data roles and responsibilities .............................................................................. 43 

Network of open data team, officers and reusers ........................................................................ 45 

4.4. Open data implementation ....................................................................................................... 47 

Data publication plans ................................................................................................................... 47 

Implementation plans and monitoring processes ......................................................................... 48 

Monitoring charging practices relating to open data ................................................................... 50 

Data literacy training and open data publication activities .......................................................... 50 

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2024 Open Data Maturity Report 

4.1. Overall performance on the policy dimension 

According to the EU-27 average in 2024, the policy dimension remains the most mature dimension of 
the  ODM  assessment,  scoring  9 percentage  points  (pp)  higher  than  the  second-ranked  portal 
dimension. The average maturity of Member States in the policy dimension in 2024 is 91 % (Figure 5). 
This  represents  a  2 pp  increase  from  2023,  marking  the  first  time  that  the  maturity  score  for  this 
dimension has surpassed 90 %. This increase has primarily been driven by the 4 pp rise in the ‘open 
data implementation’ indicator, which showed the largest growth among the three policy indicators, 
reaching  92 %.  The  ‘policy  framework’  indicator  also  increased  (+ 2 pp),  reaching  90 %  maturity 
(Figure 5). 

In  terms  of  individual  country  performance,  Estonia  (100 %),  France  (100 %),  Italy  (100 %),  Poland 
(100 %)  and  Ukraine  (100 %)  are  tied  for  first  place  in  this  dimension  (Figure 6).  Czechia  (99.2 %), 
Ireland (99.2 %) and Cyprus (99.2 %) are a close second, all scoring full points on the ‘policy framework’ 
indicator. Cyprus scored full points on the ‘governance of open data’ indicator, and Czechia and Ireland 
scored full points on the open data implementation indicator. Overall, 16 Member States scored above 
the EU-27 average of 91 %. 

Highlight from Estonia – training programmes for civil servants’ data competencies 

An important practice observed as part of this year’s report is that countries are creating structured 
training programmes to develop their civil servants’ data competencies. 

One notable example is Estonia, which is implementing a comprehensive strategy for strengthening 
the data skills of its civil servants and ensuring effective data management and open data practices 
across the public sector. 

In 2024, Estonia aimed to train over 2 500 data specialists across 10 targeted training sessions and 
between one and four online courses. This training aimed to cover key areas such as data quality 
and open data publication, contributing to improved national open data standards. Already, open 
data licensing training by Creative Commons and a data working group webinar have been held. 

Estonia  has  also  introduced  detailed  competency  profiles  for  data  engineers  and  analysts  and  is 
currently  developing  a  profile  for  data  stewards.  These  profiles  serve  as  the  foundation  for 
nationwide training programmes and provide input for higher education curricula, ensuring future 
civil servants are equipped with relevant skills. 

This best practice contributes to Estonia’s excellence across all three policy dimension indicators, 
particularly in the ‘open data implementation’ indicator. Read more about this trend in Section 4.3. 

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2024 Open Data Maturity Report 

Figure 5: The EU-27 average score on the policy dimension has risen steadily over the past three years 
(2022–2024) 

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2024 Open Data Maturity Report 

Figure 6: Twenty participating countries improved their score on the policy dimension in 2024. (EFTA: 
European Free Trade Association; YoY: year-on-year). 

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2024 Open Data Maturity Report 

Portugal  (+ 19 pp),  Croatia  (+ 10 pp)  and  Albania  (+ 9 pp)  showed  the  greatest  year-on-year 
improvement in the policy dimension. Portugal’s increased score can be attributed to its significant 
progress across all three indicators. Namely, it achieved the second-highest improvement in the ‘policy 
framework’ indicator, which can be attributed to its recent addition of an open data strategy and its 
open data policies outlining measures to incentivise the publication of and access to citizen-generated 
data, fostering the discoverability of open data on data.europa.eu and outlining measures to support 
the reuse of open data by the private sector. Portugal also achieved the second-highest increase in the 
‘open data implementation’ indicator, which can be attributed to the recent addition of its governance 
structure ensuring the facilitation of local and regional open data initiatives at the national level and a 
publicly  accessible  document  outlining  their  country’s  open  data  governance  structures.  Finally, 
Portugal achieved the greatest improvement in the ‘governance of open data’ indicator, which can be 
attributed to its recent addition of having publication plans for open data at the public body level and 
processes for ensuring that its open data policies and strategy are implemented. 

Highlight from Portugal – sector-specific citizen-driven data initiatives 

One of  the  trends  highlighted  in  this  year’s  report  is  the  inclusion of  sector-specific  initiatives  in 
national policies and strategies aimed at promoting citizen-generated data. 

For  example,  Portugal  has  outlined  key  measures  to  ensure  open  data  and  data  reuse  in  its 
transversal action plan for public administration digital transformation (part of the broader strategy 
for public administration digital transformation for 2021–2026). A central priority is establishing and 
maintaining  an  open  data  ecosystem  that  actively  engages  multiple  stakeholders.  Portugal 
promotes this initiative, in part, through citizen science projects that encourage public participation 
and collaboration in the open data space. In the field of marine biology, several entities in Portugal, 
both  governmental  and  non-governmental,  including  non-profit  organisations,  collaborate  with 
public bodies to actively involve citizens in data-generation efforts. 

A  notable  example  is the  Algarve  Centre  of Marine  Sciences  (CCMAR),  one  of Portugal’s  leading 
marine research centres, which collaborates closely with the public Portuguese Institute for Sea and 
Atmosphere (IPMA). The  Algarve Centre of Marine  Sciences encourages citizens to contribute  to 
marine conservation efforts. For example, the New Marine Species of the Algarve (NEMA) project 
invites citizens to report sightings of non-native marine species in the Algarve. At the same time, the 
Algarve  Stranding  Network  (RAAIg)  gathers  public  reports  of  stranded  marine  animals,  such  as 
dolphins and turtles, to monitor marine health. Citizens are also encouraged to report algal blooms, 
which can indicate ecological disturbances, and to document benthic species for the Marine Forests 
project  via  platforms  like  iNaturalist.  Additionally,  the  Biomares  programme  fosters  community 
involvement  by  inviting  public  observations  of  marine  life  in  the Professor Luiz  Saldanha  Marine 
Park, promoting biodiversity conservation efforts. 

Read more about this trend in Section 4.2. 

Croatia’s increased score on the policy dimension can be attributed to its 19 pp increase in the ‘policy 
framework’ indicator, which was the highest increase among all countries, as well as its reporting of a 
regular exchange of knowledge and experiences between its national open data team and the wider 
network of open data officers. Albania’s increased score on the policy dimension can be attributed to 
its 27 pp increase in the ‘open data implementation’ indicator, which was the second-highest increase 
among all countries, as well as its recent addition of measures for supporting the reuse of open data 
by the public sector in its national policies/strategy.

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2024 Open Data Maturity Report 

Highlight from Croatia – Working Group for the Coordination of State Information Infrastructure 
Projects and Digital Transformation 

Establishing  working  groups  is  a  particularly  common  method  that  countries  use  to  facilitate 
exchanges between the national open data team and the wider network of open data officers. 

For example, Croatia fosters collaboration across government bodies through the Working Group 
for the Coordination of State Information Infrastructure Projects and Digital Transformation. This 
group, which includes representatives of various governmental entities responsible for digitalisation 
such as the open data team and open data officers, meets regularly to discuss updates and share 
progress on digital transformation initiatives. 

Read more about this trend in Section 4.2. 

Ten countries’ scores on the policy dimension decreased year-on-year. In general, such decreases may 
have been influenced by new questions in the survey that asked for further details about governance 
structures and by the updating of policies and strategies compared with the previous year. 

4.2. Policy framework 

The  ‘policy  framework’  indicator  evaluates  open  data  policies,  strategies  and  action  plans  at  the 
national,  regional  and  local  levels.  Specifically,  this  indicator  investigates  whether  concrete 
mechanisms are in place to support the publication of, access to, discoverability of and reuse of several 
data types, including real-time, geospatial and citizen-generated data. 

Open data policies and strategies 

National open data policies are formalised rules and guidelines that govern open data within a country. 
In the case of Member States, national policies should include legislative measures to comply with the 
open data directive, ensuring the reuse of public sector information and promoting interoperability 
and fair access to open data across the EU. On the other hand, open data strategies are principles and 
goals  that  countries  want  to  achieve  in  the  field  of  open  data  based  on  their  open  data  policies. 
Furthermore,  regional  and  local  policies  and  strategies  play  a  crucial  role  in  promoting  open  data 
initiatives that reflect local priorities. In addition, they are often effective  in addressing the unique 
barriers to open data publication and reuse faced by subnational governments and their constituents. 
These subnational initiatives can complement national policies, focusing on the implementation and 
execution  of  open  data  practices  tailored  to  regional  governance  structures.  Table 3  presents  an 
overview of how countries responded to the questions on this topic.

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2024 Open Data Maturity Report 

Table 3: Countries’ responses to questions on open data policies and strategies 

Is there a national open 
data policy? 

Is there a national open 
data strategy? 

EU-27 

All 27 (100 %) Member 
States report having an 
open data policy. 

EFTA 

All three participating 
EFTA countries report 
having an open data 
policy. 

Candidate  All four participating 
candidate countries 
report having an open 
data policy. 

26 Member States (96 %) 
report having a stand-alone 
national open data strategy 
or relevant open data-
related objectives, actions 
and timelines incorporated 
within broader national 
policies. Portugal is a 
recent addition to the 
group. Romania did not 
report having an open-data 
strategy. 

Norway and Switzerland 
report having a national 
open data strategy, while 
Iceland reports that 
relevant open-data-related 
objectives are incorporated 
within its broader national 
policies. 

Albania and Ukraine report 
having a national open data 
strategy, while Serbia 
reports that relevant open-
data-related objectives are 
incorporated within its 
broader national policies. 

Is there an open data 
policy/strategy at the 
regional or local level? 

20 Member States (74 %) 
report having an open data 
policy/strategy at the 
regional or local level. Four 
Member States (14 %) 
responded ‘not applicable’ 
due to the specific 
governance structures in 
place (e.g. having a small 
country size). 

Iceland and Switzerland 
report having an open data 
policy/strategy at the 
regional or local level. 
Norway responded ‘not 
applicable’, as its national 
strategy is developed in 
collaboration with relevant 
local and regional 
authorities. 

Serbia and Ukraine report 
having an open data 
policy/strategy at the 
regional or local level. 

(Questions P1, P2 and P3) 

Almost  all  participating  countries  have  either  a  dedicated  national  open  data  policy  or  a  national 
framework addressing data, digitalisation, artificial intelligence (AI), e-government or similar areas that 
explicitly  incorporates  open  data  within  its  text  and  scope.  In  particular,  all  Member  States  have 
implemented the open data directive, either as stand-alone policies (e.g. the Netherlands’s Law on the 
Reuse of Public Information) or as amendments to existing laws (e.g. Croatia’s amendment of its Free 
Access to Information Act No 106/1999 Col.). 

Several  countries  take  a  broader  approach  by  incorporating  open  data  provisions  within  wider 
legislative  frameworks  on data  and  digital  transformation.  For  example,  Bulgaria  has  integrated  its 
open data initiatives into a comprehensive legal framework through the Access to Public Information 
Act, which aims to enhance transparency and accessibility across the public sector. This trend extends 

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2024 Open Data Maturity Report 

beyond the Member States, with countries such as Serbia also incorporating open data policies into 
their broader digital governance strategies through legislation (the Law on Electronic Government). 

A similar trend is seen in open data strategies. Although several countries develop specific strategies 
in line with their commitment to their open data policies, several do this as part of broader plans. For 
example, Denmark notes that its national open data strategy is to be expressed through one of seven 
themes making up its comprehensive National Strategy for Digitisation (2024–2027). This is seen at 
both the national and the regional/local level, such as strategies relating to general development, as 
seen in Ponferrada (Spain) and Reykjavik (Iceland); smart cities, exemplified by Budapest (Hungary), 
Prague  (Czechia)  and  Priboj  (Serbia);  or  general  digitalisation  of  government,  such  as  in  Utrecht 
(Netherlands), Helsinki (Finland) and Geneva (Switzerland). 

Most national open data policies commit to making public sector data openly available by default. This 
trend is then reflected in the goals and principles outlined in many national open data strategies. Often, 
in cases  such as  Cyprus, Czechia,  France,  Ireland,  Lithuania,  Slovenia, Sweden  and Ukraine, this is 
established through public information laws legally mandating citizens’ rights to request and obtain 
data. This ‘open by default’ principle is also frequently cited in national strategies. Namely, strategies 
in Austria, Czechia, Germany, Ireland, Norway, Slovenia and Ukraine explicitly advocate for treating 
official documents as public resources that should be readily available to citizens (with exceptions for 
restricted data) when outlining priorities and objectives. 

National policies also often cite the promotion of innovation as a driver for implementing open data 
legislation (e.g. in Albania, Finland, Lithuania, Slovenia and Sweden). These policies emphasise that 
greater  access  to  data  can  help  stimulate  research,  improve  public  services  and  facilitate  the 
development of data-driven solutions across various sectors. 

Many national open strategies share the following key themes. 

1.  Collaboration with stakeholders 

One frequently cited aspect of national strategies is engaging citizens more. There tends to be a focus 
on engaging the public and raising awareness about the importance and benefits of open data, often 
involving educational initiatives and participatory platforms. For example, Switzerland emphasises the 
importance of involving the public and stakeholders in implementing its open government data (OGD) 
master  plan,  including  fostering  transparency  and  data  accessibility.  Slovenia’s  strategy  includes 
specific plans to raise public awareness and enhance digital skills, recognising that informed citizens 
are crucial for utilising open data effectively. Lithuania aims to promote open data literacy among the 
public, focusing on education and engagement to ensure citizens understand open data’s benefits. 

Establishing  a  ‘data  ecosystem’  is  another  recurring  theme,  which  involves  engaging  groups  of 
stakeholders beyond individual citizens. The national strategies of Norway and Slovenia, for example, 
use the term data ecosystem when outlining objectives for fostering digital collaborations between 
data providers, analysts  and developers with a common set of information technology solutions to 
enhance data quality. On the other hand, Spain and Portugal mention data ecosystems in the context 
of intending to generate connections between the actors of the national and international open data 
ecosystems (e.g. European data system), ensuring an alignment with standards of data and enhancing 
opportunities for innovation. 

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2024 Open Data Maturity Report 

2.  Sector-specific data 

Another common theme across both national and regional/local strategies is the emphasis on specific 
sectors and  the  creation of  targeted  datasets  tailored  to  the  needs of  particular  stakeholders. This 
trend is most prominent at the national level in terms of reuse and API access to geospatial data. The 
infrastructure  for  spatial  information  in  Europe  (Inspire)  directive  (Directive  2007/2/EC),  an  EU 
initiative, plays a central role in establishing a spatial data infrastructure to support environmental 
policies  and  activities.  This  directive  ensures  that  spatial  datasets,  such  as  maps  and  geographical 
information, are accessible via network services. Countries such as Italy, Norway and Slovenia have 
highlighted access  to and the  promotion of geospatial data reuse as key priorities  in their national 
strategies. 

This trend is also observed at the regional level. For example, Prague’s 2030 strategy outlines plans to 
promote open data to leverage it for innovations by public and private sector organisations in sectors 
like mobility, energy and tourism. Furthermore, the municipality of Cēsu’s (Latvia) strategic plan for 
data outlines its objective of publishing open data, mentioning that the private sector reuse of data 
from the health, transport and environment sectors can enable innovations for public benefit. 

3.  Ethical guidelines and other protections 

Open data policies, such as those from Albania, Finland, Ireland, Lithuania and Ukraine, emphasise 
the  importance  of  privacy  and  data  protection  within  the  context  of  their  open  data  policies.  The 
policies often note that safeguarding sensitive and personal information, as well as the overall privacy 
rights of citizens, is a fundamental right to balance with the aim of promoting transparency and open 
public data. The development of legal frameworks and ethical guidelines to govern the use of open 
data is also reflected in many national open data strategies. 

Open data action plans 

An  open  data  action  plan  typically  outlines  the  specific  measures  and  steps  that  need  to  be 
implemented to achieve the goals set by the national open data strategy or policy. It includes detailed 
actions, timelines and the responsible parties for carrying out these measures. Countries frequently 
use their action plans to enhance data publication, ensure quality, improve accessibility and promote 
reuse  while  also  incorporating  innovative  aspects,  for  example  emerging  technologies  such  as  AI. 
Table 4 presents an overview of how countries responded to the question on this topic. 

Table 4: Countries’ responses to the question on open data action plans 

EU-27 

EFTA 

Does  the  national  strategy/policy  include  an  action  plan  with  measures  to  be 
implemented in the open data field? 
25 Member States (92 %), all except Croatia and Romania, report that their national 
strategy/policy includes an action plan with measures to be implemented in the open 
data field. 

Iceland, Norway and Switzerland report that their national strategy/policy includes 
an action plan with measures to be implemented in the open data field. 

Candidate 

All  four  participating  candidate  countries  report  that  their  national  strategy/policy 
includes an action plan with measures to be implemented in the open data field. 

(Question P4) 

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The most common element of action plans is a strong focus on publishing more open data, ensuring 
that  data  is  accessible,  reusable  and  regularly  updated.  Several  countries  also  emphasise  the 
importance  of  maintaining  high-quality  standards  for  open  datasets  and  their  corresponding 
metadata. Czechia, Ireland and Slovakia highlight that prioritising the publication of HVDs is a key part 
of  their  action  plans.  Czechia  and  Luxembourg  also  highlight  action  points  for  enhancing  data 
accessibility by ensuring interoperability between systems. 

Some countries also emphasise the importance of monitoring the usage and impact of open data and 
of  providing  public  dashboards  and  reports  on  the  effectiveness  of  their  open  data  policies.  For 
example, France and Iceland require each ministry or public body to set up data roadmaps and timed 
plans for data disclosure. Czechia, Germany, Luxembourg and Poland undertake regular reporting and 
progress  monitoring  and  emphasise  that  these  are  key  components  of  their  open  data,  with 
Luxembourg even publishing the results of its monitoring via a public dashboard. Similarly, Ireland and 
Spain place emphasis on tracking the impact and quality of open data usage in their countries, with 
Spain publishing Microsoft Power BI reports on the activity of its national open data platform and its 
national open data catalogue, while Ireland provides insight reports into how open data is being used. 

Several action plans have points regarding data reuse, helping users derive insights from open data. 
Namely, Ireland plans to create data visualisation capability in its national open data portal, and Malta 
has  measures  to  improve  the  readability  of  open  data.  In  addition,  Spain’s  action  plan  includes 
presenting research studies on its portal website, which provides a step-by-step account of how to 
perform analyses and create visualisations using open data, outlining which analytical tools to use. 

Many countries also include innovative action points in their plans. Specifically, Luxembourg wants to 
collaborate with its AI4Gov programme to foster the availability of open datasets that can be used for 
AI. Norway outlines actions such as developing a strategy for AI and establishing a national toolbox for 
data  sharing.  Additionally,  Spain  has  action  points  for  improving  its  national  open  data  portal  by 
incorporating capabilities relating to data spaces, further aligning with EU data rules. 

Highlight from Spain – promoting open data through social media 

As part of Spain’s 2024–2025 action plan for the national open data policy, the country has adopted 
an innovative approach to raise awareness of open data’s value among younger generations. This 
involves using social media to disseminate open data content, specifically targeting audiences aged 
16 to 35 years. This strategy expands the reach of open data and fosters greater engagement with 
younger citizens, promoting the value of data as a public asset. 

In  addition,  Spain  is  leveraging  the  power  of  podcasts  by  developing  interviews  with  open  data 
experts.  These  interviews,  lasting  15  to  20 minutes,  will  be  accompanied  by  short  promotional 
videos (three to four minutes) for use on social media platforms. 

This multifaceted approach positions Spain as a leader in modernising open data communication, 
blending education and outreach to connect with diverse audiences in the digital age. 

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Incentives for data publication and access 

Legal frameworks and open data infrastructure (e.g. open data portals) can be effective incentivisation 
mediums for encouraging the  publication of dynamic, real-time or citizen-generated data. Dynamic 
data is data that changes asynchronously over time and is periodically updated as new information 
becomes available. Real-time data is data that changes and needs updating at very frequent intervals, 
in  most  cases  several  times  a  minute.  Access  to  dynamic  and/or  real-time  data  is  most  commonly 
provided  via  APIs.  On  the  other  hand,  citizen-generated  data  is  the  data  that  people  or  their 
organisations produce to directly monitor, demand or drive change on issues that affect them. Table 5 
presents an overview of how countries responded to the questions on this topic. 

Table 5: Countries’ responses to questions on incentives for data publication and access 

Does 
the  national  strategy/policy 
outline  measures  to  incentivise  the 
publication of and access to real-time 
or dynamic data? 

strategy/policy 
Does 
the  national 
outline  measures  to 
incentivise  the 
publication  of  and  access  to  citizen-
generated data? 

EU-27 

EFTA 

Candidate 

22  Member  States  (81 %)  report  that 
their  national  strategy/policy  outlines 
measures 
the 
publication of and access to real-time 
or  dynamic  data.  Bulgaria  is  a  new 
addition to this group. 

incentivise 

to 

that 

their 

Iceland,  Norway  and  Switzerland 
national 
report 
strategy/policy  outlines  measures  to 
incentivise  the  publication  of  and 
access  to  real-time  or  dynamic  data, 
with  Switzerland  being  the  most 
recent addition. 

14  Member  States  (51 %)  report  that 
their  national  strategy/policy  outlines 
measures to incentivise the publication 
of and access to citizen-generated data.  
Czechia, Portugal and Slovakia are the 
newest countries in this group. 

the 

None  of 
three  participating 
candidate  countries  reports  that  its 
national 
outlines 
strategy/policy 
measures to incentivise the publication 
of and access to citizen-generated data. 

Albania and Ukraine report that their 
national strategies and policies outline 
measures 
the 
publication of and access to real-time 
or dynamic data. 

incentivise 

to 

that 

reports 

its  national 
Ukraine 
strategy/policy  outlines  measures  to 
incentivise the publication of and access 
to citizen-generated data. 

(Questions P5 and P6) 

Legal frameworks play an important role in enabling the publication of and access to dynamic and/or 
real-time data, as well as citizen-generated data. Many countries, in their transposition of the open 
data  directive,  mandate  the  immediate  publication  of  dynamic  and/or  real-time  data  for  reuse. 
Typically, this publication is mandated to be made accessible through appropriate APIs. Denmark and 
Luxembourg mentioned in their survey responses that they also require the option of mass download 
when appropriate. 

Some  countries’  open  data  legal  frameworks  establish  consent  mechanisms  for  sharing  citizen-
generated  data.  This  transparency  fosters  greater  trust,  thus  empowering  citizens  and  potentially 
increasing their willingness to share data for public benefit. Namely,  Denmark, Estonia  and Cyprus 

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2024 Open Data Maturity Report 

note that they have a process whereby citizens can digitally inform the government if they consent to 
their personal data being processed or shared with others. 

Some  countries  leverage  an  open  data  infrastructure,  such  as  open  data  portals,  to  incentivise 
publication and access to various types of data. Specifically, Spain, Luxembourg and Finland highlight 
measures  to  improve  (semantic)  interoperability  of  dynamic  data  on  their  portals.  Additionally, 
Bulgaria, Estonia, France and Poland highlight the user-friendliness aspect of their national open data 
portals and that everyone has the ability to publish data. France specifically notes that the tools and 
processes for publishing data are the same for all types of providers; however, a badge is provided to 
what the portal identifies as official sources (i.e. public sector organisations). 

Highlight from Iceland – the secure national data exchange infrastructure Straumurinn 
Iceland  is  in  the  process  of  implementing  Straumurinn,  a  cutting-edge  national  data  exchange 
infrastructure  based  on  the  X-Road  technology.  This  system  facilitates  secure,  real-time  data 
exchange between government agencies, municipalities and private companies, thereby enhancing 
the quality and efficiency of public services. 

Straumurinn serves as the backbone for a central service portal through which Icelandic citizens can 
access a wide range of public services in one secure location. This initiative emphasises equality by 
providing universal access to services for all citizens. 

Developed in collaboration with Estonia and Finland through the Nordic Institute for Interoperability 
Solutions, Straumurinn offers several critical features: 

•  data security – all communications are encrypted to ensure secure data exchanges; 

•  data integrity – data remains up to date, with direct, authorised communication between 

service providers and recipients; 

• 

traceability –  each  transaction  is  traceable  and timestamped,  ensuring transparency  and 
accountability. 

As public administrations may encounter technical and financial constraints in the publication process, 
some countries include measures to help make it easier for them to publish open data. For example, 
Cyprus provides both internal and external consulting services and technical support to organisations 
aiming to publish dynamic data. Slovenia provides funding to promote accessibility and the use of data 
on its national portal, and this includes dynamic data. Bulgaria also includes a clause in its national 
open data law whereby public bodies that do not have the necessary technical and financial capabilities 
to make dynamic data available for reuse immediately are allowed to publish data within a longer time 
frame and with temporary technical constraints. 

Countries often encourage the publication of and access to dynamic and/or real-time data and citizen-
generated data through sector-specific (e.g. health, environment and public transport) initiatives. For 
example, initiatives such as the DataDonor initiative (Denmark), Donate Your Speech (Estonia) and 
GelAvista (Portugal) encourage citizens to create data for research in various fields. For real-time data 
access, Denmark and Ireland have initiatives that display all public electronic car-charging stations in 
real time. In Berlin, the Jelbi app provides bus and train timetable data using real-time transport data 
and geodata from participating sharing partners. 

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Highlight from Germany – the Jelbi mobility app 
The  Jelbi  mobility  app  from  Berliner  Verkehrsbetriebe  (BVG)  combines  the  mobility  offers  of 
numerous partners in a single app with a user profile and thus provides a large selection of transport 
options. It also includes important information such as fares, vehicle locations and journey times to 
the destination directly in one place. 

The app uses real-time transport data and geodata from the participating sharing partners and the 
Berlin-Brandenburg  Transport  Association  (VBB),  whose  bus  and  train  timetable  data  (lines, 
departure times, routes, etc.) are regularly provided via the Berlin Open Data portal. 

Supporting the reuse of open data 

The primary aims of the open data directive are to encourage the opening of public sector information 
and  to  stimulate  its  reuse.  Therefore,  measures  in  the  country’s  open  data  strategy  or  policy  that 
support the reuse of open data by the public and private sectors can support the downstream activities 
of  making  data  openly  available.  Table 6  presents  an  overview  of  how  countries  responded  to  the 
questions on this topic. 

Table 6: Countries’ responses to questions on supporting the reuse of open data 

Does the national 
strategy/policy foster the 
discoverability of data 
from your country on 
data.europa.eu? 

Does the national 
strategy/policy outline 
measures to support the 
reuse of open data by the 
public sector? 

Does the national 
strategy/policy outline 
measures to support the 
reuse of open data by the 
private sector? 

EU-27 

EFTA 

23 Member States (85 %) 
report that their policies 
and strategies involve the 
publishing of data on 
data.europa.eu. Portugal 
is the newest country to 
report doing this. 
Nonetheless, the other 
Member States tend to 
make their data 
discoverable on 
data.europa.eu in 
practice, even though 
this is not explicitly 
fostered in a policy or 
strategy. 

Norway reports that its 
policies and strategies 
involve the publishing of 
data on data.europa.eu 
to foster discoverability. 

26 Member States (96 %), 
all except Belgium, report 
that their open data 
policies and strategies 
outline measures to 
support the reuse of open 
data by the public sector. 

23 Member States (85 %), 
all except Bulgaria, 
Croatia, Luxembourg and 
the Netherlands, report 
that their open data 
policies and strategies 
outline measures to 
support the reuse of open 
data by the private sector. 
Portugal is the newest 
country to report this. 

All three participating EFTA 
countries report that their 
open data policies and 
strategies outline measures 
to support the reuse of 
open data by the public 
sector. 

All three participating EFTA 
countries report that their 
open data policies and 
strategies outline 
measures to support the 
reuse of open data by the 
private sector. 

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Does the national 
strategy/policy foster the 
discoverability of data 
from your country on 
data.europa.eu? 

Does the national 
strategy/policy outline 
measures to support the 
reuse of open data by the 
public sector? 

Does the national 
strategy/policy outline 
measures to support the 
reuse of open data by the 
private sector? 

Candidate  Ukraine reports that its 

policies and strategies 
involve the publishing of 
its country’s data on 
data.europa.eu to foster 
discoverability. 

All four participating 
candidate countries report 
that their open data 
policies and strategies 
outline measures to 
support the reuse of open 
data by the public sector, 
with Albania being the 
most recent country to 
report this. 

All four participating 
candidate countries report 
that their open data 
policies and strategies 
outline measures to 
support the reuse of open 
data by the private sector. 

(Questions P7, P8 and P9) 

A prominent trend in country responses about enhancing the reuse of open data by both the private 
and the public sectors is ensuring that open data is accessible and of high quality. For example, many 
countries  have  committed  to  using  standardised  formats  and  ensuring  common  architectural 
principles and standards across all providers (e.g. by adhering to the findable, accessible, interoperable 
and  reusable  (FAIR)  data  principles).  For  example,  the  Irish  open  data  strategy  for  2023–2027 
emphasises the importance of ensuring data is fit for purpose, standardised and held in a condition 
that makes it FAIR. The national Irish data repository for Ireland’s humanities, cultural heritage and 
social sciences digital data also commits to ensuring that open data adheres to FAIR principles. Several 
countries also focus on improving interoperability capabilities to improve accessibility. Specifically, the 
Netherlands  is  creating  a  federative  system  that  connects  and  integrates  open  data  from  various 
sources within the country. Denmark and Poland are improving their open data infrastructures, with 
Denmark working to modernise its basic data registries and  Poland funding projects to improve its 
open data portal. Several countries  report  that the  data.europa.eu  platform is a popular outlet for 
open  data  reuse.  This  is  because  it  is  an  easily  accessible  central  hub  with  built-in  interoperability 
features, offering countries a unified space for seamless data sharing across borders. 

Another prominent trend is the use of training and capacity-building initiatives to improve data quality 
and reuse. Many countries prioritise educating officials from the public sector to enhance data literacy. 
For instance, Croatia focuses on training public officials to monitor compliance with open data laws, 
while  Cyprus,  Estonia,  Ireland,  Lithuania,  Slovenia  and  Switzerland  offer  dedicated  training 
programmes to build competencies within government institutions. Additionally, Serbia and Slovenia 
report that they actively organise training sessions with a broad audience, including the private sector, 
to encourage data reuse. In addition, Portugal is providing free data analysis and visualisation tools on 
its open data portal to upskill reusers. 

Finally, collaborative efforts and community engagement are further recurring trends in the promotion 
of  data  reuse  among  both  the  private  and  the  public  sectors.  Countries  such  as  Estonia,  Ireland, 
Greece, Croatia and Portugal report that they are promoting open data reuse by organising a range of 
public events, workshops and networking opportunities. Greece, Slovenia and Ukraine also note that 
they organise events such as hackathons and competitions to increase open data reuse. 

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Highlight from Austria – the Cooperation Open Government Data initiative 
Established as a pivotal component of Austria’s open data strategy, Cooperation OGD Austria serves 
as  a  collaborative  platform  between  the  Federal  Chancellery  of  Austria  and  major  cities  such  as 
Vienna,  Linz,  Salzburg  and  Graz.  This  initiative  is  designed  to  include  cross-border  partners  from 
Germany, Liechtenstein and Switzerland in the  near future, expanding its influence  and reach. It 
encompasses a diverse array of stakeholders, namely from communities, academia, culture and the 
economy, all of which are committed to enhancing the open data landscape in Austria. 

Cooperation OGD Austria fosters an environment that promotes effective collaboration among local 
communities,  including  citizens,  businesses  and  researchers.  The  initiative  facilitates  knowledge 
exchange  and  encourages  active  participation  from  various  stakeholders  within  the  open  data 
ecosystem through regular meetings and networking events, such as the Vienna open data meet-
ups. These gatherings serve as vital opportunities for sharing insights, challenges and best practices 
related to open data. 

The Austrian government reports that this cooperation has created significant synergies among the 
cities involved and has led to a marked increase in open data reuse across the four cities. 

Data inventories 

A data inventory is a comprehensive catalogue of the datasets held by an organisation and can be used 
to plan the opening of appropriate datasets. Data inventories can also include data collected by public 
bodies that cannot be published as open data (e.g. in relation to the EU data governance regulation 
(Regulation  (EU)  2022/868)).  Table 7  presents  an  overview  of  how  countries  responded  to  the 
questions on this topic. 

Table 7: Countries’ responses to questions on data inventories 

EU-27 

EFTA 

Candidate 

Do  policies  and  strategies  mandate 
that  public  bodies  carry  out  and 
maintain a data inventory, whether at 
the national or local level? 

Do  these  data  inventories  include  the 
data  collected  by  public  bodies  that 
cannot be published as open data? 

26 Member States (96 %), all except 
the Netherlands, report that their 
open data policy or strategy mandates 
that public bodies maintain a data 
inventory. 

25 Member States (92 %), all except 
Bulgaria and the Netherlands, report 
that their data inventories include the 
data collected by public bodies that 
cannot be published as open data. 

Norway and Switzerland report that 
their open data policy or strategy 
mandates that public bodies maintain 
a data inventory. 

Norway and Switzerland report that 
their data inventories include the data 
collected by public bodies that cannot 
be published as open data. 

Albania, Bosnia and Herzegovina and 
Ukraine report that their open data 
policy or strategy mandates that 
public bodies maintain a data 
inventory. 

Albania, Bosnia and Herzegovina and 
Ukraine report that their data 
inventories include the data collected 
by public bodies that cannot be 
published as open data.  

(Questions P10-a and P10-b) 

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Data inventories are often part of broader efforts in countries’ national policies/strategies to manage 
data efficiently, ensure interoperability across systems and reduce redundant data collection. Regular 
data audits are often mandated to ensure data inventories are up to date and accurate, particularly in 
the context of open data and compliance with the general data protection regulation (Regulation (EU) 
2016/679). 

Highlight from Finland – the Finnish comprehensive data inventory framework  
In  Finland,  maintaining  a  data  inventory  is  federally  mandated.  Specifically,  most  public  sector 
organisations are legally required to maintain a data inventory, as specified in the Act on Information 
Management  in  Public  Administration  (906/2019).  In  addition,  since  2021,  Finnish  public  sector 
entities  have  been  required  to  maintain  an  information  management  model  that  outlines  the 
management  of  datasets,  the  implementation  of  rights  and  restrictions  relating  to  access  to 
information, the implementation of interoperability of information systems and information pools, 
and the maintenance of information security. 

The Ministry of Finance of Finland maintains the public sector information management map, which 
describes  the  data  resources  to  utilise  and  the  procedures  for  accessing  data  from  the  data 
resources. The information management model includes both open data and data resources that 
are not available or that are not possible to publish as open data. 

In  addition,  the  Act  on  the  Openness  of  Government  Activities  (621/1999)  mandates  that  the 
catalogues  listing  the  data  inventories  be  published  as  open  data.  These  catalogues  give  an 
indication  of  what  each  data  or  information  repository  holds,  for  example  the  City  of  Vantaa’s 
catalogues of information systems. The dataset provides a list of all of the information systems in 
use in the city, information on system ownership and technical responsibility, and a brief description 
of each information system. 

Highlight from Slovakia – data inventory for enhanced transparency and accountability 
In  Slovakia,  it  is  mandated  that  data  inventories  must  include  detailed  records  for  all  datasets 
managed by public institutions, not just those available to the public. This comprehensive approach 
ensures  transparency  about  datasets,  even  if  they  are  restricted  for  reasons  such  as  privacy, 
commercial confidentiality, statistical confidentiality, national security or intellectual property. 

Key elements of Slovakia’s practice include the following. 

• 

Inclusive data inventory. Slovakia’s data inventory encompasses all datasets managed by 
public  institutions,  ensuring  that  both  open  and  non-open  data  are  documented.  This 
includes  maintaining  records  of  datasets  that  cannot  be  publicly  accessed,  with  clear 
reasons provided for their restricted status. 

•  Detailed metadata and documentation. The data inventory model in Slovakia is designed 
to include detailed metadata for all datasets. This documentation provides an insight into 
the nature of each dataset, including non-public ones, and explains why certain data cannot 
be released. This practice supports transparency by informing stakeholders about the data 
held by public bodies, even if it is not openly accessible. 

•  Model  structure  and  public  accessibility.  The  Data  Unit  at  the  Ministry  of  Investments, 
Regional Development and Informatization has developed and published a model structure 
for  data  inventories.  This  model  is  publicly  accessible  and  includes  documentation  for 
datasets, contributing to a transparent data management process. 

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Prioritising high-value datasets 

HVDs are datasets that hold significant potential for economic, social or environmental benefits when 
made openly available. Commission Implementing Regulation (EU) 2023/138, adopted in December 
2022 and published in January 2023, lays down a list of specific HVDs and the arrangements for their 
publication and reuse. 

The  ODM  questionnaire  included  two  questions  to  inquire  about  countries’  progress  with 
implementing the EU regulation on HVDs. Table 8 presents an overview of how countries responded. 

Table 8: Countries’ responses to questions on implementing the EU regulation on HVDs 

Is  your  country  applying  Commission 
Implementing Regulation (EU) 2023/138 on 
HVDs? 

Have  the  public  bodies  in  your  country 
denoted relevant datasets as HVDs in their 
metadata? 

EU-27  All Member States (100 %) report that they 
are  working  towards  applying  Commission 
Implementing Regulation (EU) 2023/138 on 
HVDs. 

21 Member States (77 %) report that their 
public bodies with HVDs have denoted this 
in the dataset’s metadata. 

(Questions P11 and P12) 

Non-EU countries were not surveyed on this question, since this regulation applies only to EU Member States. 

On average, progress is most advanced for statistics (80 %) and geospatial (77 %) datasets (Figure 7). 
In contrast, the high-value category of ‘companies and company ownership’ (69 %) has seen the lowest 
average progress, followed by mobility datasets (70 %). 

Turning to the underlying requirements, the most advanced progress is seen in terms of identifying 
and  inventorying  HVDs  (technical  progress)  (83 %),  followed  by  addressing  legal  barriers  (legal 
progress)  (77 %)  and  setting  up  new  roles  and  workflows  (organisational  progress)  (77 %). 
Requirements  related  to  technical  progress  score  the  lowest,  with  the  requirements  of  quality 
metadata (71 %), machine-readable formats via APIs (69 %)  and bulk download (66 %)  showing the 
lowest average progress. 

Estonia, Lithuania, Latvia, Denmark, Slovenia, Poland and Finland are highly mature in terms of their 
implementation of the HVD regulation, achieving above 90 % maturity on average. On the other hand, 
Bulgaria, Croatia and Greece report the least progress in implementing the HVD regulation, scoring 
less than 50 % on average. 

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2024 Open Data Maturity Report 

Figure 7: Average maturity scores of the six categories of HVDs and seven areas of activities 

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Figure 8:  12  Member  States  are  at  or  above  the  EU  average  maturity  for  implementing  the 
requirements on HVDs 

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2024 Open Data Maturity Report 

4.3. Governance of open data 

This  indicator  evaluates  the  governance  structures  and  operating  models  in  place  at  the  national, 
regional and local levels to support open data initiatives. This includes the appointment of civil servants 
with a remit on open data and the exchange of knowledge and experiences within the public sector 
and with open data reusers. 

Governance structures 

A governance structure for open data refers to the formal system or framework that ensures various 
open data stakeholders’ participation, collaboration and inclusion. This framework helps to ensure that 
open  data  initiatives  are  inclusive,  transparent  and  aligned  with  the  needs  of  all  stakeholders. 
Governance structures can be top-down, with coordinating power exercised by an established body, 
or  enacted  using  a  hybrid  model,  allowing  regional  autonomy  while  maintaining  central  oversight. 
Either way, countries will often have mechanisms for engaging stakeholders within their governance 
systems. Table 9 presents an overview of how countries responded to the questions on this topic. 

Table 9: Countries’ responses to questions on governance structures 

EU-27 

EFTA 

Candidate 

Is there a governance structure in 
place that enables the participation 
and/or inclusion of various open data 
stakeholders? 

25 Member States (93 %), all except 
Bulgaria and Croatia, report that their 
governance structures enable the 
participation and inclusion of various 
stakeholders in open data policies. 

Iceland, Norway and Switzerland 
report that their governance 
structures enable the participation 
and inclusion of various stakeholders 
in open data policies, with Iceland as 
the most recent addition to this 
group. 

Albania and Ukraine, along with 
Serbia as a new addition this year, 
report that their governance 
structures enable the participation 
and inclusion of various stakeholders 
in open data policies. 

How would you classify the model used 
for governing open data in your 
country? 

20 Member States (74 %) report using 
a hybrid model, combining elements of 
a top-down and a bottom-up approach. 
Seven Member States (26 %) report 
that they implement a top-down 
approach. 

All three participating EFTA countries 
report using a hybrid model, combining 
elements of a top-down and a bottom-
up approach. 

All four participating candidate 
countries report using a hybrid model, 
combining elements of a top-down and 
a bottom-up approach. 

(Questions P13 and P14) 

Most countries involve various stakeholders from different sectors, including government, civil society, 
academia and the private sector, in their open data governance structures. Typically, countries report 
that a centralised entity is established to govern open data activities. Indeed, all countries that report 
that  their  governance  model  uses  a  top-down  approach  (i.e.  Bulgaria,  Czechia,  Estonia,  Ireland, 

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2024 Open Data Maturity Report 

Greece, Cyprus and Slovenia) also mention having such a central coordinating entity, but so do several 
countries that report a hybrid governance model. In hybrid models, this is often noted to be due to the 
institutional and political structure of the country. In this model, local and regional bodies maintain 
the autonomy to pursue their own open data initiatives. At the same time, the central government 
retains oversight to offer guidance, allocate funding and prevent redundancies. 

Countries like Austria, Bulgaria, Estonia, Greece, Iceland, Latvia, Lithuania, the Netherlands, Poland 
and Ukraine have assigned oversight of open data affairs to specific national ministries. On the other 
hand, Ireland  and Cyprus have established open data governance  boards, comprising professionals 
from  public  services,  academia  and  the  private  sector,  to  provide  strategic  direction  to  open  data 
initiatives.  Furthermore,  countries  such  as  Denmark,  Hungary  and  Romania  coordinate  open  data 
efforts  through  specialised  agencies  responsible  for  broader  digital  governance  and  data  issues. 
Meanwhile, France, Romania and Finland utilise interministerial and interdepartmental structures for 
managing open data initiatives. 

We have a decentralised public sector, but the Ministry of Finance and the Ministry of Higher 
Education,  Science,  and  Innovation  are  responsible  for  providing  open  data.  Currently,  the 
stewardship is at the ministerial level, but the execution is decentralised. 

Iceland’s survey response 

Among most countries, there is an emphasis on participatory governance methods. There are certain 
ways  in  which  most  governments  integrate  different  forms  of  collaboration,  coordination  and 
stakeholder engagement within their governance system. 

One prominent method is the establishment of formal working groups and task forces as a means to 
govern  open  data  activities.  These  groups  provide  a  forum  for  ongoing  discussions  and  can  help 
enhance  decision-making.  Specifically,  Belgium,  Czechia,  Estonia,  Romania,  Serbia,  Slovakia  and 
Ukraine note that their focus groups include diverse stakeholders, such as government officials, local 
authorities, civil society, the technology community, academia and the private sector. Whereas some 
groups,  such  as  those  from  Belgium,  France  and  Poland,  are  formalised  around  specific  open  data 
strategies or networks, others, such as in Estonia and Slovakia, are more informal, with members not 
necessarily formally appointed but rather included through informal mechanisms like mailing lists or 
voluntary participation. Various countries also note that they hold regular structured meetings as a 
mechanism for participatory governance, such as with a network of national ministries. 

Furthermore,  open  feedback  and  consultation  mechanisms  are  also  used  to  engage  various 
stakeholders in managing open data matters. For instance, France and Lithuania systematically collect 
feedback from stakeholders on open data that they access through their national open data platforms. 
Denmark has two forums managed by internal representatives who gather feedback from open data 
users. 

Highlight from Czechia – adapting governance models over time 
An interesting dynamic noted by Czechia is the transition of governance models. In Czechia, open 
data measures were initially driven by localities; however, since the introduction of national open 
data legislation, the national government has taken the steering role in open data initiatives. 

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Local and regional governance structures 

To  ensure  the  effective  publication  and  reuse  of  open  data  across  a  country,  governance  must  be 
established  not  only  at  the  national  level  but  also  at  the  subnational  level.  This  entails  national 
governments creating an enabling environment for subnational entities to thrive in their open data 
endeavours. Although structural and legal limitations might exist, national governments often provide 
technical,  monetary  and  advisory  support  to  local  administrations  for  their  open  data  initiatives. 
Table 10 presents an overview of how countries responded to the questions on this topic. 

Table 10: Countries’ responses to questions on local and regional governance structures 

EU-27 

EFTA 

Does  the  governance  structure  ensure 
that  the  local  and  regional  open  data 
initiatives are facilitated and supported 
at the national level? 

24 Member States (89 %), all except 
Germany and Finland, report that the 
governance structure in their country 
ensures that local and regional open 
data initiatives are facilitated and 
supported nationally.  Malta, Austria 
and Portugal are the newest countries 
to make this addition to their 
governance structure. 

Iceland and Norway report that the 
governance structure in their country 
ensures that local and regional open 
data initiatives are facilitated and 
supported nationally. Switzerland 
reports that this question is ‘not 
applicable’, as the laws behind its 
national governance structure do not 
directly apply at the regional level but 
instead serve as guidelines for regional 
governance . 

Candidate  Serbia and Ukraine report that the 

governance structure in their country 
ensures that local and regional open 
data initiatives are facilitated and 
supported nationally. 

To  what  degree  do  local/regional  public 
bodies conduct open data initiatives? 

Nine Member States (33 %) report that all 
local/regional public bodies in their country 
conduct open data initiatives, and seven 
Member States (25 %) report that the 
majority of local/regional public bodies do. 
Czechia reports that there has been 
increased participation, from a few public 
bodies in 2023 to the majority being 
involved in these efforts in 2024. Cyprus 
and Malta indicate that this question is 
‘not applicable’ due to their small size and 
the absence of regional governance 
structures. 

Norway and Switzerland report that the 
majority of the local/regional public bodies 
in their country conduct open data 
initiatives. Switzerland reports that there 
has been an increase in participation, from 
approximately half of local/regional public 
bodies in 2023 to a majority in 2024 being 
involved in these efforts. Iceland reports 
that only a few public bodies in the country 
conduct open data initiatives. 

Ukraine reports that all local/regional 
public bodies conduct open data initiatives. 
Serbia reports that approximately half of 
the local/regional public bodies conduct 
open data initiatives, and Albania and 
Bosnia and Herzegovina report that only a 
few public bodies do. 

(Questions P15 and P16) 

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2024 Open Data Maturity Report 

A central national entity typically facilitates local and regional open data initiatives from the national 
level. Nonetheless, some countries, such as Belgium, Germany and Switzerland, cite structural or legal 
limitations (e.g. federalised structures) as reasons for not having robust national support for local and 
regional open data initiatives. That being said, many of these countries report that cooperation may exist 
between their national and regional bodies. 

Local  data  initiatives  are  very  important  in  France  and  are  often  encouraged ...  they  often 
constitute interesting experiments that can be generalised. 

France’s survey response 

When support for local and regional open data initiatives is provided, national entities do this in 
various ways. 

•  Technical support. Estonia, Ireland, Greece, Spain and France note that they provide technical 
and advisory support to regional and local governments from their national governments. For 
example, Greece’s Ministry of Digital Governance offers technical support for publishing local 
datasets, and Spain’s Aporta Initiative (managed by the Ministry for Digital Transformation and 
Public Service) offers specialised advice on open data technical and methodological aspects. 
Croatia, Poland and Portugal note that they use national data portals as a way to provide a 
platform for local authorities to share their data without them needing to develop their own 
systems. 
Funding  support.  Some  countries  also  note  that  the  national entity may  provide  monetary 
support to local and regional open data initiatives. For example, France’s national government 
funds digital initiatives through the Public Action Transformation Fund. 

• 

•  Capacity-building support. Some countries note that they provide structured programmes and 
events to facilitate local and regional open data initiatives. While these can come in the form 
of open data workshops or training on behalf of the national entity responsible for open data 
matters  (as  in  the  case  of  Poland),  other  countries,  such  as  Czechia,  Cyprus  and  Slovakia, 
specifically  note  that  they  sponsor,  support  or  encourage  local  open  data  hackathons  to 
facilitate engagement with open data. 

•  Advisory support. Some countries (e.g. Bulgaria, Italy, Lithuania, Poland and Sweden) note 
that their national governments undertake regular dialogue and knowledge sharing with their 
regional and local counterparts, which also helps to facilitate open data initiatives at the local 
and regional levels. In Lithuania, this is done through newsletters and public communications 
from the Ministry of Economy and Innovation. In  Italy  and Sweden, dedicated networks of 
national and municipal personnel exchange information regarding open data initiatives. 

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Highlight from Serbia – United Nations Development Programme collaboration for promoting 
local initiatives 
In Serbia, the Office for Information Technology and e-Government, in collaboration with the United 
Nations Development Programme, actively supports local and regional open data initiatives. This 
multi-stakeholder cooperation aims to enhance the effectiveness  and reach of open data efforts 
throughout the country. 

Already, more than 50 % of user accounts on the national open data portal are owned by local self-
governments. This can be attributed to the engagement that the initiative has fostered from local 
entities. In fact, over the past seven years, the initiative has supported numerous local events and 
activities,  including  the  launch  of  an open  data  challenge  focused on  promoting  local open  data 
usage.  In  April  2024,  the  Office  for  Information  Technology  and  e-Government  provided  expert 
support  for  the  regional  open  data  challenge,  facilitated  by  the  United  Nations  Development 
Programme and the Regional School of Public Administration. 

Highlight from Italy – the Agency for Digital Italy 
In Italy, the Agency for Digital Italy (AGID) facilitates the implementation of regional digital agendas 
in alignment with the country’s three-year plan for information and communication technology in 
public  administration.  These  efforts  encompass  specific  actions  aimed  at  enhancing  open  data 
initiatives. 

A crucial component in each individual public administration is the Office of the Digital Transition 
Manager (RTD), established by Article 17 of the Digital Administration Code. The RTD oversees the 
transition to digital operations and reports directly to the political leadership or, in their absence, to 
the administrative management. This role serves as a vital link between top management, AGID and 
the Presidency of the Council of Ministers, addressing issues related to the digital transformation of 
public administrations. 

AGID  promotes  regular  dialogue  with  the  appointed  digital  transition  managers  in  each  public 
administration through a dedicated platform that fosters communities focused on open data. This 
engagement ensures that the local and regional levels are actively involved and supported in their 
open data endeavours. 

Outlining open data roles and responsibilities 

A network of open data officers serves as a system of communication and collaboration between the 
national open data team and various open data officers across different regions or sectors within the 
country.  Having  civil  servants  across  public  sector  bodies  with  an  official  remit  on  open  data  can 
facilitate the process of making data open. Table 11 presents an overview of how countries responded 
to the questions on this topic. 

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Table 11: Countries’ responses to questions on open data roles and responsibilities 

Is a document describing the 
responsibilities and governance structure 
of the national (and/or regional/local) 
open data team publicly available? 

Does the governance model include the 
appointment of official roles in civil 
services that are dedicated to open data 
(e.g. open data officers)? 

EU-27 

EFTA 

24 Member States (88 %), with Malta and 
Portugal as the most recent additions, 
report that they have a publicly available 
document describing the responsibilities 
and governance structure of the national 
(and/or regional/local) open data team. 
Denmark, Croatia and Sweden do not 
report having such a document available. 

Switzerland reports that it has a publicly 
available document describing the 
responsibilities and governance structure 
of the national (and/or regional/local) 
open data team. 

Candidate  All four participating candidate countries, 

including Serbia as the most recent 
addition, report that they have a publicly 
available document describing the 
responsibilities and governance structure 
of the national (and/or regional/local) 
open data team. 

25 Member States (95 %), all except 
Belgium and Denmark, report that their 
governance model includes the 
appointment of dedicated open data 
roles in civil services. 

Iceland and Switzerland report that their 
governance models include the 
appointment of dedicated open data 
roles in civil services. 

Albania, Serbia and Ukraine report that 
their governance models include the 
appointment of dedicated open data 
roles in civil services. 

(Questions P17 and P19) 

Several countries, such as Germany, Spain, Croatia, Poland and Slovenia, report that they have specific 
national laws that require the  appointment of specific roles  focused on open data. In particular, in 
Spain  over  the  past  year,  some  government  bodies  have  started  creating  a  unit  responsible  for 
information, as required by Law 37/2007. This unit will manage the reuse of public sector information 
(i.e. open data). Many countries appoint a designated coordinator, steward or officer for open data in 
their public bodies. These are specific individuals in government bodies who are tasked with managing 
open data affairs. However, in some countries, open data matters are designated as the responsibility 
of broader data officer roles, as these roles often existed prior to open data legislation. Individuals in 
these roles manage open data on top of other data-related matters (i.e. management, quality and data 
governance).  For  example,  in  2022,  Estonia  created  the  Data  Stewards  Steering  Group,  which 
coordinates  data  stewards  from  various  public  authorities  to  ensure  the  sustainable  and  balanced 
development of the data field, including open data matters. 

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Highlight from Cyprus – governance structure outlined in the open data strategic plan for 2023–
2027 
Cyprus’s  Open  Data  Strategic  Plan  2023–2027  outlines  its  main  goals  and visions  for open  data, 
including action points and critical success factors. In addition, on page 9, the open data governance 
structure is outlined, displaying different stakeholders and their interactions (Figure 9). 

Figure 9: Diagram of Cyprus’s 
governance structure (TTDP: 
Department of Public Administration 
and Personnel in Cyprus). 

Network of open data team, officers and reusers 

Communication  and  collaboration  between  various  stakeholders  are  important  for  fostering  a 
functional  open  data  ecosystem.  A  regular  exchange  of  knowledge  and  experiences  between 
stakeholders, both within and across countries, can play a significant role in enhancing the quality and 
accessibility of open data and in creating feedback loops for improving open data policies. A prominent 
approach to facilitating these exchanges that is employed by countries is to create formal and informal 
groups  that  engage  through  various  platforms  and  events.  Table 12  presents  an  overview  of  how 
countries responded to the questions on this topic. 

Table 12: Countries’ responses to questions on communication and collaboration between 
stakeholders 

EU-27 

Is there a regular 
exchange of knowledge 
or experiences between 
the national open data 
team and the team 
maintaining the national 
portal? 

Is there a regular exchange 
of knowledge or 
experiences between the 
national open data team 
and the wider network of 
open data officers in your 
country? 

Is there a regular exchange 
of knowledge or 
experiences between public 
sector bodies (i.e. the 
providers) and open data 
reusers (e.g. academia, 
citizens and businesses)? 

26 Member States 
(96 %), all except 
Finland, report that the 
national open data team 
and the team 
maintaining the national 
portal in their countries 
have regular exchanges. 

All Member States (100 %), 
with Croatia as the most 
recent addition, report that 
the national open data 
team and the wider 
network of open data 
officers in their countries 
have regular exchanges. 

All Member States (100 %) 
report that public sector 
bodies and open data 
reusers in their countries 
regularly exchange 
knowledge and 
experiences. 

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2024 Open Data Maturity Report 

Is there a regular 
exchange of knowledge 
or experiences between 
the national open data 
team and the team 
maintaining the national 
portal? 

Is there a regular exchange 
of knowledge or 
experiences between the 
national open data team 
and the wider network of 
open data officers in your 
country? 

Is there a regular exchange 
of knowledge or 
experiences between public 
sector bodies (i.e. the 
providers) and open data 
reusers (e.g. academia, 
citizens and businesses)? 

All three participating 
EFTA countries report 
that the national open 
data team and the team 
maintaining the national 
portal in their countries 
have regular exchanges. 

All three participating EFTA 
countries report that the 
national open data team 
and the wider network of 
open data officers in their 
countries have regular 
exchanges. 

All three participating EFTA 
countries report that 
public sector bodies and 
open data reusers in their 
countries regularly 
exchange knowledge and 
experiences. 

EFTA 

Candidate  Albania, Serbia and 

Ukraine report that the 
national open data team 
and the team 
maintaining the national 
portal in their countries 
have regular exchanges. 

Albania and Ukraine report 
that the national open data 
team and the wider 
network of open data 
officers in their countries 
have regular exchanges. 

Serbia and Ukraine report 
that public sector bodies 
and open data reusers in 
their countries regularly 
exchange knowledge and 
experiences. 

(Questions P18, P20 and P21) 

Exchanges between the national open data team and the team maintaining the national portal can be 
formalised around established groups, such as in Denmark (the forum for data distributors), Germany 
(the  GovData  working  group)  and  Austria  (Cooperation  OGD  Austria).  Such  exchanges  can  also  be 
informal  and  occur  on  an  ad  hoc  basis;  this  may  be  because  the  open  data  team  and  the  team 
maintaining the portal work within the same institution (e.g. in Hungary, Italy, Norway, Romania and 
Serbia),  such  as  an  agency  or ministry,  or  because  they  are  part of the  same  team  (e.g.  in  Cyprus, 
France, Greece, Malta, Poland, Switzerland and Ukraine). In contrast, some countries use external 
parties to maintain their open data portals (e.g. Albania and Ireland). 

Similarly, exchanges between the national open data team and the wider network of open data officers 
are often arranged through working groups. Some exchanges can also be arranged around workshops 
and  specialised  forums  or  events,  such  as  the  open  data  liaison  officer  meeting  in  Ireland,  the 
Interbestuurlijke Datastrategie Café in the Netherlands and the data stewards event in Slovenia. These 
meetings are sometimes specifically focused on training and development activities. For example, in 
Ukraine, the Open Data Academy was set up to boost skills through training programmes. 

On the other hand, exchanges between national public sector bodies and open data reusers are often 
arranged through conferences and forums. Conferences such as the Danish Forum for the Use of Basic 
Data  and  Other  Public  Data,  the  German  Berlin  Open  Data  Day,  the  Irish  National  Open  Data 
Conference and the Swiss Open Data Beer bring together public sector officials, academics, businesses 
and other stakeholders to discuss open data issues and innovations. 

Furthermore, regular exchange of knowledge between the public sector and open data reusers is often 
fostered through collaborative working groups that include representatives of the public sector, the 
private sector,  academia  and  civil  society.  Some  examples  include  the  Bulgarian  working  group  on 

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2024 Open Data Maturity Report 

transposing the open data directive, which includes representatives of public sector bodies, academia, 
businesses, non-governmental organisations and citizens, and the Serbian Open Data Working Group, 
which includes participants from the technology community, the media, academia and civil society. 

Digital platforms are also used in this context to facilitate knowledge exchange. In addition to more 
general  digital  platforms  (e.g.  email  and  online  meetings),  some  countries  report  that  they  have 
developed unique platforms dedicated to engaging various users in open data topics, such as the Dutch 
Geoform platform or the Italian Forum Italia platform. 

Highlight from Norway – Datalandsbyen (Data Village)  
Norway’s  Datalandsbyen,  or  ‘Data  Village’,  is  an  interactive  online  forum  designed  to  facilitate 
engagement among users. It allows individuals to pose questions about data, engage in discussions, 
share their projects, connect with others and explore potential collaborations. In addition, it enables 
constant communication between the open data team, data professionals, the team maintaining 
the Norwegian national portal, open data reusers and the public. 

4.4. Open data implementation 

This indicator evaluates the processes and activities in place to implement the open data policies and 
strategies  outlined.  Specifically,  this  indicator  examines  the  initiatives  that  assist  data  providers, 
including holders of real-time, geospatial and citizen-generated data, with their open data publication 
process and that promote open data literacy among civil servants and the broader public. 

Data publication plans 

Data  publication  plans  are  specific  workflows  or  internal  data  management  processes  for  the 
publication  of  datasets.  Data  publication  plans  and  related  monitoring  mechanisms  are  needed  to 
enable those  responsible  to oversee  the progress being made towards  opening up datasets and to 
intervene in the event of barriers. Table 13 presents an overview of how countries responded to the 
question on this topic. 

Table 13: Countries’ responses to the question on data publication plans 

Do data publication plans exist at the public body level? 

EU-27 

EFTA 

Candidate 

All Member States (100 %), with Lithuania and Portugal as the most recent additions, 
report that they have publication plans for open data at the public body level. 

Norway and Switzerland report that they have publication plans for open data at the 
public body level. 
Albania  and  Ukraine  report  that  they  have  publication  plans  for open  data at the 
public body level. 

(Question P22) 

The majority of countries have implemented legal frameworks or regulations that require public sector 
bodies  to  develop  and  implement  data  publication  plans.  In  particular,  countries  tend  to  use 
centralised  national  platforms  or  geoportals  with  specific  workflows  and  procedures  to  help  them 
publish open data. 

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Highlight from Denmark – structured data publication planning 
In Denmark, data publication plans exist at various levels within public bodies. 

• 

Statistics Denmark. Statistical datasets follow a detailed release calendar, with publication 
dates announced at least a year in advance. The processes and workflows are documented 
in the statistical documentation available for each dataset. 

•  Basic data. The Datafordeleren platform connects to more than 20 public data registries, 
making it a central hub for accessing various types of public data. This integration simplifies 
the  data  discovery  process  for  users  by  providing  a  one-stop  shop  for  diverse  datasets 
ranging  from  demographic  information  to  economic  indicators.  Information  about  new 
releases,  planned  service  changes  and  documentation  is  easily  accessible  through  the 
website. Additionally, Datafordeleren supports various formats for data retrieval, enhancing 
its usability for developers and analysts. 

•  General  guidelines.  The  Danish  Agency  for  Digital  Government  provides  a  reference 
architecture  for  data  sharing  and  technical  guidance  that  data  publishers  can  use  when 
developing their publication plans. By adhering to these documents, agencies can enhance 
collaboration  and  streamline  processes.  This  framework  promotes  best  practices  in  data 
management  and  encourages  innovation  by  enabling  seamless  data  integration  across 
various platforms and services. 

Implementation plans and monitoring processes 

It is important that governments establish processes to ensure the effective implementation of their 
policies  and  strategies  and  to  ensure  continuous  updates  to  maintain  their  relevance.  Table 14 
presents an overview of how countries responded to the questions on this topic. 

Table 14: Countries’ responses to questions on implementing plans and monitoring processes 

Are  there  processes  to  ensure  that  the 
open  data  policies/strategy  previously 
mentioned are implemented? 

Do  you  update  your  policy/strategy  as 
appropriate to ensure its success, such as 
based on data collected for monitoring? 

EU-27 

EFTA 

All Member States (100 %), with Belgium 
and  Portugal  as 
recent 
additions, report that they have processes 
to ensure that their open data policies and 
strategies are implemented. 

the  most 

All  three  participating  EFTA  countries 
report that they have processes to ensure 
that 
their  open  data  policies  and 
strategies are implemented. 

19 Member States (70 %) report that they 
have procedures in place to update  their 
policy/strategy as appropriate. 

Norway and Switzerland report that they 
have procedures in place to update  their 
policy/strategy as appropriate. 

Candidate  Albania,  Serbia  and  Ukraine  report  that 
they have processes to ensure that their 
open  data  policies  and  strategies  are 
implemented. 

Albania,  Serbia  and  Ukraine  report  that 
they  have  procedures  in  place  to  update 
their policy/strategy as appropriate. 

The most frequently mentioned mechanism for ensuring the implementation of open data strategies 
and policies is regular progress monitoring. In many cases, the monitoring of progress is mandated by 
the  open  data  strategies  and  policies  themselves.  Additionally,  many  countries  have  designated 

(Questions P23 and P24) 

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agencies or councils that are responsible for overseeing the implementation of open data policies and 
for  providing  support  to  ensure  the  process  runs  smoothly.  For  example,  Hungary  mandated  the 
creation of the  National Data  Asset  Council to support the implementation of its  open data policy, 
while Estonia created the National Open Data Team in collaboration with multiple agencies to monitor 
open data plans and provide technical support. 

Highlight from Ireland – iterative development and continuous improvement 
Ireland employs an iterative process to developing and updating its national open data strategy, 
emphasising continuous improvement. The Open Data Unit collaborates with a stakeholder working 
group  to  draft  the  strategy,  which  outlines  specific  goals,  objectives  and  action  plans.  After 
incorporating public feedback on the draft, the strategy is finalised and submitted for review and 
approval by the governance board and other stakeholders before being presented to the cabinet for 
government endorsement. 

Once  approved,  the  Open  Data  Unit  oversees  the  implementation  of  the  strategy’s  initiatives, 
collaborating with various government agencies and stakeholders. The unit actively monitors user 
needs and collects  feedback  from data publishers and users  to ensure that the  strategy  remains 
effective. This ongoing communication facilitates the identification of necessary revisions to adapt 
to evolving needs and challenges, initiating a new development cycle. 

The  most  recent  updates  to  the  strategy,  covering  2023  to  2027,  focus  on  three  key  pillars: 
supporting  data  publishers,  maintaining  the  open  data  platform  and  engaging  users.  This  shift 
towards  a  more  user-centric  approach  includes  strengthening  communication channels  between 
data publishers and users to better tailor data offerings to their needs. 

In some cases, countries emphasise specific aspects of the policies and strategies for monitoring. For 
example, open data availability and quality are prominent focuses of countries’ monitoring efforts (e.g. 
as  mentioned  by  Czechia,  Italy,  Luxembourg,  Poland,  Sweden  and  Ukraine).  This  includes  tracking 
metadata quality, ensuring compliance with legislation, and assessing data availability and publication 
timelines. 

Publishing annual reports is a frequent way in which countries monitor their progress. These are either 
made publicly available (e.g. in Albania, Bulgaria, Czechia, Lithuania, Poland, Portugal and Serbia) or 
submitted to federal parliament or institutions overseeing the governance of open data in the country 
(e.g.  in  Croatia,  Germany,  Ireland,  Slovenia  and  Ukraine).  In  addition,  France,  Italy  and  Portugal 
provide online tools, such as public dashboards, to monitor the implementation of open data policies 
in a transparent manner. 

In  terms  of  updating  policies/strategies,  many  countries  have  scheduled  policy  updates  whereby 
policies  are  reviewed  and  amended  based  on  a  predetermined  time  frame.  Others  employ  more 
adaptive approaches, updating policies when needed. Countries have various means of informing the 
content and timing of their policy updates. For example, Latvia, Norway and Spain highlight the need 
to align with international standards (e.g. EU legislation and the UN’s sustainable development goals) 
and maintain consistency with broader frameworks, which serves as a key driver for updating their 
open data policies and strategies. Similarly, Estonia and Portugal note that they update their policies 
and strategies based on the emergence of new technologies. 

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Monitoring charging practices relating to open data 

Legal frameworks often mandate different processes to ensure that public bodies understand when 
they can charge above the marginal costs and which bodies are permitted to do so. Table 15 presents 
an overview of how countries responded to the question on this topic. 

Table 15: Countries’ responses to the question on monitoring charging practices 

EU-27 

EFTA 

Are there any processes in place to assess if public sector bodies are charging for data 
above the marginal costs? 
25 Member States (92 %), all except Hungary and Sweden, report that they 
implement processes to assess if public bodies charge above the marginal costs for 
the data they provide. Romania is the most recent addition to this group. 

Iceland and Norway report that they implement processes to assess if public bodies 
charge above the marginal costs for the data they provide. 

Candidate 

Serbia, Ukraine and, the most recent addition, Albania, report that they implement 
processes to assess if public bodies charge above the marginal costs for the data 
they provide.  

(Question P25) 

The majority of countries have put in place clear legal frameworks that stipulate in what cases public 
sector bodies can charge fees for data and how high these fees can be. Croatia notes that its decree 
also includes an audit of its methodology to determine prices. Often, an open data team or legal body 
(e.g. executive branches or courts) applies the rules set out in these decrees and laws and coordinates 
assessments of cases in which fees apply, ensuring they comply with cost regulations. 

Often, countries will have publicly available lists of which public bodies are allowed to charge above 
the marginal costs, how much they are allowed to charge and sometimes (as in the case of France and 
Latvia) the methodology for determining the pricing of paid services, and the procedure for approving 
the pricing. France notes that its price list will be reviewed at least every five years and that the details 
of calculations are published jointly in electronic form on the website of the administration concerned. 
In the cases of Ireland and Austria, public bodies are responsible for notifying the national government 
regarding their choice to charge fees. 

On the other hand, Bulgaria, Iceland and Spain note that the onus is on the data requesters interested 
in  accessing  data  to  report  if  they  are  being  overcharged.  This  typically  involves  reporting  to  a 
committee, a court or the department overseeing open data matters, which then decides whether the 
data provider will need to change its fees. Spain provides an option in its national catalogue for users 
to  report  whether  public  sector  agencies  are  charging  above  the  marginal  costs  for  data,  and  the 
platform administrator team will evaluate it. 

Data literacy training and open data publication activities 

Activities to support open data  publication are  initiatives designed to assist data holders in making 
their data publicly available in an open and accessible format. These activities, which can come in the 
form of training programmes, often coincide with efforts to develop civil servants’ competencies with 
data. Countries can help to ensure that public sector staff are well equipped to handle data-related 
responsibilities  by  aligning  open  data  support  with  professional  development  efforts.  Table 16 
presents an overview of how countries responded to the questions on this topic. 

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2024 Open Data Maturity Report 

Table 16: Countries’ responses to questions on open data publication and data literacy training 

EU-27 

EFTA 

Are  there  any  activities  in place  to  assist 
data holders with publishing their data as 
open data? 

Is  there  a  professional  development  or 
training  plan  for  civil  servants  working 
with data in your country? 

26  Member  States  (96 %),  all  except 
Bulgaria, have activities in place to assist 
data  providers  with  their  open  data 
publication. 

All  three  participating  EFTA  countries 
report  having  activities  in  place  to  assist 
data  providers  with  their  open  data 
publication. 

26  Member  States  (96 %),  all  except 
Malta, report that they offer professional 
training  to  civil  servants  working  with 
open data. Latvia is the latest addition to 
this group. 

All  three  participating  EFTA  countries 
report  offering  professional  training  to 
civil servants working with open data. 

Candidate  Albania, Serbia and Ukraine report having 
activities in place to assist data providers 
with their open data publication. 

Albania,  Serbia  and  Ukraine  report  that 
they  offer  professional  training  to  civil 
servants working with open data. 

(Questions P27 and P28) 

Structured training programmes on open data and data governance are common in most countries to 
equip  civil  servants  with  the  necessary  skills  for  working  with  open  data.  These  courses  are  often 
provided  by  government  and  public  institutions  and  are  usually  accessible  asynchronously  for  civil 
servants via digital learning platforms (e.g. in Italy (Syllabus), the Netherlands (RADIO) and Finland 
(eOppiva)).  Several  countries  also  collaborate  with  external  organisations  to  offer  specialised  data 
training, such as universities, academic institutions and private companies (e.g. Greece collaborates 
with Microsoft and Oracle to provide official certification in digital competencies for civil servants). 
Many countries note that they provide on-demand support services to data holders based on specific 
needs. 

Cyprus  and  Sweden  note  that  public  sector  bodies  that  wish  to  publish  their  data  must  appoint 
designated open data personnel, who undergo a training programme and are responsible for ensuring 
the publication of open data on behalf of that organisation. 

Providing technical support for publishing open data is commonplace in all countries. This can come in 
various forms, such as creating automated data publication scripts (Luxembourg), providing assistance 
on publication aspects such as API standards (Austria), developing custom harvesters for large data 
publishers  (Serbia)  or  providing  resources  to  smaller  public  bodies  such  as  a  shared  metadata 
catalogue (Sweden). Additionally, Denmark and Estonia note that they provide financial assistance to 
data holders to encourage them to publish their data. 

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2024 Open Data Maturity Report 

Highlight from Luxembourg – activities to support data owners 
In Luxembourg, various activities are implemented to assist data owners in opening their datasets. 
These initiatives include the following. 

•  Advisory  meetings.  During  these  meetings,  data  owners  discuss  their  datasets  and 
inventory  documents,  allowing  obstacles  to  be  identified  that  may  have  hindered  data 
openness. The team provides legal guidance and technical support as needed. 

•  Harvester scripts development. The team regularly develops custom harvester scripts after 
collaborating with data owners to obtain their feedback and consent regarding licensing, 
description and data validity. 

•  Publication script guidance. Assistance is offered to data owners who are writing their own 
automatic publication scripts, ensuring that they have the necessary support for successful 
data sharing. 

•  Central  infrastructure  maintenance.  The  creation  and  maintenance  of  centralised 
infrastructures,  such  as  the  national  Inspire  platform,  the  geoportal  and  the  HVD4Gov 
platform (currently under construction), facilitate the preparation, description, modification 
and publication of data. These infrastructures establish a clear workflow that ensures that 
data  becomes  accessible  as  open  data,  searchable,  downloadable or  usable  via  APIs  and 
web services on the national open data portal. 

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Chapter 5: Open data portals 

Public  sector  organisations  at  the  European,  national  and  local  levels  create  open  data  portals  to 
publish  open  data  and  make  it  easily  accessible  to  anyone  who  wishes  to  use  it.  These  websites 
function as directories to help users find public data resources. Rather than serving only as storage 
sites,  these  portals  often  act  as  metacatalogues,  focusing  on  making  data  stored  elsewhere  easily 
discoverable in a central location. Governments that operate these portals usually engage in a range 
of activities to promote the availability and reuse of public sector information. In this broader context, 
portals also play a key role in raising awareness about open data and encouraging its reuse among 
users. 

The portal dimension of the open data maturity (ODM) assessment is designed to encourage national 
portals  to  offer  features  and  functionalities  that  meet  user  needs  and  deliver  a  positive  user 
experience.  A  well-designed,  user-friendly  portal  can  boost  the  adoption  of  open  data  and  help 
transform casual users into active reusers. 

In brief, the portal dimension investigates the functionality of national open data portals, how user 
needs and behaviours are incorporated into portal improvements, the availability of open data across 
various  sectors  and  strategies  to  ensure  the  portal’s  long-term  sustainability.  Table 17  provides  an 
overview of the indicators used to assess the portal dimension. 

Table 17: Indicators of the portal dimension 

Indicator 

Portal features 

Portal usage 

Data provision 

Key elements 

Portal features ensure access to datasets and relevant content, and include 
more advanced features such as SPARQL Protocol and RDF Query Language 
(SPARQL) search, discussion forums, rating of datasets, means of requesting 
datasets and transparency on the status of requested datasets. Activities are 
conducted to promote the visibility and reuse of high-value datasets (HVDs) 
through the portal. 

Traffic to the portal is monitored, and analytics tools are used to gain insights 
into  users’  behaviour  and  the  most  and  least  consulted  data  categories.  In 
addition,  the  portal  offers  application  programming  interfaces  (APIs)  or 
SPARQL end points through which advanced users can access the metadata 
programmatically. 

Most  data  providers contribute data to the national portal, and actions are 
taken  to  support  data  publication.  In  addition,  access  to  real-time  data  is 
provided through the portal, and data that does not stem from official sources 
(e.g.  citizen-generated  data)  can  be  uploaded.  Furthermore,  data  from 
regional or local sources is discoverable on the national portal. 

Portal 
sustainability 

A strategy to ensure the sustainability of the portal has been determined, and 
activities are conducted to ensure the portal’s visibility, including through a 
social media presence. In addition, user surveys are conducted regularly and 
feed into a review process to improve the portal. 

This  chapter  will  first  present  overall  performance  on  the  portal  dimension  and  then  provide  a 
summary of the results and best practices for each indicator. 

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Contents 

5.1. Overall performance on the portal dimension ......................................................................... 55 

5.2. Portal features ........................................................................................................................... 59 

Overview of the national portals ................................................................................................... 59 

Preview functions .......................................................................................................................... 62 

Providing feedback on the portal .................................................................................................. 62 

High-value datasets ....................................................................................................................... 64 

Requesting datasets and providing transparency ......................................................................... 64 

Actively involving users ................................................................................................................. 66 

Enhancing the open data culture .................................................................................................. 67 

Providing examples of open data reuse ........................................................................................ 68 

5.3. Portal usage ............................................................................................................................... 68 

User analytics ................................................................................................................................ 69 

Enhancing the performance of national portals ........................................................................... 69 

Most popular data domains .......................................................................................................... 71 

Application programming interfaces ............................................................................................. 72 

5.4. Data provision ............................................................................................................................ 73 

Official data providers ................................................................................................................... 73 

Non-official data providers ............................................................................................................ 74 

Assistance for data providers ........................................................................................................ 75 

Regional and local data sources .................................................................................................... 75 

Access to real-time and dynamic data .......................................................................................... 77 

5.5. Portal sustainability ................................................................................................................... 78 

Strategy and visibility .................................................................................................................... 78 

Availability of documents to the public ......................................................................................... 79 

Monitoring performance ............................................................................................................... 79 

5.6. Pilot indicator: automated tests of portal performance .......................................................... 82 

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5.1. Overall performance on the portal dimension 

In 2024, the portal dimension is the second-best performing dimension among the EU-27, achieving a 
maturity score of 82 % (Figure 10). This is despite its being the only dimension to have experienced a 
decreased score compared with 2023, with a drop of 3 percentage points (pp). The reduced score on 
the portal dimension in 2024 can be attributed to a decrease in all four of the underlying indicators in 
this dimension, with the ‘portal features’ indicator showing the largest decline (– 6 pp). This decline 
may be partially influenced by changes in the methodology, including introducing new questions that 
set higher requirements. 

Figure 10: The EU-27 average score on the portal dimension decreased year-on-year 

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Regarding  individual  country  performance,  Poland  stands  out  as  the  only  participating  country  to 
report having conducted all of the activities assessed in the questionnaire, earning a 100 % score on 
this dimension, a 2 pp increase from 2023 (Figure 11). France follows closely in second place, with a 
maturity score of 98.5 % (a 2 pp increase from 2023). In total, 20 countries surpass the EU average of 
82 %, with 11 countries achieving scores above 90 %. Notably, among these are Ukraine, a candidate 
country with a score of 94 %, and Norway, a European Free Trade Association (EFTA) country with a 
score of 91 %. 

Czechia (+ 20 pp) and Croatia (+ 14 pp) achieved double-digit improvements in their maturity scores 
compared  with  2023.  Albania  (+ 9 pp)  and  Slovakia  (+ 9 pp)  are  also  among  the  most  improved 
countries in this dimension. Czechia’s improved maturity can be attributed to progress across all four 
indicators  of  the  portal  dimension.  The  country  achieved  a  notable  increase  in  the  ‘portal  usage’ 
indicator (+ 48 pp), reflecting a focus on enhancing user engagement, including monitoring trends and 
user preferences and enabling regular updates to better align the portal’s offerings with user demand. 
Many countries, including Czechia, have integrated capabilities for programmatic metadata queries via 
APIs and SPARQL access points, demonstrating a well-defined technology stack. The Comprehensive 
Knowledge Archive Network (CKAN) remains the most widely adopted platform, followed by Udata 
and LinkedPipes. The LinkedPipes extract, transform and load (ETL) tool, the LinkedPipes Data Catalog 
Vocabulary – Application Profile (DCAT-AP) viewer and Openlink Virtuoso are used by Czechia, which 
bases its implementation on open-source DCAT-AP-compliant tools. 

Highlight from Czechia – analysing users’ experiences through a questionnaire 
One  of  the  key  practices  highlighted  in  this  year’s  report  is  basing  portal  improvements on  user 
feedback. 

Czechia, for example, initiated research at the beginning of 2024 focused on users’ experiences of 
its  national  portal  and  data  catalogue.  The  research  involved  a  questionnaire,  distributed  via  a 
newsletter and published on the portal, and direct interviews and focus group sessions with users. 
The  findings  from  this  research  are  currently  being  analysed  and  will  inform  the  strategy  for 
developing the portal in 2025. 

Read more about this trend in Section 5.3. 

Croatia saw a large improvement in the ‘data provision’ indicator (+ 21 pp). Croatia allows both official 
and  non-official  providers  to  publish  open  datasets,  and  the  national  portal  aggregates  data  from 
various local and regional portals across the country. However, a common challenge, also reported by 
other countries, has been the incomplete harvesting of metadata from all local and regional portals. 
While some countries automatically harvest the data from other sources, other countries strike ad hoc 
agreements  with  regional  and  local  bodies  to  extract  their  data.  Croatia  has  set  up  an  automated 
synchronisation system with three of the seven regional and local portals identified, specifically those 
of Rijeka, Zagreb and Varaždin. This advancement ensures that the national portal is updated more 
frequently, moving Croatia closer to establishing a comprehensive one-stop shop for data across the 
country. 

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2024 Open Data Maturity Report 

Figure 11: The majority of countries had a decreased score on the portal dimension in 2024. (YoY: 
year-on-year). 

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2024 Open Data Maturity Report 

Highlight from Croatia – supporting local and regional portals in publishing metadata 
One  of  the  key  practices  highlighted  in  this  year’s  report  is  countries  providing  support  to  data 
providers at the local and regional levels to increase the quality and quantity of data on the national 
portal. 

The Central State Office for the Development of Digital Society and the Information Commissioner 
in Croatia play key roles in supporting public authorities and users in the process of publishing open 
data. As government bodies responsible for promoting and facilitating the publication of open data 
at  both  the  national  and  the  local  levels,  they  provide  comprehensive  assistance  through  the 
following activities. 

•  Online education (webinars). They organise webinars focused on open data, where public 
authorities and other interested parties receive training on the importance of open data, 
the processes involved in publishing metadata and how to effectively manage and use open 
data. These webinars serve as a key resource for building capacity and awareness among 
data publishers. 

•  Guidelines on reuse of open data. They provide detailed guidelines aimed at helping public 
authorities understand how to reuse open data. These guidelines outline the best practices 
for publishing metadata, ensuring the data’s quality and encouraging its use in innovation 
and decision-making processes by various stakeholders. 

•  Direct communication and assistance. They maintain open channels of communication via 
email and over the telephone, through which public authorities can seek advice on their 
legal  obligations  to  publish  open  data  on  the  national  open  data  portal.  They  also  offer 
technical and legal assistance in ensuring the smooth publication and management of this 
data, helping authorities to comply with relevant laws and standards. 

Read more about this trend in Section 5.4. 

Slovakia  achieved  full  maturity  scores  on  the  ‘portal  usage’  and  ‘portal  sustainability’  indicators. 
Countries  with  high  maturity  in  portal  sustainability,  like  Slovakia,  have  long-term  strategies  for 
maintaining the  national portal. This includes making the portal’s  source  code, documentation and 
other  relevant  artefacts  publicly  accessible,  often  hosted  on  platforms  like  GitHub  or  GitLab.  Such 
transparency and open access to resources foster community trust and allow developers to contribute 
to ongoing improvements, reinforcing the portal’s sustainability and adaptability over time. 

Highlight from Slovakia – the SPARQL end point 
One of the key practices highlighted in this year’s report is the offering of tools to data providers to 
assist them with publishing data. 

Slovakia has implemented a SPARQL end point with predefined queries to assist data providers in 
monitoring  and  improving  the  quality  of  their  metadata.  This  tool  allows  providers  to  track  key 
metrics, such as metadata quality, and to benchmark their performance against other providers. 
With  these  insights,  providers  can  more  effectively  ensure  that  their  data  aligns  with  national 
standards and user expectations. 

Additionally, a dedicated web page offers an overview of basic statistics. This web page provides an 
overview of metadata quality indicators, enabling providers and stakeholders to easily assess the 
consistency and completeness of the metadata available on the national platform. The goal is to 
promote  high  standards  in  metadata  management  and  to  facilitate  continuous  improvement 
through accessible, data-driven insights, thereby leading to increases in the usability of the datasets 
and supporting a more transparent and reliable open data ecosystem. 

Read more about this trend in Section 5.4. 

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2024 Open Data Maturity Report 

Albania achieved the most significant progress on the ‘portal sustainability’ indicator (+ 48 pp), with 
progress  also  made  on  the  ‘portal  features’  indicator  (+ 7 pp).  Key  improvements  included 
implementing  a  long-term  strategy  to  ensure  the  portal’s  sustainability  and  initiating  regular 
monitoring of published data characteristics, such as category distribution, the ratio of static to real-
time data and how these metrics evolve over time. This monitoring process allows the portal team and 
data providers to make informed improvements, ensuring higher performance and more relevant data 
offerings on the national portal. 

Highlight from Albania – action plan for portal sustainability  
One of the key practices highlighted in this year’s report is the setting up of long-term strategy plans 
for better maintenance of the portal. 

For  example,  in  Albania,  the  National  Agency  of  Information  Society,  which  oversees  the 
opendata.gov.al  portal,  has  appointed  dedicated  contacts  who  coordinate  regularly  with 
representatives from other institutions to boost the number of available datasets. Additionally, the 
agency collaborates closely with the Prime Minister’s Office, which plays a key role in leading high-
level  initiatives,  including  the  preparation  of  annual  reports  and  documentation  for  the  Open 
Government Partnership. These reports are made publicly accessible on opendata.gov.al. As part of 
the World-Bank-supported programme ‘Improving equitable access to high-standard, sustainable 
public services at central and sub-national levels’, an action plan and strategy are being developed 
to enhance the open data portal’s functionality and ensure its long-term sustainability. 

Read more about this trend in Section 5.5. 

5.2. Portal features 

This  indicator  assesses  both  basic  and  advanced  features  of  national  open  data  portals.  Basic 
functionalities  include  advanced  search  options  (e.g.  multifield  searches  and  filtering),  dataset 
downloads and the ability to search by file format or data domain. More advanced portals allow users 
to access data programmatically through APIs or SPARQL queries. This indicator also looks at whether 
users can request and rate datasets and if the portals showcase reuse cases. Additionally, it evaluates 
features  that  promote  online  interaction  between  data  providers  and  users,  including  discussion 
forums, feedback channels and notifications for new datasets. 

Overview of the national portals 

All participating countries, except Bosnia and Herzegovina, have a national open data portal. However, 
there  are  some  local open  data  portals  in  Bosnia  and  Herzegovina.  To ensure more  advanced  and 
flexible search capabilities, many national open data portals provide APIs (26 EU Member States; 96 %) 
or SPARQL end points (12 Member States; 44 %), along with documentation, to enable programmatic 
querying of metadata. These  tools allow  users and developers to interact  directly with the portal’s 
underlying  data  structures,  facilitating  sophisticated  searches  beyond  what  is  possible  through  a 
standard  web  interface.  Table 18  provides  an  overview  of  the  key  features  of  national  open  data 
portals. 

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Table 18: Overview of national open data portals for all of the 2024 ODM participants 

Country 

National portal 
website 

Member States 

Belgium 

https://data.gov
.be/en 

Bulgaria 

https://data.ego
v.bg 

Czechia 

Denmark 

https://data.gov
.cz/english 
www.datavejvis
er.dk 

Germany 

https://www.go
vdata.de 

Estonia 

https://avaand
med.eesti.ee 

Ireland 

Greece 

Spain 

France 

Croatia 

Italy 

Cyprus 

Latvia 

Lithuania 

Luxembourg 

Hungary 

https://data.gov
.ie 
https://data.gov
.gr 
http://repositor
y.data.gov.gr 
https://datos.go
b.es/en 
https://www.da
ta.gouv.fr 
https://data.cod
eforcroatia.org/  
https://dati.gov.
it 
https://www.da
ta.gov.cy/ 
https://data.gov
.lv/eng 
https://data.gov
.lt/?lang=en 
https://data.pu
blic.lu/en 
https://kozadat
portal.hu 

Technology stack 

API present? 

SPARQL access point 
present? 

Custom back end with 
Drupal front end (see 
GitHub) 
Custom, including 
Fluentd, Elasticsearch 
node, MariaDB and 
Graylog 
Custom, including 
LinkedPipes 
CKAN back end with a 
DCAT plug-in and a 
front end designed 
with React 
Custom, including the 
CMS Typo3 for 
editorial content and 
Piveau for data 
storage 
Custom, including 
Typescript, PostgreSQL 
and Solr 
CKAN 

Custom based on 
CKAN 

Yes (see API) 

Yes (see API) 

Yes (see API) 

Yes (see end point) 

Yes (see API) 

Yes (migrating 
from CKAN API 
to Piveau API) 

Yes (see end point) 

Yes (see API) 

Yes (see end point) 

Yes (see API) 

Yes (see API) 

CKAN and Drupal 

Yes (see API) 

Yes (see end point) 

Udata 

CKAN 

Yes (see API) 

Yes (see end point) 

Yes (see API) 

Yes (see end point) 

CKAN and Drupal 

Yes (see API) 

Yes (see end point) 

EKAN 

CKAN 

Self-developed 
solution in Python 
Udata 

Yes (see API) 

Yes (see API) 

Yes (see end point) 

Yes (see API) 

Yes (see end point) 

Yes (see API) 

CKAN 

Yes (see API) 

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Country 

Malta 

National portal 
website 

https://open.da
ta.gov.mt 

Technology stack 

API present? 

SPARQL access point 
present? 

Custom 

Netherlands  https://data.ove

CKAN 

Yes (see API) 

Austria 

Poland 

rheid.nl/en 
https://www.da
ta.gv.at/en 
https://dane.go
v.pl/ 

Portugal 

Romania 

Slovenia 

Slovakia 

Finland 

Sweden 

https://dados.g
ov.pt/en/ 
https://data.gov
.ro/en 
https://podatki.
gov.si 
https://data.gov
.sk/en 
https://www.av
oindata.fi/en 
https://www.da
taportal.se/en 

EFTA countries 
Iceland 

Norway 

https://opingog
n.is 
https://data.nor
ge.no 

Switzerland 

https://opendat
a.swiss/en/ 

Candidate countries 
Bosnia and 
Herzegovina 
Albania 

None 

Serbia 

Ukraine 

https://opendat
a.gov.al/en 
https://data.gov
.rs 
https://data.gov
.ua/en 

(CMS: content management system). 

CKAN and Wordpress 

Yes (see API) 

Custom, including 
Falcon, Django, 
RDFLib, Wagtail CMS, 
Typescript 
(microservice 
architecture) 
Udata 

CKAN 

CKAN 

Custom, including 
LinkedPipes 
CKAN 

Yes (see API) 

Yes (see end point) 

Yes (see API) 

Yes (see API) 

Yes (see API) 

Yes (see end point) 

Yes (see API) 

Yes (see end point) 

Custom, including 
EntryScape, the Strapi 
CMS and NodeBB 

Yes (see API) 

CKAN 

Custom, including 
React, Java/Kotlin, 
Python, Jena, Fuseki, 
Elasticsearch, 
PostgreSQL, MongoDB 
and Kafka 
CKAN 

Udata 

CKAN 

Yes (see API) 

Yes (see end point) 

Yes (see API) 

Yes 

Yes (see API) 

Yes (see API) 

Yes (see end point) 

(Questions PT1, PT2, PT3 and PT4) 

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Preview functions 

Making  data  more  accessible  without  requiring  downloads  can  enhance  usability,  encouraging 
individuals to engage with and analyse the data directly. This approach applies to both tabular and 
geospatial  data,  fostering  a  more  interactive  and  user-friendly  experience.  Table 19  presents  an 
overview of how countries responded to the questions on this topic. 

Table 19: Countries’ responses to questions on preview functions 

Does the national portal offer a preview 
function for tabular data? 

Does the national portal offer a preview 
function for geospatial data? 

EU-27 

18 Member States (67 %) report that 
they offer a preview function for 
tabular data. 

EFTA 

Norway and Switzerland report having 
preview functions for tabular data. 

Candidate  Albania, Serbia and Ukraine report 
having preview functions for tabular 
data. 

15 Member States (56 %) report having a 
preview function for geospatial data. This 
is an increase from 2023, with Croatia, 
France and Sweden the latest additions to 
this group. 

Norway and Switzerland report having 
preview functions for geospatial data. This 
remained stable from 2023. 

Albania and Ukraine report having a 
preview function for geospatial data. 

(Questions PT20 and PT21) 

In  most  portals,  users  can  activate  a  ‘preview’  feature  to  quickly  explore  data  without  needing  to 
download it. This is true of a diverse range of datasets. For example, in  Albania, users can preview 
datasets on healthcare centres and fuel imports. In Sweden, geospatial data such as air humidity can 
be viewed, while, in Estonia, users can explore data on ports. 

Providing feedback on the portal 

To  encourage  continued  improvement  and  usability  of  the  national  portal,  countries  can  offer  a 
mechanism for users to provide general feedback, such as a ‘Contact us’ or ‘Feedback’ button placed 
in a visible spot that allows users to send a general comment concerning the portal. Feedback can also 
be  specific  to  certain  datasets.  Table 20  presents  an  overview  of  how  countries  responded  to  the 
questions on this topic. 

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Table 20: Countries’ responses to questions on portal feedback mechanisms 

EU-27 

EFTA 

Does the national portal 
offer a mechanism for users 
to provide general 
feedback? 

Does the national portal 
offer a mechanism for 
users to provide feedback 
on specific datasets? 

Does the national portal 
provide a mechanism for 
users to rate datasets? 

25 Member States (93 %) 
enable users to provide 
general feedback on the 
portal. Czechia and 
Luxembourg newly report 
offering this feature. 

All three participating EFTA 
countries enable users to 
provide feedback on the 
portal, with Switzerland 
newly reporting this. 

22 Member States (81 %) 
enable users to provide 
feedback on a specific 
dataset. 

14 Member States (52 %) 
enable users to rate 
datasets. Latvia and 
Poland newly report 
offering this feature. 

Iceland and Norway 
enable users to provide 
feedback on specific 
datasets. 

None of the participating 
EFTA countries enables 
users to rate specific 
datasets. 

Candidate  Albania and Ukraine enable 

users to provide general 
feedback on the portal. 

Ukraine enables users to 
rate datasets. 

Albania, Serbia and 
Ukraine enable users to 
comment on specific 
datasets. Albania is the 
latest country to report 
this. 

(Questions PT8, PT9 and PT10) 

Most  countries  offer  a  public  contact  point  on their  open  data websites,  enabling  users  to  directly 
reach out to the open data team with specific questions, ensuring user privacy in their inquiries. In 
addition, some countries support public discussion boards, on which users can post comments and 
view  issues  or  insights  shared  by  others,  fostering  a  spillover  effect  that  enhances  community 
knowledge. These boards allow users to ask questions or provide feedback on the portal as a whole or 
on individual datasets. Some systems also incorporate a rating feature, whereby users can evaluate 
datasets using a star or voting system, helping improve data quality and relevance. In Norway, users 
can publicly comment on all the resources available on the portal. If they do not want their feedback 
published online, users can also directly email the open data team. 

Highlight from Sweden – enabling users to directly contact data providers 
In Sweden, each dataset on the national portal includes a dedicated section where users can discuss 
the data and ask questions. Additionally, every dataset features a feedback button that allows users 
to  contact  the  publishing  organisation  for  inquiries,  feedback  and  requests  regarding  the 
information on this page. Users  can also  directly contact the  dataset owner through the contact 
information provided on each data page. 

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High-value datasets 

The reuse of HVDs offers significant benefits to society, the environment and the economy. Promoting 
these datasets on the portal can help boost the visibility and reuse of these datasets. Table 21 presents 
an overview of how countries responded to the question on this topic. 

Table 21: Countries’ responses to the question on HVDs 

Do you promote HVDs on your national portal? 

EU-27 

20 Member States (70 %) report actively promoting HVDs on their national portals. 

(Question PT22) 

Non-EU countries were not surveyed on this question, since Commission Implementing Regulation (EU) 
2023/138 on HVDs applies only to EU Member States. 

Common approaches to promoting HVDs on the national portal include incorporating filtering options 
to help users easily locate these datasets or using editorial tools such as labels or tags to promote their 
visibility  and  encourage  reuse.  Several  countries  have  also  created  dedicated  sections  within  their 
portals to inform users about HVDs and their significance. 

For example, Poland’s open data portal promotes various types of HVDs, which are graphically marked 
so that users can filter them. The portal also features a special section focused on HVDs, offering an 
overview  of  their  characteristics  and  updates  on  relevant  policy  developments.  Similarly,  France 
employs multiple strategies to highlight high-value data. A dedicated thematic page provides context, 
linking datasets to their practical applications, and a tagging system facilitates easy filtering. The French 
portal also includes a progress tracking dashboard, allowing users to monitor the release of public data, 
including ministerial commitments and HVDs. 

Requesting datasets and providing transparency 

Users may seek datasets that are not available on the national portal. In this case, it is valuable if they 
can  request  specific  datasets,  such  as  through  a  ‘request  data’  button.  These  requests  and  their 
progress status should be presented transparently. Table 22 presents an overview of how countries 
responded to the questions on this topic. 

Table 22: Countries’ responses to questions on requesting datasets and providing transparency 

Does the national portal 
enable users to request 
datasets? 

Are requests for datasets 
and their progress status 
presented in a transparent 
manner on the national 
portal? 

Does the team monitor 
the extent to which 
requests result in the 
publication of the 
requested data? 

EU-27 

22 Member States (81 %) 
provide the possibility for 
users to request datasets. 
This number has decreased 
by one country, Serbia, 
since 2023. 

Like in 2023, 18 Member 
States (67 %) report that 
they display the progress 
of requests on their 
national portals. 

23 Member States (85 %) 
report that they monitor 
the results of requests. 
This number has 
decreased by one 
country, Germany, since 
2023. 

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Does the national portal 
enable users to request 
datasets? 

Are requests for datasets 
and their progress status 
presented in a transparent 
manner on the national 
portal? 

Does the team monitor 
the extent to which 
requests result in the 
publication of the 
requested data? 

EFTA 

Like in 2023, Norway 
reports that it provides the 
possibility for users to 
request datasets. 

Like in 2023, Norway 
reports that it displays 
requests on its national 
portal. 

Like in 2023, Norway 
reports that it monitors 
the status of requests. 

Candidate  Albania, Serbia and 
Ukraine provide the 
possibility for users to 
request datasets. Albania 
newly reported enabling 
this. 

Ukraine reports that it 
displays requests on its 
national portal. 

Serbia and Ukraine report 
that they monitor the 
status of requests. 

(Questions PT13, PT14 and PT15) 

The open data team is often in charge of periodically assessing requests for datasets, tracking them 
and  replying  to  them.  In  some  countries,  this  is  an  automated  process  whereby  requests  are  sent 
through standardised forms and dashboards. In other countries, users request datasets via email and 
the open data team needs to assess the questions manually. 

Highlight from Spain – interacting with users 
In Spain, users can submit requests for data that is not currently available in the catalogue through 
a user-friendly, dedicated form. These requests are automatically routed to the appropriate public 
bodies,  which  evaluate  whether  the  requested  data  can  be  published  or  incorporated  into  their 
open data initiatives and future roadmaps. 

Users  also  have  the  option  to  support  existing  requests  by clicking  the  ‘join  the  request’  button 
displayed  alongside  each  dataset  request.  This  collaborative  feature  encourages  a  sense  of 
community  among  users  with  similar  data  needs,  potentially  increasing  the  priority  of  popular 
requests. All requests are managed transparently in the data availability section, where users can 
follow  each  request’s  journey  through  various  status  stages:  received,  assigned,  under  study, 
programmed, published and the final outcome, which indicates if the data was released or provides 
an explanation if it was declined. This section also provides historical tracking. 

Over  the  past  year,  Spain  has  actively  responded  to  user  data  demands,  fulfilling  31  new  data 
requests.  This  approach  not  only  enhances  the  responsiveness  of  public  data  services  but  also 
fosters a more engaged and data-driven citizenry. 

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Actively involving users 

Users can be a source of citizen-generated data, including open data that they have processed into 
new  forms.  This  can  help  national  portals  increase  the  variety  of  available  data  and  enhance  the 
community’s  engagement.  When  new  datasets,  whether  from  official  or  non-official  sources,  are 
published, national portals could notify users to enhance the reach of open data. Table 23 presents an 
overview of how countries responded to the questions on this topic. 

Table 23: Countries’ responses to questions on actively involving users 

Does the national portal provide the 
functionality for users to contribute 
datasets that they have produced or 
enriched? 

Does the national portal offer the 
possibility for users to receive 
notifications when new datasets are 
available on the national portal? 

EU-27 

EFTA 

18 Member States (67 %) report that they 
enable users to actively publish datasets 
on the national portal. There has been a 
sharp decrease in the number of 
countries that allow users to publish 
datasets. Unlike in 2023, Czechia, Greece, 
Croatia, Italy, Malta, Romania and 
Slovenia no longer report offering this 
feature. 

Norway reports that it enables users to 
publish datasets on the national portal. 
Unlike in 2023, Iceland and Switzerland 
no longer report implementing this 
feature. 

Candidate 

Albania, Serbia and Ukraine report that 
they enable users to publish datasets. 

20 Member States (74 %) report that 
they notify users when new datasets 
are available. 

Norway and Switzerland report that 
they notify users when new datasets 
are available. 

Serbia and Ukraine report offering 
notifications on new content being 
published, with Serbia the newest 
addition to this group. 

(Questions PT7 and PT12) 

This year, there has been a noticeable decline in the number of users permitted to publish data on 
national open data portals. Many portals now restrict data publishing rights exclusively to official data 
providers, limiting contributions from citizens and other independent actors. Conversely, countries are 
enhancing user engagement by introducing more proactive notification systems, allowing users to be 
promptly informed whenever a new dataset is published. 

In  Sweden,  any  user  who  has  created  a  dataset  can  publish  it  on  the  national  portal,  along  with 
supporting materials such as documentation or test cases. This is done through the ‘admin’ tool, which 
is accessible after logging in. In Latvia, users can subscribe to a newsletter to receive notifications when 
new datasets are uploaded. Meanwhile, in Portugal, users can opt to be notified about specific dataset 
activities by clicking the star button. Notifications are then sent via email and directly to the user’s 
administration area on the portal. 

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Enhancing the open data culture 

To further engage  users, national data  portals often provide  functionality that enables reusers and 
data providers to interact. At the same time, many national portals provide a space to find information, 
events and news on relevant open data topics in the country. These features enhance the open data 
culture by allowing interaction between users and updating them on the ongoing trends in the field. 
Table 24 presents an overview of how countries responded to the questions on this topic. 

Table 24: Countries’ responses to questions on enhancing the open data culture 

Does the national portal enable users to 
find information and news on relevant 
open data topics in the country? 

Does the national portal offer a mechanism 
through which users can undertake 
exchanges with others? 

EU-27 

22 Member States (81 %) report 
publishing information on open data 
topics in the country. 

19 Member States (70 %) report providing 
a space for dialogue on their national 
portal, such as a discussion forum. This 
number has decreased by one country 
since 2023. 

EFTA 

Norway and Switzerland report 
publishing information on open data 
topics in the country. 

Norway reports offering a mechanism for 
users to exchange information with other 
users. 

Candidate  Serbia and Ukraine report updating 

users on open data topics. 

Serbia and Ukraine report enabling users 
to interact with each other on the national 
portal. 

(Questions PT11 and PT16) 

Most countries publish information and updates on open data topics through their national portals. 
Lithuania, for instance, has a dedicated blog page for the latest news. Ireland has a news section on 
its portal and distributes a newsletter. 

In terms of dialogue functionality, Austria, for example, uses the GitHub platform to facilitate public 
discussions.  Questions  are  directed  to  the  national  open  data  team,  who  respond  accordingly.  By 
categorising issues based on specific portal components, it becomes easier for other users to search 
for  and  participate  in  relevant  discussions.  This  public  format  also  allows  data  publishers  directly 
affected by the query to respond to the user. In some cases, countries have decided not to provide this 
feature. For example, Finland has removed the discussion board from its national open data portal due 
to low usage and significant security concerns. The forum was frequently flooded with fake accounts 
posting  spam  and  advertisements,  requiring  extensive  manual  moderation.  Previously,  moderation 
support was provided by Disqus, which could automatically block spam and bots; however, due to EU 
data protection regulations, Disqus is no longer a viable option, since it is headquartered in the United 
States and does not comply with EU privacy standards. A thorough evaluation of other open-source 
solutions  revealed  similar  vulnerabilities  that  did  not  meet  the  Finnish  Digital  Agency’s  security 
policies.  As  a  result,  Finland  does  not  plan to  reintroduce  the  discussion  board  feature  in the  near 
future. 

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Providing examples of open data reuse 

Making open data available for reuse is one of the primary purposes of open data portals. Showcasing 
reuse examples is one way to inspire reusers and stimulate the uptake of open data. Countries may 
provide the possibility for users to submit their own reuse examples as a way to enrich the showcase 
on the national portal and give the open data team a better overview of what their datasets are being 
reused for and how. Table 25 presents an overview of how countries responded to the questions on 
this topic. 

Table 25: Countries’ responses to questions on showcasing open data reuse examples 

Does the national portal 
showcase reuse 
examples, such as in a 
designated section of the 
portal? 

25 Member States (93 %) 
report highlighting reuse 
cases in a designated 
section of their portals. 
Sweden newly reported 
doing this. 

Norway and Switzerland 
report highlighting reuse 
cases in a designated 
section of their portals. 

Does the national portal 
reference the datasets that 
the showcased reuse 
examples are based on? 

Does the national portal 
provide the possibility for 
users to submit their own 
reuse cases? 

21 Member States (78 %) 
report linking reuse cases 
to the underlying datasets. 

21 Member States (78 %) 
report enabling users to 
submit their own reuse 
cases. 

Norway and Switzerland 
report linking reuse cases 
to the underlying datasets. 

Norway and Switzerland 
report enabling users to 
submit their own reuse 
cases. 

EU-27 

EFTA 

Candidate  Serbia and Ukraine 

report highlighting reuse 
cases in a designated 
section of their portals. 

Serbia and Ukraine report 
linking reuse cases to the 
underlying datasets. 

Serbia and Ukraine report 
enabling users to submit 
their own reuse cases. 

(Questions PT17, PT18 and PT19) 

Most countries showcase reuse examples on their portal (this topic is investigated in more detail in 
Chapter 4 of this report). For instance, the Italian national open data portal tags use cases, enabling 
users  to search  for  them easily.  Additional tags may  be  applied  if  the  use  case  is  linked  to  specific 
events, news articles, data stories or webinars. In Switzerland, each reuse case includes a dedicated 
‘datasets in showcase’ section, allowing users to find the referenced datasets used by the reuse case. 

5.3. Portal usage 

This indicator evaluates whether portal administrators frequently assess the alignment of the portal’s 
design, features and available data with user needs. Although direct feedback from users is useful, it 
can often be anecdotal. Therefore, this indicator also explores whether systematic monitoring of portal 
usage is employed to gain a broader insight into user behaviour. Specifically, it looks into whether data 
on the number of unique visitors, common user profiles, the most accessed datasets, preferred data 
categories and traffic generated through the portal’s APIs is collected and analysed. 

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User analytics 

It is important that countries are aware of the usage of portals to better direct their efforts to increase 
the supply and reuse of open data. These questions aim to understand whether countries monitor the 
portal’s  traffic.  Moreover,  countries  can  also  perform  other  activities  to  better  understand  the 
behaviour and needs of users of their portals, such as web analytics, surveys and analysis of social 
media feeds. Table 26 presents an overview of how countries responded to the questions on this topic. 

Table 26: Countries’ responses to questions on user analytics 

Do you monitor the portal’s traffic? 

EU-27 

All 27 Member States report that they 
monitor the portal’s traffic. This 
number has decreased by one country, 
Czechia, since 2023. 

EFTA 

All participating EFTA countries report 
that they monitor the portal’s traffic. 

Besides monitoring portal traffic, do you 
perform any further activities to better 
understand the behaviour and needs of 
users of your portal? 

23 Member States (85 %) report that they 
conduct other activities to understand 
users’ needs. 

All participating EFTA countries report that 
they conduct other activities to understand 
users’ needs. 

Candidate  All participating candidate countries 
report that they monitor the portal’s 
traffic. 

Serbia and Ukraine report that they 
conduct other activities to understand 
users’ needs. 

(Questions PT23 and PT25)  

Countries use various analytics tools to monitor the popularity of datasets and gain insights into how 
to improve the quality of the datasets. The most popular tools include Matomo Web Analytics, Google 
Analytics and Piwik PRO. 

Furthermore, social media platforms are widely used to monitor user behaviour, and many countries 
use surveys and interviews to gather direct feedback from users. Norway, for instance, uses a dual 
approach: first, it uses Monsido for analytics to track portal usage; it then conducts surveys to validate 
its hypotheses and identify ways to enhance the website based on user needs. Iceland, on the other 
hand, analyses communications from users who contact the open data team. By examining the reasons 
for contact and compiling statistics on common issues, they can assess whether improvements  are 
necessary. 

Enhancing the performance of national portals 

Assessing user analytics  for insights  and following these up with concrete  improvements can allow 
national portals to serve their users better. Similarly, national portals undertake activities to promote 
the  portal  and  attract  new  users  or  new  audiences  to  enhance  the  impact  of  open  data.  Table 27 
presents an overview of how countries responded to the questions on this topic. 

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Table 27: Countries’ responses to questions on enhancing the performance of national portals 

Do you use the insights about portal 
usage and about the behaviour and 
needs of portal users to improve the 
portal accordingly? 

Do you undertake any activities to promote 
the portal and attract new users or new 
audiences? 

EU-27 

EFTA 

24 Member States (89 %) report using 
insights from users to keep improving 
the portal. 

25 Member States (93 %) report 
conducting activities to promote and 
attract new users. 

Norway and Switzerland report using 
user insights to keep improving the 
portal. 

Norway and Switzerland report 
conducting activities to promote and 
attract new users. 

Candidate  All candidate countries, except Bosnia 

and Herzegovina, report using user 
insights to keep improving the portal. 

All candidate countries, except Bosnia and 
Herzegovina, report conducting activities 
to promote and attract new users. 

(Questions PT26 and PT27) 

User input is essential for identifying current needs and prioritising improvements to enhance national 
portal performance. In  Denmark, for example, feedback  from users is used to guide  developers on 
which features to implement. Most improvements focus on enhancing metadata and onboarding new 
authorities  based  on  the  demand  for  specific  data.  Recently,  they  introduced  the  display  of  data 
services,  a  highly  requested  feature  by  advanced  users.  They  also  added  roles  like  ‘Originator’ 
(Ophavsmand) to provide clearer attribution for datasets. In Luxembourg, user feedback revealed that 
outdated datasets were  receiving more  views than newer,  up-to-date ones on the same  topics. To 
address this, documentation for older datasets was updated to redirect users to the latest versions. 

Countries take diverse approaches to promoting open data. Serbia, for instance, launched a regional 
open  data  challenge,  requiring  participants  to  use  at  least  one  public  open  dataset  to  participate. 
Slovakia offers open and free training sessions to attract new users. Slovenia organises hackathons, 
university lectures and events for businesses and the public sector. Similarly, Romania promotes its 
open data portal through webinars, public meetings with academia and the private sector, student-
focused information sessions and presentations at relevant events such as the National Committee on 
e-Government and Red-tape Reduction. 

Highlight from Sweden – improving the data portal through user experience 
Sweden  adopted  an  innovative,  user-centred  approach  to  redesigning  its  national  data  portal, 
collaborating with web consultants who specialise in user experience to ensure that the platform 
meets the needs of diverse users. This conceptual redesign focused on user-driven design principles, 
incorporating  iterative  testing  and  continuous  feedback  to  enhance  both  functionality  and  user 
satisfaction. In March 2024, Sweden launched the new data portal, featuring a range of significant 
improvements  designed to streamline access and boost usability.  Key enhancements  include the 
following. 

•  User-friendly  design  and  structure.  A  cohesive  and  consistent  design  refresh  was 
implemented, making navigation intuitive and visually clear, thereby enhancing the overall 
user experience. 

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Highlight from Sweden – improving the data portal through user experience 

•  Support and tools section. This section offers users advanced filtering options, helping them 
to  locate  data  more  efficiently  and  customise  search  criteria  according  to  their  specific 
needs. 

•  Good examples showcase. Users can now apply to share their successful data reuse cases, 
highlighting practical examples of data-driven solutions and fostering a sense of community 
and knowledge exchange. 

•  Data  collaboration  hub.  This  dedicated  area  showcases  national 

initiatives  and 
collaborations  aimed  at  positioning  data  as  a  strategic  resource,  encouraging  collective 
efforts and highlighting innovative data reuse. 

•  Educational  resources  page.  An  easily  accessible  resource  section  provides  users  with 
educational materials and guides related to data, promoting data literacy and supporting 
users in developing their data-related skills. 
‘Why  share  data?’  section.  This  page  outlines  the  benefits  of  data  sharing,  relevant 
regulations and best practices, providing a comprehensive  view of how  sharing data can 
drive innovation and transparency. 

• 

•  Results and follow-ups section. This page displays key metrics, including metadata quality 
assessments across various data catalogues, reinforcing the platform’s commitment to data 
quality and continuous improvement. 

Through this user-focused redevelopment, Sweden’s data portal not only enhances accessibility but 
also supports users in exploring, using and contributing to the nation’s data resources, ultimately 
advancing the strategic use of data as a public asset. 

Most popular data domains 

Analytics  on  what  users  prefer  can  improve  the  usability  and  utility  of  the  portal.  This  involves 
monitoring what keywords are used to search for data and content on the portal, as well as monitoring 
the most and least consulted pages. Similarly, national portals take measures to optimise the search 
and  discoverability  of  content.  Table 28  presents  an  overview  of  how  countries  responded  to  the 
questions on this topic. 

Table 28: Countries’ responses to questions on the most popular data domains 

Do you monitor what keywords are used to 
search for data and content on the portal? 

Do you take measures to optimise the 
search and discoverability of content? 

EU-27 

EFTA 

24 Member States (88 %) report that they 
monitor the keywords used in the portal 
and the most and least consulted pages. 

All participating EFTA countries, except 
Iceland, report that they monitor the 
keywords used in the portal and the most 
and least consulted pages. 

All Member States (100 %) report 
optimising the discoverability of datasets. 
This number has decreased by one 
country, Croatia, since 2023. 

All participating EFTA countries report 
that they implement measures to 
improve the discoverability of content. 

Candidate  Serbia and Ukraine report that they 

monitor the keywords used in the portal 
and the most and least consulted pages. 

Albania, Serbia and Ukraine report that 
they implement measures to improve the 
discoverability of content. 

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Do you monitor what keywords are used to 
search for data and content on the portal? 

Do you take measures to optimise the 
search and discoverability of content? 

This number has decreased by one 
country, Albania, since 2023. 

(Questions PT28 and PT30) 

Monitoring  the  keywords  used  in  data  portal  searches  can  offer  insights  into  user  interests  and 
navigation  patterns.  In  Austria,  this  monitoring  is  enhanced  by  artificial  intelligence  models,  which 
provide  data  for  a  comprehensive  dashboard.  France  takes  a  similar  approach,  tracking  the  most 
viewed pages and popular new content. A daily top 10 list is shared within the team to identify trending 
topics that may warrant further development, such as writing dedicated articles or highlighting specific 
datasets. This also helps to determine when data exploration is needed. For example, certain datasets 
are popular because  users seek  information rather than raw data, guiding decisions on whether to 
redirect users to different datasets or create tailored data exploration tools. 

To improve searches and content discoverability, Finland has upgraded its portal’s search engine, with 
better  support  for  both  Finnish  and  Swedish  users.  Additionally,  the  national  DCAT-AP  extension 
requires a set of mandatory, optional and recommended attributes, further enhancing data findability. 

Application programming interfaces 

APIs  allow  reusers  to  programmatically  access  metadata  and  thereby  to  automatically  execute 
searches and process data. National portals can run analytics on this API usage in the same way as they 
do for regular portal traffic. Moreover, metadata on the portal can be made available in clear, plain 
language  to  enable  both  humans  and  machines  to  read  and  understand  it.  Table 29  presents  an 
overview of how countries responded to the questions on this topic. 

Table 29: Countries’ responses to questions on APIs 

Do you run analytics on API usage? 

EU-27 

17 Member States (63 %) report 
analysing API usage. 

EFTA 

Iceland reports analysing API usage. 

Is the metadata on your portal available in 
clear, plain language to enable both 
humans and machines to read and 
understand it? 

All Member States (100 %) have metadata 
that is written in language that is 
understandable to humans and machines, 
like in 2023. 

All participating EFTA countries report 
providing human-readable metadata. 

Candidate  Albania, Serbia and Ukraine report 
analysing API usage. 

Albania, Serbia and Ukraine report 
providing human-readable metadata. 

(Questions PT24 and PT31) 

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APIs allow different software systems to communicate and exchange data. For instance, a government 
portal might have APIs that let external developers access public data or integrate services. Analytics 
on API usage involve collecting data on various aspects of API usage, such as how often the API is being 
accessed, which services or systems are using the API, the performance of the API (response time and 
error rates) and patterns in API calls over time (e.g. peak usage hours). In Cyprus, Matomo is employed 
to analyse API usage, providing insights into the popularity of specific APIs, such as the page titles and 
uniform resource locators (URLs) being accessed. Additionally, it gathers detailed information about 
reusers, including their internet protocol (IP) address; the request date, time and location; and device 
specifics like operating system, model, browser and screen resolution. The report also captures the 
unique visitor identification, along with the timing and frequency of all visits made by each user. 

The  majority  of  countries  provide  metadata  in  forms  for  both  humans  and  machines  to  read  and 
understand, like in Germany, where the metadata is human-readable and is accompanied by a link to 
a machine-readable resource description framework (RDF) file. 

5.4. Data provision 

This  indicator  measures  the  level  of  contributions  from  data  providers  to  national  portals  and  the 
initiatives implemented to encourage their participation, including the connections between national 
and regional/local portals. It also explores how open data portals help users  find citizen-generated 
data and data that cannot be publicly shared. Finally, it evaluates how effectively the national portal’s 
infrastructure allows access to real-time and dynamic data. 

Official data providers 

Public sector bodies are the primary suppliers of open data. Therefore, it is interesting to assess to 
what degree public sector data providers contribute data to the national portal. In addition to open 
data, national portals can also show users if data exists that cannot be made available as open data. A 
feature like this can help reduce  freedom-of-information requests for data that cannot be opened. 
Table 30 presents an overview of how countries responded to the questions on this topic. 

Table 30: Countries’ responses to questions on official data providers 

EU-27 

EFTA 

To what degree do public sector data 
providers contribute data to the portal? 

Does the national portal allow users to see if 
data exists that cannot be made available as 
open data? 

22 Member States (81 %) report that all 
or the majority of public sector 
providers supply data to the national 
portal. 

19 Member States (70 %) report that they 
show users if data exists that cannot be 
made available as open data. Germany, 
Croatia and Latvia newly report this. 

Norway and Switzerland assess that 
approximately half of data providers 
supply data to the portal. Iceland 
reports that only public sector bodies 
supply data to the national portal. 

All the participating EFTA countries report 
that they show users if data exists that 
cannot be made available as open data. 

Candidate  Ukraine reports that all public sector 
providers supply data to the national 
portal. Albania and Serbia assess that 

None of the participating candidate 
countries report showing users if data exists 
that cannot be made available as open data. 

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To what degree do public sector data 
providers contribute data to the portal? 

Does the national portal allow users to see if 
data exists that cannot be made available as 
open data? 

approximately half of data providers 
supply data to the portal. 

(Questions PT32 and PT40) 

In general, official data providers make data available on the central portal. This is achieved through 
ongoing efforts by national portal teams. For example, in the Netherlands, public sector data providers 
are generally proactive  in publishing their datasets on the national data portal. Most organisations 
automatically  synchronise  their  internal  catalogues  with  the  portal.  However,  ongoing  relationship 
management  is  essential to  ensure  data owners  consistently  upload their  datasets.  In  Czechia,  the 
legislation mandates that all open data must be registered in the national open data portal. As a result, 
the portal includes datasets from central, regional and local providers, who directly register their data. 
After initial registration, the portal can automatically harvest updates and new information. 

Some  countries  also  publish  lists  of  data that exist  but  are  not  available as open  data.  In  Italy,  for 
example, the national data portal features a specific section for public administration databases that 
are not available as open data. Additionally, the portal is linked to the catalogue for spatial data, which 
contains both open and restricted datasets. For open data, the corresponding metadata is also made 
accessible via the dati.gov.it portal, using the DCAT-AP standard for geographical metadata. 

Non-official data providers 

Some countries also allow non-official providers to contribute data to the portal, such as community-
sourced / citizen-generated data. Table 31 presents an overview of how countries responded to the 
question on this topic. 

Table 31: Countries’ responses to the question on non-official data providers 

EU-27 

EFTA 

Does the national portal provide a way for non-official data to be published? 

17 Member States (62 %) report allowing the publication of non-official data on their 
portal. Czechia, Germany, Ireland, Croatia, Slovakia and Sweden newly report this. 

None of the EFTA countries report allowing the publication of data from non-official 
providers on the national portal. 

Candidate 

Serbia and Ukraine report allowing the publication of non-official data on their portal. 
This number has increased by one country, Ukraine, since 2023. 

(Question PT39)  

Often, national portals publish non-official datasets in the same catalogue as official datasets and use 
tags to indicate when datasets stem from non-official sources. For example, in Croatia, any user can 
apply to publish data through the national portal by submitting a designated form. Similarly, Estonia 
has no distinction between official and non-official data; instead, the focus is on the organisation or 

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individual publishing the data. In France, publishers are identified with a specific label to distinguish 
official from non-official sources. 

Assistance for data providers 

By  identifying  data  providers  who  have  not  yet  published  data  on  the  national  portal  and  taking 
concrete  actions  to  assist  them,  national  portals  can  increase  the  supply  of  open  data.  Table 32 
presents an overview of how countries responded to the questions on this topic. 

Table 32: Countries’ responses to questions on assistance for data providers 

Do you identify the data providers that 
are not yet publishing data on the 
national portal? 

Were there concrete actions taken to assist 
these data providers with their publication 
process? 

EU-27 

EFTA 

All Member States (100 %) report that 
they identify the data providers not yet 
publishing data on the national portal. 

26 Member States (96 %), all except 
Lithuania, report that they take concrete 
actions to assist these data providers with 
their publication process. 

All participating EFTA countries report 
that they identify the data providers not 
yet publishing data on the national 
portal. 

All participating EFTA countries report that 
they take concrete actions to assist these 
data providers with their publication 
process. 

Candidate  All candidate countries, except Bosnia 

and Herzegovina, report that they 
identify the data providers not yet 
publishing data on the national portal. 

All participating candidate countries, 
except Bosnia and Herzegovina, report 
that they take concrete actions to assist 
these data providers with their publication 
process. 

(Questions PT33 and PT34) 

Countries support data providers in publishing datasets on national portals through various methods, 
including  by  providing  general  guidelines,  online  tutorials  and  frequently-asked-questions  pages  or 
organising ad hoc meetings. In Portugal, for example, tutorials on registration, publication and reuse 
are available, and organisations receive direct assistance for more complex inquiries. In Albania, new 
publishers can email their data for manual insertion by the open data team, which handles publication 
on the portal. Technical support is provided for automatic publication through electronic systems. 

Regional and local data sources 

National  portals  primarily focus on  data  provided  by  national-level  sources.  However,  regional and 
local datasets can offer detailed, context-specific insights on a range of subjects. Making these regional 
and local datasets accessible through national portals can promote their discovery and broader reuse. 
Table 33 presents an overview of how countries responded to the questions on this topic. 

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Table 33: Countries’ responses to questions on regional and local datasets 

Besides the national open 
data portal, are there 
other regional and local 
portals? 

Are regional and local 
portals and their data 
sources discoverable via the 
national portal? 

To what degree are 
regional and local sources 
harvested automatically? 

EU-27 

24 Member States (88 %) 
report that there are 
other regional and local 
portals besides the 
national open data 
portal. 

22 countries (81 %) report 
that regional and local 
sources are discoverable 
via the national portal. 

EFTA 

All participating EFTA 
countries report that 
regional and local portals 
exist in their country. 
Iceland newly reports 
this. 

All participating EFTA 
countries report that 
regional and local sources 
are discoverable via the 
national portal. Iceland 
newly reports this. 

Candidate  All participating 

candidate countries 
report that regional and 
local portals exist in their 
country. 

Serbia and Ukraine report 
that regional and local 
sources are discoverable 
via the national portal. 

17 Member States (63 %) 
report that all or the 
majority of regional and 
local datasets are 
harvested automatically. 5 
Member States (19 %) 
indicated that this question 
was not applicable, mainly 
because there are no 
regional bodies given the 
size of their countries. 

Norway reports that all 
regional and local datasets 
are harvested 
automatically. For 
Switzerland, this is true of 
the majority of datasets. 
Iceland reports that none 
of the regional and local 
datasets are automatically 
harvested. 

Ukraine reports that all 
regional and local datasets 
are harvested 
automatically. For Sebia, 
this is true of the majority 
of datasets. 

(Questions PT35, PT36 and PT37) 

A national open data portal can play a crucial role in promoting open data across the country. These 
portals often serve as a comprehensive one-stop shop, and most countries make regional and local 
data  discoverable  through  their  national  portals.  For  example,  in  Germany,  datasets  from  various 
regions are accessible through the main portal and can be easily filtered for specific locations. Some 
countries, such as Luxembourg and Malta, do not have regional data portals, mainly due to the smaller 
size of the country and the fact that there are no regions. 

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In  many  cases,  datasets  from  smaller  regional  and  local  portals  are  automatically  harvested  after 
agreements are made with local authorities. For example, in Spain in 2024: 

•  20 regional initiatives contributed 42 % of the total data in the national catalogue, with 99 % 

of these datasets being automatically harvested; 

•  102 local initiatives contributed 17 % of the total data, also with 99 % of the datasets harvested 

automatically. 

However, in some cases, like in Denmark, automatic harvesting is not implemented due to time and 
resource  constraints  on  both  sides,  making  it  difficult  to  align  data  models  and  agree  on  certain 
technical specifications. 

Access to real-time and dynamic data 

Dynamic data is information that evolves over time and is updated periodically as fresh data points are 
collected,  like  weekly  reports  on  unemployment  figures.  In  contrast,  real-time  data  involves 
continuous  updates  at  short  intervals,  with  examples  including  air  quality  readings,  live  weather 
reports and transportation or traffic details. This type of data plays a crucial role in various applications, 
such  as  traffic-optimised  navigation  systems or economic  forecasting models.  Table 34  presents  an 
overview of how countries responded to the question on this topic. 

Table 34: Countries’ responses to the question on real-time and dynamic data 

Does the national portal include datasets of real-time or dynamic data? 

EU-27 

24 Member States (89 %) report that they offer real-time or dynamic data on their 
portal. Malta newly reports this. 

EFTA 

All participating EFTA countries offer real-time or dynamic data on their portal. 

Candidate 

All participating candidate countries, except Bosnia and Herzegovina, report offering 
real-time or dynamic data on their portal. 

(Question PT38)  

Most countries have real-time or dynamic data on their national portals. In France, for example, one 
of the most successful applications of real-time data has been in the transportation sector. The portal 
transport.data.gouv.fr showcases reuse examples based on real-time transport data. The task force 
behind  the  portal  has  undertaken  substantial  efforts  to  promote  real-time  data  use,  offering 
documentation on standardisation, maintaining an inventory of real-time data that still needs to be 
standardised and fostering dialogue with stakeholders to advance adoption. 

Similarly, in Lithuania, real-time road traffic and weather conditions data is accessible through the local 
infrastructure portal eismoinfo.lt. This data is searchable and downloadable from the national data 
portal’s  metadata  catalogue  at  data.gov.lt,  which  provides  a  source  URL  for  traffic  intensity 
information.  The  data  is  dynamically  updated  as  it  is  registered  in  the  primary  database  and  is 
presented to citizens through a user-friendly application, enhancing accessibility and engagement. 

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5.5. Portal sustainability 

This  indicator  investigates  the  strategies  and  procedures  established  to  maintain  the  long-term 
sustainability of national portals. It encompasses initiatives aimed at increasing the visibility of these 
portals,  efforts  to  gauge  user  satisfaction  and  incorporate  their  feedback,  and  mechanisms  for 
monitoring and enhancing the performance of the national portal. 

Strategy and visibility 

A key step in ensuring the long-term sustainability of national portals is developing a strategy or action 
plan that outlines the activities and mechanisms needed for continued operation. These plans often 
focus on securing funding, maintaining key personnel, fostering public engagement and ensuring that 
the  portal  meets  the  needs  of  its  core  audience.  Table 35  presents  an  overview  of  how  countries 
responded to the questions on this topic. 

Table 35: Countries’ responses to questions on strategy and visibility 

Does the national portal have a strategy 
to ensure its sustainability? 

Is your national portal active on social 
media? 

EU-27 

22 Member States (81 %) report that 
the national portal has a strategy to 
ensure its sustainability. 

EFTA 

Norway and Switzerland report that 
the national portal has a strategy to 
ensure its sustainability. 

Candidate  All participating candidate countries, 

except Bosnia and Herzegovina, report 
having a strategy to ensure the portal’s 
sustainability. Albania newly reports 
this. 

21 Member States (78 %) are active on 
social media to increase the visibility of the 
portal. Germany and the Netherlands did 
not report doing this, a change from the 
previous year. 

All participating EFTA countries are active 
on social media. 

All participating candidate countries, 
except Bosnia and Herzegovina, report 
being active on social media. 

(Questions PT41 and PT42) 

In  many  countries,  the  national  portal  serves  as  a  cornerstone  of  the  national  open  data  policy  or 
strategy. In Ukraine, for example, the Ministry of Digital Transformation has taken steps to ensure the 
portal’s sustainability by preparing a technical task and a technical and economic justification for its 
modernisation. Key documents include the results of the portal audit, technical task and technical and 
economic  justification.  Additionally,  Ukraine’s  draft  Strategy  for  the  development  of  the  open  data 
sphere for 2025–2027 sets out an operational action plan for each strategic goal. It outlines specific 
measures,  expected results, deadlines  and responsible actors. One of the  key strategic goals is the 
enhancement of the accessibility and capabilities of the unified state web portal of open data. 

Furthermore, the majority of countries are available on social media. X, Facebook and LinkedIn are the 
most used social media platforms. These channels are used to boost the public’s awareness of open 
data and directly interact with users and data enthusiasts. 

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Availability of documents to the public 

National  portals  can  make  their  portal’s  source  code  and  relevant  documentation  and  artefacts 
available to the public (e.g. on platforms such as GitHub or GitLab) to foster transparency and promote 
open-source initiatives. Table 36 presents an overview of how countries responded to the question on 
this topic. 

Table 36: Countries’ responses to the question on the public availability of documents 

Are the portal’s source code and relevant documentation and artefacts made available 
to the public? 

Like in 2023, 25 Member States (93 %) report publicly sharing the portal’s source code 
and relevant documentation. 

All participating EFTA countries report publicly sharing the portal’s source code and 
relevant documentation. 

EU-27 

EFTA 

Candidate 

Bosnia and Herzegovina and Serbia report publicly sharing the portal’s source code 
and relevant documentation. 

(Questions PT43)  

The great majority of the countries interviewed report that they provide such documents on GitHub. 
For  instance,  Belgium  makes  them  available  for  back-end  tools  on  GitHub,  while  the  web  content 
management system front end relies on the Drupal distribution OpenFed. 

Monitoring performance 

To track progress and plan improvements, national portals can assess various characteristics of the 
data  published  on  their  portals, such  as  the  number  of  datasets  available,  their  distribution  across 
categories, the presence of real-time data and how these aspects have evolved over time. Additionally, 
performance and usage  reports can provide valuable evidence to support continued initiatives  and 
justify investments. Table 37 presents an overview of how countries responded to the questions on 
this topic. 

Table 37: Countries’ responses to questions on monitoring performance 

EU-27 

Do you monitor the characteristics of 
the data published on the portal, such 
as the distribution across categories, 
static versus real-time data, and how 
these change over time? 

25 Member States (93 %) report that 
they monitor the characteristics of the 
data published on the portal. Denmark, 
Latvia and Slovakia newly report this, 
and Germany no longer reports doing 
this in 2024, a change from the previous 
year. 

Does this monitoring enable the portal 
team and/or data providers to take action 
to improve their performance on the 
national portal? 

25 Member States (93 %) report that this 
monitoring enables the portal team and/or 
data providers to take action to improve 
their performance on the national portal. 

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Do you monitor the characteristics of 
the data published on the portal, such 
as the distribution across categories, 
static versus real-time data, and how 
these change over time? 

Does this monitoring enable the portal 
team and/or data providers to take action 
to improve their performance on the 
national portal? 

EFTA 

Norway reports that it monitors the 
characteristics of the data published on 
the portal. 

Candidate  All participating candidate countries, 

except Bosnia and Herzegovina, report 
that they monitor the characteristics of 
the data published on the portal. 
Albania newly reports this. 

Norway responded this monitoring 
enables the portal team to take action to 
improve their performance on the national 
portal. 

All candidate countries, except Bosnia and 
Herzegovina, report that this monitoring 
enables the portal team and/or data 
providers to take action to improve their 
performance on the national portal. 

(Questions PT44 and PT45) 

The majority of countries  have  implemented  a monitoring  framework  to  continuously  improve  the 
portal. This particularly involves monitoring metadata, such as analysing both summary and specific 
statistics  on  metadata  to  track  any  missing  DCAT-AP  attributes  across  datasets.  In  Sweden,  for 
example,  the  statistics  at  a  glance  section  includes  information  on  the  number  of  organisations 
publishing data, those with the most published datasets and the five most common data categories. 

Many countries also analyse performance metrics to further enhance portal usability. In  Serbia, for 
example, monitoring covers aspects such as data formats, quality, description and update frequency. 
This  information  is  shared  with  data  providers,  along  with  recommendations  for  improvement.  In 
Czechia, dashboards tracking the quality of data and metadata are accessible to the national team and 
data  providers.  The  team  monitors  these  dashboards  regularly,  addresses  irregularities  with 
providers – especially members of the Open Data Working Group – and encourages improvements. 
Performance results from major providers are also published annually in the Annual Report of the State 
of Open Data in an easy-to-understand format. 

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Highlight from Lithuania – monitoring dashboard 
Lithuania provides an example of how the characteristics of the data published on the portal, such 
as the distribution across categories and static versus real-time data, can be monitored over time 
(Figure 12). 

Figure 12: Lithuania’s open data monitoring dashboard 

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5.6. Pilot indicator: automated tests of portal performance 

Pilot indicator – automated tests 

In  addition  to  gathering  qualitative  information  on  portals,  there  are  technical  and  quantitative 
methods to evaluate portals on objective metrics. Such tests can complement the insights derived 
from the questionnaire and extend the scope of the ODM report. As a pilot, four indicators (mobile 
friendliness, page speed, security and web accessibility) were measured for this year’s report but 
did not contribute to countries’ maturity score. These tests were conducted on the portal URLs listed 
in Table 18. 

Mobile friendliness assesses how well a website adapts to mobile devices, ensuring a seamless user 
experience  for visitors on smartphones and tablets. This indicator is operationalised through the 
Bing mobile friendliness tool. In summary: 

•  94 % of all portals are mobile friendly; 
•  100 % of all EU portals are mobile friendly; 
•  portals from Albania and Iceland were not evaluated as mobile friendly by this automated 

tool. 

Page  speed  assesses  a  selection  of  speed  and  performance  standards  from  Google’s  PageSpeed 
Insights. The results can be summarised as follows. 

•  Of all portals, 85 % pass the time to interactive test. This test measures how long it takes a 
page to become fully interactive. Sites are considered fully interactive when (a) the page 
displays useful content, (b) event handlers are registered for the most visible page elements 
and (c) the page responds to user interactions within 50 milliseconds. 

•  Of all portals, 82 % pass the first contentful paint test. This test measures the time from 
when the user first navigated to the page to when any part of the page’s content is rendered 
on the screen. Sites should strive to have a first contentful paint of 1.8 seconds or less. 
•  Of all portals, 52 % pass the largest contentful paint test. This test reports the render time 
of the largest image, text block, or video visible in the viewport, relative to when the user 
first navigated to the page. To provide a good user experience, sites should strive to have a 
largest contentful paint of 2.5 seconds or less. 

•  Of all portals, 33 %  pass the  cumulative layout shift  test. This test measures the  biggest 
group  of  unexpected  layout  changes  that  happen  on  a  web  page  while  it  is  loading.  To 
provide a good user experience, sites should strive to have a cumulative layout shift score 
of 0.1 or less. 

Security assesses several complementary metrics related to basic cybersecurity hygiene using the 
publicly  available  security  testing  tool  by  the  Dutch  national  government  called  internet.nl.  The 
results can be summarised as follows. 

•  Of all portals, 15 % pass the modern address (IPv6) test. This test evaluates if the website is 
reachable  for  visitors  using  a  modern  internet  address  (IPv6),  making  it  fully  part  of  the 
modern internet. 

•  Of  all  portals,  27 %  pass  the  domain  name  system  security  extensions  test.  This  test 
evaluates if the website’s domain is signed with a valid signature, which protects against 
manipulated translation from the domain into rogue internet addresses. 

•  Of all portals, 12 %  pass the  secure connection  test. This test evaluates if information in 
transit  between  the  website  and  its  visitors  is  protected  against  eavesdropping  and 
tampering. 

•  Of all portals, 3 % pass all three tests. 

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Web  accessibility  assesses  the  accessibility  status  of  websites  (including  for  individuals  with 
disabilities)  using  the  open-source  Axe-core  tool.  The  accessibility  criteria  are based  on  the  web 
content accessibility guidelines (WCAGs). The results can be summarised as follows. 

•  Of all portals, 53 % pass the alternative text (WCAG 1.1.1) test. This test evaluates 
whether the website offers text alternatives for non-text content, enabling it to be 
transformed into formats like large print, braille, speech, symbols or simplified language to 
meet diverse user needs. 

•  Of all portals, 47 % pass the colour contrast (WCAG 1.4.3) test. This test evaluates if the 
visual presentation of text and images on the website has a contrast ratio of at least 4.5:1. 
Exceptions  include  cases  of  large  text,  text  or  images  part  of  an  inactive  user  interface 
component, and text that is part of a logo or brand name. 

•  Of all portals, 75 % pass the page/document title (WCAG 2.4.2) test. This test evaluates if 

the website has titles that describe the topic or purpose. 

•  Of all portals, 50 % pass the link name (WCAG 2.4.4) test. This test evaluates the clarity and 

accessibility of links on a website. 

•  Of all portals, 69 % pass the language attribute (WCAG 3.1.1) test. This test evaluates if the 
primary language of each web page is specified in a way that can be identified by software, 
such as screen readers and search engines. 

•  Of all portals, 69 % pass the valid language code (WCAG 3.1.2) test. This test evaluates if 
the  language  of  each  passage  or  phrase  in  the  website’s  content  can  be  identified  and 
defined  by  software,  allowing  assistive  technologies  (e.g.  screen  readers)  to  accurately 
convey content in the appropriate language. 

•  Of all portals, 50 % pass the name, role, value (WCAG 4.1.2) test. This test evaluates the 
accessibility and compatibility of user interface components of the website with assistive 
technologies. 

•  Of all portals, 22 % pass all seven of the above tests. 

•  Of all EU portals, 27 % pass all seven of the above tests. 

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Chapter 6: Open data quality 

The quality of the data refers to the overall state of the dataset. Preparing high-quality data includes 
dealing with missing values and other inaccurate elements, harmonising data structures and making 
the data available in accessible formats. Data quality also depends on the quality of its deployment on 
national portals, which can be assessed by looking at the use of aspects such as open data licences, 
machine-readable  data  formats,  unique  resource  identifiers  (a  character  sequence  that  identifies  a 
dataset) and a linked data approach (a set of design principles for relating datasets to one another). 

In addition to the data itself, high-quality data is accompanied by good descriptions. Such descriptive 
data is called metadata and gives information about other data, such as author, date and keywords. 
Specifications  such  as  the  Data  Catalog  Vocabulary –  Application  Profile  (DCAT-AP) –  which  was 
designed to describe public sector datasets in Europe and is, therefore, the reference specification in 
the  open  data  maturity  (ODM)  assessment  methodology –  define  the  structure  and  content  of 
metadata descriptions and aim to make public sector data more easily searchable across borders and 
sectors. 

Data that is high quality has greater value. This value derives from characteristics such as being easier 
for  reusers  to  analyse  and  visualise.  High-quality  metadata  similarly  aids  reuse  by  making  datasets 
more discoverable, since search engines can better match the data’s description with a user’s search 
terms. 

The quality dimension of the ODM assessment encourages national portals to publish datasets with 
high-quality data and metadata. The ODM methodology emphasises metadata quality, since national 
portals aim to make datasets discoverable and harvest metadata. The methodology also investigates 
whether  portal managers have  materials  and  processes  to  assist  and  incentivise  data  publishers  to 
provide high-quality data. 

In  brief,  the  quality  dimension  assesses  the  measures  adopted  by  portal  managers  to  ensure  the 
systematic and timely harvesting of metadata and the monitoring mechanisms in place to ensure the 
publication  of  metadata  that  is  compliant  with  the  DCAT-AP  metadata  standard  and  several 
deployment quality requirements. Table 38 summarises the key elements of the quality dimension.

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Table 38: Indicators of the quality dimension 

Indicator 

Metadata currency 
and completeness 

Key elements 

A  systematic  approach  is  in  place  to  ensure  that  metadata  is  up  to  date. 
Programmes  that  harvest  metadata  automatically  are  used  to  ensure  that 
changes at the source are reflected with minimal delay on the national portal. 
The  portal  provides  access  to  a  vast  range  of  historical  and  contemporary 
data.  Preparations  are  under  way  to  ensure  that  high-value  data  is 
interoperable with high-value datasets (HVDs) from other countries. 

Monitoring and 
measures 

Mechanisms are in place to monitor metadata quality on the national portal 
and compliance with licensing standards. Measures are in place to assist data 
providers in publishing high-quality metadata and choosing the right type of 
licence for their data. 

DCAT-AP 
compliance 

Compliance with the DCAT-AP standard regarding mandatory, recommended 
and optional classes is monitored. Guidelines and learning materials help data 
providers in ensuring compliance with DCAT-AP. 

Deployment 
quality and linked 
data 

A model is used to assess the quality of data and metadata deployment. The 
percentage of published open data that complies with specific deployment 
quality requirements, including having links to other data sources, is known, 
and improvements in terms of deployment are monitored. 

This  chapter  will  first  present  overall  performance  on  the  policy  dimension  and  then  provide  a 
summary of the results and best practices for each indicator. 

Contents 

6.1. Overall performance on the quality dimension ....................................................................... 86 

6.2. Metadata currency and completeness ..................................................................................... 89 

Currency of metadata .................................................................................................................... 89 

Completeness of metadata ........................................................................................................... 92 

Interoperability of high-value datasets ......................................................................................... 93 

6.3. Monitoring and measures ......................................................................................................... 94 

Monitoring the quality of metadata on portals ............................................................................ 94 

Setting metadata standards and licensing requirements ............................................................. 97 

Support activities for data providers ............................................................................................. 98 

6.4. DCAT-AP compliance ............................................................................................................... 101 

Creating a framework for DCAT-AP compliance ......................................................................... 101 

Compliance with the DCAT-AP specifications ............................................................................. 102 

6.5. Deployment quality and linked data ...................................................................................... 104 

Use of models for deployment quality ........................................................................................ 104 

Activities for data providers to ensure high-quality data............................................................ 105 

Deployment quality ..................................................................................................................... 106 

6.6. Pilot indicator: automated tests of metadata quality ............................................................ 107 

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6.1. Overall performance on the quality dimension 
The quality dimension is the least mature dimension of the ODM assessment according to the EU-27 
average in 2024 (Figure 13). The average maturity of EU Member States in the quality dimension is 
79 %. This is a 3 percentage point (pp) decrease from 2023, primarily driven by a 6 pp decrease in the 
‘monitoring and measures’ indicator and a 4 pp decrease in the ‘DCAT-AP compliance’ indicator. These 
decreases may be attributed to the introduction of 11 new questions or criteria related to the quality 
dimension in this year’s questionnaire, which introduced a higher set of requirements that were not 
previously measured.  In  addition,  several  countries reported  lower  metadata quality  scores  on the 
same questions asked last year. 

Figure 13: The EU-27 average score on the quality dimension decreased year-on-year but is still more 
mature than in years before 2023 

In  terms  of  individual  country  performance,  France  (100 %)  is  the  most  mature  in  the  quality 
dimension, achieving full points in all four of the underlying indicators (Figure 14). Latvia (95 %) and 
Ukraine  (94 %)  follow  closely,  both  demonstrating  full  maturity  (100 %)  in  the  ‘monitoring  and 

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measures’ indicator. Ukraine also demonstrates full maturity in the ‘DCAT-AP compliance’ indicator. In 
addition, Denmark (92 %) and Poland (90 %) are also notable performers, both achieving above 90 % 
maturity in this dimension. Demark is the only country besides France to achieve 100 % maturity on 
the ‘deployment quality and linked data’ indicator, while Poland scores full points on the ‘monitoring 
and measures’ and the ‘DCAT-AP compliance’ indicators. Overall, 15 Member States score above the 
EU average of 79 %. 

Highlight from France – automated metadata harvesting 

One of the key practices highlighted in this year’s report is the use of fully automated harvesting 
systems for metadata, whereby metadata is updated from the source rather than edited manually. 

France ensures that 100 % of the essential metadata on its national portal, data.gouv.fr, is obtained 
automatically from the  source  through a comprehensive  and robust  system. The platform offers 
several methods for data publication: 

•  direct publication, 
•  publication via application programming interfaces (APIs), 
•  publication through harvesting. 

Data.gouv.fr supports the harvesting of various metadata formats, including DCAT, Comprehensive 
Knowledge Archive Network (CKAN) and GeoNetwork. Data providers can set up a harvester, which 
the data.gouv.fr team must then validate to ensure accuracy and compatibility. This process involves 
establishing the mapping of fields for essential metadata while retaining additional properties for 
traceability. 

Once harvesters are properly configured, data.gouv.fr can retrieve 100 % of the essential metadata 
for  their  model.  Currently,  harvested  data  accounts  for  approximately  50 %  of  the  data.gouv.fr 
catalogue, highlighting the effectiveness and efficiency of this automated system in maintaining up-
to-date and accurate metadata on the national portal. Read more about this trend in Section 6.2 

Serbia  (+ 17 pp),  Latvia  (+ 10 pp)  and  Belgium  (+ 5 pp)  demonstrated  the  greatest  year-on-year 
improvement in the quality dimension. Serbia’s improvement can be attributed to substantial progress 
on  the  ‘DCAT-AP  compliance’  indicator  (+ 50 pp).  Serbia  now  reports  that  it  investigates  the  most 
common causes of non-compliance with DCAT-AP standards. Additionally, 90 % of Serbia’s datasets 
now include metadata referencing a web page where the data can be accessed. Serbia also achieved 
a 6 pp increase in the ‘deployment quality and linked data’ indicator. This increase can be attributed 
to the recent introduction of a model for assessing the quality of data deployment in the country. 

Highlight from Serbia – discussion modules to improve metadata quality 

One of the trends highlighted in this year’s report is the use of data quality assessment techniques 
that  either  combine  or  go  beyond  the  widely  used  5-star  open  data  model  and  the  findable, 
accessible, interoperable and reusable (FAIR) principles. 

In Serbia, each dataset comes with a discussion module through which users can share feedback 
regarding datasets. This feature allows users to share positive and negative opinions, report 
anomalies and directly suggest improvements to the dataset provider. Serbia uses this discussion 
module to facilitate more in-depth and actionable feedback, helping to improve the quality of data 
over time. This enables a rich dialogue between users and data providers, promoting continuous 
data quality improvement. See an example of the discussion module in action with the Address 
Register, a fundamental public register containing data on streets (determined by local 
government decisions) and house numbers across the Republic of Serbia. Read more about this 
trend in Section 6.5. 

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Figure 14: The scores of the majority of countries decreased on the quality dimension in 2024. (YoY: 
year-on-year). 

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Latvia’s increase in its score on the quality dimension can be attributed to its 13 pp increase in the 
‘DCAT-AP  compliance’  indicator.  Additionally,  Latvia  saw  a  19 pp  increase  in  the  monitoring  and 
measures  indicator,  which  may  be  attributed  to  its  recently  starting  to  publish  information  on  the 
quality of its metadata on its open data portal. Belgium’s increase in its score on the quality dimension 
can  be  attributed  to  its  22 pp  increase  in  the  ‘metadata  currency  and  completeness’  indicator  and 
14 pp increase in the ‘deployment quality and linked data’ indicator. 

Highlight from Belgium – enhancing metadata through automated pipelines 

One  of  the  key  practices  highlighted  in  this  year’s  report  is  the  use  of  an  automatic  metadata 
harvesting process that is operated under a centralised model, whereby multiple sub portals are 
interconnected under a single catalogue. 

In  Belgium,  using  command  line  tools,  metadata  is  automatically  collected  and  then  enhanced 
through  SPARQL  Protocol  and  RDF  Query  Language  (SPARQL)  queries  and  Simple  Knowledge 
Organisation System (SKOS) data, which helps improve the structure and quality of the metadata. 
Once enhanced, the metadata is pushed on GitHub (a web-based platform for version control and 
collaboration), where different teams can access it. Finally, data.europa.eu collects the enhanced 
metadata  from  GitHub,  ensuring  that  high-quality,  standardised  metadata  is  available  at  the 
European level. This workflow supports both automation and the enhancement of metadata quality 
across various systems. 

Read more about this trend in Section 6.2. 

6.2. Metadata currency and completeness 
This  indicator  assesses  the  extent  to  which  countries  systematically  ensure  that  their  data  and 
metadata are up to date. The indicator also investigates automatic harvesting processes, which ensure 
that changes at the data source are reflected with as little delay as possible on the portal where the 
dataset is made discoverable. Furthermore, the completeness of data that has a time component and 
preparations  to  ensure  that  HVDs  are  interoperable  with  other  datasets  on  the  portal  are  also 
evaluated by this indicator. 

Currency of metadata 

Metadata  plays  a crucial  role  in  enhancing  the  usability  and  reliability  of open data,  and  its  timely 
update is essential for maintaining data relevance and accuracy. A predefined approach to ensuring 
that  metadata  remains  up  to  date  involves  implementing  systematic  processes  and  mechanisms 
tailored to the specific characteristics and update frequency of different datasets. An efficient method 
is automatic metadata sourcing, which is when metadata is generated and updated directly from the 
data source without manual intervention. By adopting these practices, organisations can ensure that 
metadata remains accurate, relevant and aligned with the characteristics and requirements of each 
dataset. Table 39 presents an overview of how countries responded to the questions on this topic. 

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Table 39: Countries’ responses to questions on the currency of metadata 

Is there a predefined 
approach to ensure that 
metadata is kept up to 
date? 

What percentage of the 
metadata on the national 
portal is obtained from the 
source automatically rather 
than edited manually? 

EU-27 

26 Member States 
(96 %), all except 
Bulgaria, report having a 
predefined approach to 
ensuring that metadata is 
kept up to date. 

Six Member States (22 %) 
report that 100 % of the 
metadata on their national 
portals is obtained 
automatically from the 
source. Five Member States 
(19 %) indicate that at least 
90 % of their metadata is 
sourced automatically, 
while four Member States 
(15 %) report that at least 
70 % of their metadata is 
sourced automatically. 

What is the average delay 
from when the metadata 
describing a dataset is 
updated at the source to 
when the change is visible 
on the portal? 

19 Member States (70 %) 
report that the average 
delay from when the 
metadata describing a 
dataset is updated at the 
source to when the change 
is visible on the portal is 
less than one day. Five 
Member States (19 %) 
indicate that this delay is 
typically less than one 
week. Croatia and 
Romania note that the 
average delay is up to one 
month, while Greece 
reports that it can extend 
beyond one month. 

EFTA 

All three participating 
EFTA countries report 
having a predefined 
approach to keeping 
metadata up to date. 

Candidate  Albania, Serbia and 

Ukraine report having a 
predefined approach to 
keeping metadata up to 
date. 

Norway and Switzerland 
report that at least 90 % of 
the metadata on their 
national portals is obtained 
automatically from the 
source. Iceland reports that 
this figure is less than 30 % 
of the metadata. 

Norway and Switzerland 
report that the average 
delay in updating 
metadata from the source 
is less than one day. 
Iceland reports that this 
delay can extend beyond 
one month. 

Ukraine reports that at 
least 50 % of the metadata 
on its national portal is 
obtained automatically 
from the source. Serbia 
indicates that this figure is 
at least 30 %, while both 
Bosnia and Herzegovina 
and Albania report that 
less than 30 % is sourced 
automatically. 

Serbia and Ukraine report 
that the average delay in 
updating metadata from 
the source is less than one 
day. Bosnia and 
Herzegovina and Albania 
report that this delay can 
extend beyond one month. 

(Questions Q1, Q2 and Q3) 

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To ensure that metadata is kept up to date, most countries rely on automated harvesting systems, 
whereby  data  is  continuously  updated  from  the  source.  Many countries  harvest  metadata  under a 
centralised  model,  whereby  multiple  sub  portals  are  interconnected  under  a  single  (national) 
catalogue.  This  automated  harvesting  process  comes  in  various  forms.  For  example,  Estonia  and 
Switzerland  report  relying  on  a  daily  job  scheduler,  Slovakia  conducts  nightly  updates  via  the 
LinkedPipes technology, and Luxembourg and Slovenia report utilising daily scripts. Estonia, France, 
Luxembourg,  Portugal  and  Romania  report  using  APIs  to  facilitate  metadata  harvesting.  Finland, 
France, Ireland, Luxembourg, Norway, Spain and Switzerland note that their automated harvesting 
method accommodates different data formats (e.g. comma-separated values (CSV) and geographical 
JavaScript  object  notation  (GeoJSON)  and  types  of  metadata.  In  addition  to  automated  processes, 
some countries (e.g. Denmark, Ireland, Austria and Portugal) also note certain instances that warrant 
manual checks (e.g. for smaller data providers). 

While most countries use time-triggered updates, such as Italy’s weekly harvesting of the federated 
catalogue,  Austria  also  incorporates  event-triggered  updates,  which  are  activated  by  specific 
occurrences, such as legislative changes or significant weather events. 

Several  countries,  such  as  Estonia,  Cyprus,  Latvia  and  Slovenia,  also  mention  that  they  have  legal 
frameworks  and  regulations  that  mandate  the  regular  updating  of  metadata.  In  many  cases, 
designated  open  data  personnel  and  the  open  data  portal  administrators  oversee  the  quality  of 
metadata,  conducting  regular  checks  and  informing data  publishers  of  discrepancies.  On  the  other 
hand, countries such as Greece, Lithuania, Serbia, Slovenia, Spain and Switzerland report that their 
metadata updates depend on the data publishers and that the data publishers set a frequency for the 
metadata to get updated or harvested. 

Highlight from Spain – automatic metadata harvesting workflow 

In  Spain,  a  significant  percentage  (90–99 %)  of  the  metadata  on  the  national  portal  is  obtained 
automatically  from  the  source  rather  than  being  manually  edited.  This  automation  is  facilitated 
through a well-structured workflow managed by the portal’s back office, which includes a federation 
management  console.  This  console  enables  publishers  to  manage  and  schedule  automatic  data 
harvesting tasks efficiently. 

The process undertaken is as follows. 

1.  Defining the source uniform resource identifier (URI). Publishers begin by defining the URI 
of the resource description framework (RDF) / extensible markup language (XML) file that 
contains  the  source  open  data  catalogue,  ensuring  that  the  national  catalogue  can 
accurately retrieve the metadata. 

2.  Adjusting harvesting frequency. Publishers can set the frequency for metadata harvesting 
based on their needs, with options including manual updates or automatic updates on a 
daily, weekly, biweekly or monthly basis. 

3.  Automatic parsing and updating. Once the URI and frequency are configured, the national 
catalogue automatically parses the RDF/XML file and updates the relevant datasets on the 
portal. 

This automated process applies to all types of data published in source catalogues described using 
the RDF, ensuring that the metadata on the national portal remains consistent and up to date and 
requires minimal manual intervention. 

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Completeness of metadata 

Having complete and up-to-date data is important, since the applications and reuse cases may require 
historical or current data to be feasible and impactful. How current this data needs to be depends on 
what the data is about. Datasets that represent phenomena that change in real time, such as weather 
or traffic data, should be updated close to real time to enable complex applications. For other datasets, 
a different frequency of updates may be appropriate. Gaps in a time series can also negatively affect 
the usability of datasets. Again, the definition of ‘up to date’ depends on what the data represents and 
the frequency with which it is collected. Table 40 presents an overview of how countries responded to 
the question on this topic. 

Table 40: Countries’ responses to the question on the completeness of metadata 

Do you undertake efforts to ensure that published data covers the full period from 
when it was first published? 

EU-27 

EFTA 

20 Member States (74 %) report undertaking efforts to ensure that published data 
covers the complete time series. 

Iceland and Norway report undertaking efforts to ensure that published data covers 
the complete time series. 

Candidate 

Serbia and Ukraine report undertaking efforts to ensure that published data covers 
the complete time series. 

(Question Q4) 

Regular monitoring, auditing and validation processes are common methods to ensure that data covers 
the full time series. Countries such as Bulgaria, Estonia, Hungary and Serbia report having monitoring 
systems in place, either through portal editors or national teams that validate the completeness of 
data  over  time.  Luxembourg  reports  that  it  actively  monitors  the  availability  of  new  datasets  and 
engages  with  data  producers  to  explore  the  possibility  of  incorporating  historical  time-series  data. 
Many  countries  also  report  providing  direct  support,  guidance  and  recommendations  to  data 
publishers to maintain data integrity across time periods. 

Furthermore, Denmark and Slovakia note that they use the attribute dcat:temporal within the DCAT 
standard and recommend it to publishers. This attribute explicitly documents the temporal scope of 
datasets.  This  is  also  helpful  if,  for  example,  datasets  are  discontinued.  In  these  cases,  the 
dcat:temporal attribute helps clarify which time periods the new datasets cover, and users can see the 
temporal break or shift in the data series. 

Finally,  automation  is  used  in  some  countries  to  ensure  the  continuity  of  data  publication  and  to 
prevent time gaps. For example, Portugal and Slovakia report that they use automated processes to 
update datasets and ensure no data is missed. At the same time,  Latvia’s portal includes a feature 
whereby data  holders will see a message next  to datasets if they are  not  updated by the specified 
deadline, indicating the need to update the dataset. 

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Highlight from Czechia – registration of data series 

In Czechia, the  national portal supports the registration of ‘data series’, which are collections of 
datasets connected by certain contextual relationships. These connections can be  temporal (e.g. 
budget data over several years), spatial (e.g. lists of streets in different municipalities) or thematic 
(e.g. datasets from a particular system). See, for example, the data series on the fiscal outlook or 
the administrative register of economic entities. 

These  measures  help  to  ensure  that  datasets  are  comprehensive  and  that  the  data’s  temporal, 
spatial and thematic continuity is maintained. 

Interoperability of high-value datasets 

The DCAT-AP annotation for HVDs can help denote HVDs, making it easier for users to identify and 
access them. Moreover, by adhering to this standard, national portals can ensure that their datasets 
are interoperable with those from other countries. Such interoperability is key to unlocking the full 
potential of the data, enabling more comprehensive analyses. Table 41 presents an overview of how 
countries responded to the questions on this topic. 

Table 41: Countries’ responses to questions on the interoperability of HVDs 

Have you implemented the DCAT-AP 
HVDs tag to denote HVDs in your 
portal? 

Besides the DCAT-AP tag, have you 
implemented any other measures to 
ensure that HVDs are interoperable with 
datasets from other countries? 

EU-27 

17 Member States (63 %) report that 
they have implemented the DCAT-AP 
HVDs tag in their (national) open data 
portal(s). 

21 Member States (78 %) report that 
they have implemented other measures 
to ensure that HVDs are interoperable 
with datasets from other countries.  

(Questions Q5 and Q6) 

Non-EU countries were not surveyed on this question, since Commission Implementing Regulation (EU) 
2023/138 on HVDs applies only to EU Member States. 

Over  half  of  Member  States  have  implemented  the  DCAT-AP  HVD  annotations  in  their  open  data 
portals. However, some countries report challenges regarding compliance across all public bodies and 
adapting  their  CKAN  systems  to  implement  requirements  for  HVDs  fully.  Some  countries,  such  as 
Belgium  and  Germany,  emphasise  the  integration  of  DCAT-AP  HVDs  with  existing  geoportals.  In 
Germany, Geoportal Berlin has an API connection to the Berlin open data portal, meaning that data 
published  on  the  geoportal  is  automatically  indicated  in  the  open  data  portal.  In  Belgium,  the 
properties  for  HVDs  are  collected  during  harvesting  (i.e.  the  automated  process  of  gathering  and 
synchronising  datasets)  on  geoportals  like  MetaWal,  where  there  is  also  mapping  between  data 
covered  under  the  infrastructure  for  spatial  information  in  Europe  (Inspire)  directive  (Directive 
2007/2/EC), a European directive for geospatial data, and DCAT-AP HVDs. Slovenia and Finland also 
emphasise that they harvest data from geoportals and align it with the HVD structure. Indeed, several 
countries,  including  Belgium,  Spain,  Austria  and  Romania,  with  advanced  initiatives  related  to 
geospatial,  environmental  and  earth  observation  data,  have  relied  on  the  Inspire  directive’s 
recommendations to ensure cross-border interoperability. 

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In addition to the DCAT-AP HVD annotations, Member States highlight various ways to ensure that 
their HVDs are interoperable with datasets of other countries. For example, Czechia and France note 
that they directly communicate with data producers from other countries. Denmark and Ireland note 
that they encourage the use of standardised licences (e.g. Creative Commons (CC)) or data formats 
(e.g. CSV, JavaScript object notation (JSON), XML and GeoJSON) to facilitate interoperability. Belgium 
and Ireland also report focusing on API development as a way to ensure data interoperability. 

6.3. Monitoring and measures 
This indicator assesses the extent to which mechanisms are in place to evaluate and improve metadata 
quality  and  its  compliance  with  licensing  standards.  Moreover,  the  indicator  looks  at  the  support, 
guidelines  and  tools  available  to  assist  data  publishers  in  publishing  high-quality  metadata  and 
choosing the correct licence type for their data. 

Monitoring the quality of metadata on portals 

Monitoring metadata quality is important for ensuring datasets are discoverable,  well documented 
and usable by stakeholders. From manual reviews to automated systems, countries use  a range of 
methods  to  ensure  compliance  with  standards.  Dashboards  and  reports  are  effective  tools  for 
monitoring and visualising metadata quality, and providing public access to these resources enhances 
transparency and accountability. Table 42 presents an overview of how countries responded to the 
questions on this topic. 

Table 42: Countries’ responses to questions on monitoring the quality of metadata 

EU-27 

EFTA 

Do you monitor the quality of the 
metadata available on your portal? 

26  Member  States  (96 %),  all  except 
Finland, report monitoring the quality 
of metadata available on their portals. 

Do you publish information on the 
quality of the metadata available on 
the portal? 

22 Member States (81 %), with the 
recent additions of Latvia, Malta and 
Romania, report that they publish 
information on the quality of metadata 
available on their portals. 

All three participating EFTA countries 
report monitoring the quality of 
metadata available on their portals. 

reports 

it  publishes 
Norway 
information on the quality of metadata 
available on its portal. 

that 

Candidate 

Serbia and Ukraine report monitoring 
the quality of metadata available on 
their portals. 

reports 

Ukraine 
it  publishes 
information on the quality of metadata 
available on its portal. 

that 

(Questions Q7 and Q8) 

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Most countries use automated systems to ensure metadata quality. For example, Estonia, Germany, 
Lithuania,  the  Netherlands  and  Switzerland  report  that  they  use  automated  systems  for  checking 
broken  links,  compliance  with  standards  such  as  DCAT-AP  and  the  completeness  of  data.  Some 
countries  such  as  Bulgaria,  Latvia  and  Ukraine  also  report  performing  manual  reviews  through 
administrators. Additionally, Lithuania, Austria, Poland and Romania report enabling users to provide 
feedback on metadata quality, which portal administrators then take into account. 

Highlight from Portugal – metadata quality box 

In Portugal, the national open data portal (dados.gov.pt; Figure 15) provides a dedicated ‘quality’ 
box within the administration area to help users improve the quality of their published dataset’s 
metadata. This tool offers an overview of how well the dataset’s metadata is structured, highlighting 
areas  that  could  be  enhanced  to  improve  discoverability  and  reuse.  The  system  automatically 
analyses the metadata for each dataset, assessing whether it has been correctly filled out. Based on 
this analysis, it suggests improvements,  such as adding more  accurate and detailed descriptions, 
including  additional  tags,  or  attaching  resources  in  more  open,  machine-readable  formats.  This 
proactive approach to monitoring and enhancing metadata quality ensures that contributors can 
easily publish high-quality, reusable data, benefiting the broader open data ecosystem. 

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Figure 15: Screenshot of the data provider dashboard view on Portugal’s portal 

Many countries use dashboards and reports to monitor and visualise metadata quality. Some, such as 
Italy,  Poland,  Spain  and  Ukraine,  report  having  publicly  available  dashboards  and  reports,  while 
others,  such  as  France,  Luxembourg  and  Serbia,  report  that  these  resources  are  mainly  used  by 
internal personnel. In addition, Czechia and Germany integrate their public dashboards with SPARQL 
(a  query  language  for  databases)  to  allow  users  to  access  the  metadata  quality  data  through  an 
interface or end point. Several countries, including  Hungary,  Ireland, Norway  and  Romania, report 
integrating  standardised  EU  tools  and  frameworks,  specifically  the  metadata  quality  assessment 
(MQA) methodology from data.europa.eu, to assess and monitor metadata quality. 

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Setting metadata standards and licensing requirements 

Metadata serves as a foundational layer that describes the content, context and structure of datasets, 
enabling users to discover and utilise data effectively. Ensuring the quality of metadata is essential for 
fostering findability, interoperability and effective data sharing. Countries often set various standards 
and guidelines that organisations must implement to govern metadata quality and ensure the usability 
and reliability of open data. Licensing is a common way to govern open data and relevant metadata 
quality. Without a licence, data may be publicly available, but reusers will not have certainty about 
what permissions they have to access, use, change or share the data under copyright or database laws. 
Table 43 presents an overview of how countries responded to the questions on this topic. 

Table 43: Countries’ responses to questions on metadata standards and licensing requirements 

Do you set any 
standards on 
metadata quality 
that data providers 
must abide by? 

Do your open data 
publication or licensing 
guidelines recommend 
using CC licences? 

26 Member States 
(96 %), all except 
Greece, report 
that they set 
standards on 
metadata quality 
that data providers 
must abide by. 

25 Member States (93 %), 
all except Greece and 
Hungary, report that their 
publication or licensing 
guidelines provide 
recommendations for 
using CC licences. Italy 
and Finland are the most 
recent additions to this 
group. 

What percentage 
of the open data 
available on the 
national portal is 
accompanied by 
licensing 
information? 

20 Member States 
(74 %) report that 
more than 90 % of 
their datasets 
have licensing 
information. 

Switzerland 
reports that it sets 
standards on 
metadata quality 
that data providers 
must abide by. 

All three participating 
EFTA countries report that 
their publication or 
licensing guidelines 
provide 
recommendations for 
using CC licences. 

Norway and 
Switzerland 
report that over 
90 % of their 
datasets have 
licensing 
information. 

EU-27 

EFTA 

Candidate  Serbia and 

Ukraine report 
that they set 
standards on 
metadata quality 
that data providers 
must abide by.  

Albania (the most recent 
addition), Serbia and 
Ukraine report that their 
publication or licensing 
guidelines provide 
recommendations for 
using CC licences. 

Serbia and 
Ukraine report 
that more than 
90 % of their 
datasets have 
licensing 
information. 

How many 
different licences 
are used on your 
portal? 

17 Member States 
(63 %) report 
having one to four 
licences on their 
portal. Only 
Belgium, Czechia 
and Sweden 
report having 
more than 10 
licences on their 
portals. 

All three 
participating EFTA 
countries report 
having one to four 
licences on their 
portal. 

Serbia and 
Ukraine report 
having one to four 
licences on their 
portal. 

(Questions Q10, Q11, Q12 and Q13) 

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Countries  often  set  mandatory  metadata  fields  that  must  be  filled  in  when  publishing  datasets. 
Specifically, many countries tend to implement variations of the DCAT-AP metadata standard, such as 
specifying key metadata fields as mandatory and, in some cases, mandating the inclusion of additional 
metadata classes compared with those required by the general DCAT-AP framework. 

Most countries also have specific requirements for and recommendations on the licences that must 
be  applied  to  datasets.  In  many  countries,  the  CC  Attribution  4.0  International  (CC  BY  4.0)  and  CC 
Universal (CC0) licences are mandated by laws or national strategies for public sector data publication. 
For example, the Austrian framework for open government platforms serves as an official agreement 
between the federal and state levels. According to this agreement, CC BY 4.0 is mandatory for Austrian 
public sector bodies for the publication of open government data. 

Several countries offer flexibility in terms of licensing, allowing data providers to choose from various 
CC licences, although CC BY 4.0 and CC0 are often highlighted as preferred options. For example, in the 
Netherlands, it is mandatory to select a licence. However, publishers are free to choose which licence 
from a list provided by the government. In Cyprus, public sector bodies must seek permission from the 
licensing authority to use a licence other than CC BY 4.0 or CC Attribution-ShareAlike 4.0 International 
(CC BY-SA 4.0). 

Highlight from Cyprus –tailored DCAT-AP application 

Cyprus  has  adopted  a  tailored  version of  the  DCAT-AP  framework  to  maintain  high  standards of 
metadata quality on its national data portal. This variation includes more mandatory classes than 
the  standard  EU  framework,  ensuring  that  metadata  is  more  comprehensive  and  uniform.  In 
addition to the required fields, optional DCAT-AP fields are also available to enhance the metadata’s 
depth. 

Two standardised usage licences were selected to further support uniformity and practicality: CC BY 
4.0  and  CC  BY-SA  4.0.  Public  bodies  can  choose  the  most  appropriate  licence  when  publishing 
datasets, ensuring clear and consistent data usage rights. 

Cyprus mandates a minimum of 15 fields for metadata, which include essential information such as: 

•  dataset title 
•  description 
• 
topics 
• 
licence to use 
•  geospatial coverage 
•  access uniform resource locator (URL). 

Support activities for data providers 

Activities to support data providers with publishing high-quality data can take many forms. Documents, 
tools, training and tailored guidance  are common methods that countries  use to ensure publishers 
supply  high-quality  datasets.  Table 44  presents  an  overview  of  how  countries  responded  to  the 
questions on this topic. 

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Table 44: Countries’ responses to questions on support for data providers 

Do you publish guidelines and have tools 
to assist publishers in publishing high-
quality metadata? 

23  Member  States  (85 %),  all  except 
Bulgaria,  Greece,  Croatia  and  Malta, 
report  that  they  publish  guidelines  and 
have tools in place to assist publishers in 
publishing high-quality metadata. 

Besides providing guidelines, are regular 
activities conducted or mechanisms in 
place to assist publishers in supplying 
high-quality datasets? 

22 Member States (81 %) report that 
they conduct regular activities or have 
mechanisms in place to assist publishers 
in supplying high-quality datasets.  

Norway and Switzerland report that they 
publish guidelines and have tools in place 
to assist publishers in publishing high-
quality metadata. 

Norway and Switzerland report that they 
conduct 
regular  activities  or  have 
mechanisms in place to assist publishers 
in supplying high-quality datasets. 

EU-27 

EFTA 

Candidate  Serbia and Ukraine report that they 

publish guidelines and have tools to assist 
publishers in publishing high-quality 
metadata.  

Albania,  Serbia  and  Ukraine  report  that 
they  conduct  regular  activities  or  have 
mechanisms in place to assist publishers 
in supplying high-quality datasets. 

Most countries publish manuals and handbooks that include information on publishing high-quality 
metadata.  Czechia,  Denmark,  Luxembourg,  Hungary  and  Sweden  also  report  that  they  provide 
manuals on how to properly license metadata, helping to clarify how data can be used and whether it 
can be shared or modified. 

(Questions Q9 and Q14) 

Highlight from Spain – guides for improving data and metadata quality 

In Spain, there are several guides aimed at improving the quality of both the metadata and the data 
itself. These include: 

•  Practical Manual to Improve Open Data Quality, 
•  How to develop a plan of measures to promote openness and reuse of open data, 
•  Practical Guide for Publishing Linked Data in RDF, 
•  Practical Guide for Publishing Spatial Data, 
•  Practical Guide for Publishing Tabular Data in CSV Format, 
•  Practical Guide for Publishing Data through APIs, 
• 
•  How to Implement Linked Data: Real case of the Aragón open data portal, 
•  Open Data in Real Time: Use cases for smart cities, 
•  Guide for priority datasets to be published by municipalities, 
•  Data Visualisation Guide for Local Authorities. 

Introduction to Data Anonymisation: Techniques and case studies, 

Furthermore,  Belgium,  Germany,  Estonia,  France,  Italy,  Lithuania  and  Poland  provide  metadata 
validation  tools  to  ensure  compliance  with  established  standards  such  as  DCAT-AP.  For  example, 

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Germany provides a self-service tool with detailed metadata end point testing and feedback. Estonia’s 
open  Rihake  tool  allows  users  to  describe  datasets,  classifiers  and  services  and  to  compile  data 
dictionaries and business glossaries, while Belgium provides a lightweight validator tool that checks 
metadata against  certain  standards  (via  GitHub).  Similarly,  Italy  reports  that  its  national open  data 
portal  includes  a  metadata  validator  that  checks  the  conformity  of  its  metadata  to  its  national 
metadata profile DCAT-AP_IT. 

In  addition  to  guiding  documents,  training  is  a  prominent  way  in  which  governments  help  data 
providers to publish high-quality datasets. For example, Czechia, Denmark and Romania note that they 
regularly host webinars about ensuring high-quality data management. In addition, Czechia, Estonia, 
Hungary,  Ireland,  Poland  and  Ukraine  report  that  they  specifically  utilise  e-learning  to  train  data 
providers on publishing high-quality data, which also includes information on the proper procedures 
for metadata. 

Many countries also conduct ongoing meetings with data providers to improve data quality. These are 
often held regularly, allowing for a continuous dialogue and exchange of knowledge (e.g. on updates 
and best practices) between the open data team and data providers. Ireland and Spain frame these 
meetings as ‘audits on data quality’, at which data providers receive personalised evaluations of their 
data (and metadata) quality and discuss their results. While most countries report that these meetings 
with data providers are one-on-one, some countries, such as Luxembourg, Norway and Switzerland, 
have routine forums and peer exchanges with established networks and groups of public sector data 
providers. These sessions facilitate knowledge exchange on topics such as publishing high-quality data. 

Highlight from Luxembourg – three-tier approach for ensuring high-quality datasets 

Luxembourg  has implemented a comprehensive, multi-tier strategy to continuously  improve  the 
quality of public sector open data. 

1.  Training and capacity building. The National Institute of Public Administration offers regular 
training sessions dedicated to public sector open data. These sessions are available to all 
public sector agents and cover the national portal and related open data topics. This ensures 
that public officials are well equipped with the knowledge and skills necessary to manage 
open data effectively. 

2.  Open data representatives group. In line with the Prime Minister’s directive, public sector 
organisations  are  required  to  appoint  official  open  data  representatives.  This  group 
facilitates regular meetings to exchange best practices, technical support and general open 
data information. This network of representatives enhances collaboration and ensures that 
organisations meet the obligations of the open data directive (Directive (EU) 2019/1024) 
and  national  laws.  The  first  meeting  of  this  series  took  place  in  April  2024,  marking  the 
beginning of this collaborative effort. 

3.  One-on-one support  for data  owners.  Luxembourg’s open data team works closely with 
individual data owners, providing tailored advice and technical assistance when datasets are 
published. This personalised approach ensures a focus on data quality, including aspects like 
regular updates, resource formats and metadata completeness. Additionally, Luxembourg 
has  implemented  a  link-checking  programme  to  automatically  verify  the  availability  of 
datasets not hosted directly on the portal. The system runs monthly tests, and any issues 
(e.g. broken links) are addressed by contacting the relevant organisations. This has proven 
effective  in  maintaining  data  availability,  as  demonstrated  with  Luxembourg’s  national 
weather data provider, Meteolux. 

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6.4. DCAT-AP compliance 
DCAT is a World Wide Web Consortium standard designed to facilitate interoperability between data 
catalogues published online. DCAT-AP is an extension to DCAT – an ‘application profile’ – developed 
by the European Commission to improve interoperability and foster the discoverability and reuse of 
open  data  across  European  catalogues.  The  ‘DCAT-AP  compliance’  indicator  assesses the  extent  to 
which metadata on national portals complies with the DCAT-AP standard for describing public sector 
datasets and what efforts are taken to assist data publishers in following DCAT-AP. 

Creating a framework for DCAT-AP compliance 

Having  a  standard  way  to  describe  datasets  helps  to  ensure  that  data  catalogues  from  different 
organisations  or  regions  are  compatible.  This  is  why  many  national  portals  follow  the  DCAT-AP 
framework or other standards to ensure interoperability with DCAT-AP. Many countries have created 
national extensions of DCAT-AP to tailor the general framework to their specific needs, enhancing its 
relevance  and  functionality  for  their  contexts.  Table 45  presents  an  overview  of  how  countries 
responded to the questions on this topic. 

Table 45: Countries’ responses to questions on creating a framework for DCAT-AP compliance 

Does the national portal follow the DCAT-
AP framework or, if not, are standards in 
place to ensure interoperability with 
DCAT-AP? 

24 Member States (89 %), all except 
Bulgaria, Greece and Malta, report that 
their national portals follow the DCAT-AP 
framework or ensure interoperability 
with DCAT-AP. 

Norway and Switzerland report that their 
national portals follow the DCAT-AP 
framework or ensure interoperability 
with DCAT-AP. 

Is there a national extension of the DCAT-
AP standard developed for your country? 

15 Member States (56 %) report having a 
national extension of the DCAT-AP 
standard. 

Norway and Switzerland report having a 
national extension of the DCAT-AP 
standard. 

EU-27 

EFTA 

Candidate  Serbia and Ukraine report that their 
national portals follow the DCAT-AP 
framework or ensure interoperability 
with DCAT-AP. 

None of the participating candidate 
countries reports having a national 
extension of the DCAT-AP standard. 

(Questions Q15 and Q19) 

Several countries ensure compliance with DCAT-AP by leveraging existing technical platforms or plug-
ins designed with built-in DCAT-AP support. For instance, many countries note that they use the CKAN 
platform, which has a plug-in that allows users to describe datasets according to DCAT-AP standards. 
On the other hand, Portugal and Serbia report using the Udata platform, which follows the DCAT-AP 
standard and has tools for mapping other frameworks and standards (e.g. CKAN and operational data 
store (ODS)). Ireland and Norway highlight that they have implemented tools to automatically validate 
metadata against DCAT-AP standards. 

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Highlight from Ireland – automated audit tool for DCAT-AP 

In Ireland, the national open data portal, data.gov.ie, fully adheres to the DCAT-AP framework to 
ensure interoperability and consistency with international open data standards. Compliance with 
DCAT-AP  is  mandated  for  all  data  published  on  the  platform,  which  is  outlined  in  the  portal’s 
technical framework and the publishing guidelines. 

To ensure compliance, the portal advocates using URIs, which play a crucial role in improving data 
discovery  and  interoperability  across  platforms.  Additionally,  the  portal  provides  an  audit  tool 
specifically designed to validate datasets against DCAT-AP standards. This tool checks for missing 
mandatory properties, verifies the correct use of controlled vocabularies and ensures adherence to 
the DCAT-AP schema. 

Moreover, the portal offers a range of training resources to support data providers in creating high-
quality,  DCAT-AP-compliant  metadata.  These  resources  include  best  practices,  examples  and 
tutorials,  all  aimed  at  enhancing  the  quality  and  interoperability  of  published  datasets.  Through 
these  measures,  data.gov.ie  ensures  that  all  published  data  meets  international  standards, 
facilitating better data sharing and reuse. 

Although  not  compulsory,  many  countries  have  developed  national  extensions  of  the  DCAT-AP 
standard. These countries often emphasise that their modifications are intended to better serve the 
needs of their national contexts, particularly for the public sector and data communities. For example, 
Czechia,  Italy  and  Poland  report  making  such  modifications  to  comply  with  their  specific  legal 
frameworks  or  regulations  that  govern  data.  These  legal  obligations  often  necessitate  changes  to 
metadata, vocabularies or properties to ensure compliance. 

Other  countries  report  that  they  have  made  national  extensions  to  ensure  more  structured  and 
comprehensive  metadata.  This  often  involves  adding  additional  mandatory  fields  or  adapting 
vocabularies to ensure consistency and data quality. For example, the Netherlands reports enriching 
the EU standard by enabling fewer free-answer options, which it believes allows easier verification of 
the metadata quality. 

Compliance with the DCAT-AP specifications 

DCAT-AP has various metadata properties that can be used to describe data. As a specification, DCAT-
AP  defines  a  hierarchy  of  properties,  grouped  as  classes,  that  are  mandatory,  recommended  or 
optional. Table 46 presents an overview of how countries responded to the questions on this topic. 

Table 46: Countries’ responses to questions on compliance with DCAT-AP specifications 

EU-27 

What is the percentage 
of metadata on your 
portal that is DCAT-AP 
compliant in terms of 
mandatory classes? 

22 Member States (81 %) 
report that more than 
90 % of their portals’ 
metadata complies with 
DCAT-AP’s mandatory 
classes. 

What is the percentage of 
metadata on your portal 
that uses DCAT-AP 
recommended classes? 

What is the percentage of 
metadata on your portal 
that uses DCAT-AP optional 
classes? 

19 Member States (70 %) 
report that more than 90 % 
of the metadata on their 
portals follows DCAT-AP’s 
recommended classes. 

16 Member States (59 %) 
report that more than 90 % 
of the metadata on their 
portals follows DCAT-AP’s 
optional classes. 

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EFTA 

What is the percentage 
of metadata on your 
portal that is DCAT-AP 
compliant in terms of 
mandatory classes? 

Norway and Switzerland 
report that more than 
90 % of the metadata on 
their portals is compliant 
with DCAT-AP’s 
mandatory classes. 

What is the percentage of 
metadata on your portal 
that uses DCAT-AP 
recommended classes? 

What is the percentage of 
metadata on your portal 
that uses DCAT-AP optional 
classes? 

Norway and Switzerland 
report that more than 90 % 
of the metadata on their 
portals follows DCAT-AP’s 
recommended classes. 

Switzerland reports that at 
least 50 % of the metadata 
on its portal follows DCAT-
AP’s optional classes. For 
Norway, this percentage is 
at least 30 % and, for 
Iceland, it is less than 10 %. 

Ukraine reports that more 
than 90 % of the metadata 
on its portal follows DCAT-
AP’s optional classes. 

(Questions Q16, Q17 and Q18) 

Candidate  Serbia and Ukraine 

report that more than 
90 % of the metadata on 
their portals is compliant 
with DCAT-AP’s 
mandatory classes. 

Serbia and Ukraine report 
that more than 90 % of the 
metadata on their portals 
follows DCAT-AP’s 
recommended classes. 

Despite growing compliance with DCAT-AP, not all data providers publish data that fully aligns with the 
DCAT-AP standard. Investigating the common causes of non-compliance can help national portals to 
develop strategies to help data providers improve the quality of their metadata. Table 47 presents an 
overview of how countries responded to the question on this topic. 

Table 47: Countries’ responses to the question on non-compliance with the DCAT-AP standard 

EU-27 

EFTA 

Do you investigate the most common causes of the lack of DCAT-AP compliance? 
19  Member  States  (70 %),  with  Greece  and  Sweden  as the most  recent  additions, 
report investigating the most common causes of the lack of DCAT-AP compliance. 

Switzerland reports investigating the most common causes of the lack of DCAT-AP 
compliance. 

Candidate 

Serbia and Ukraine report investigating the most common causes of the lack of DCAT-
AP compliance. Serbia newly reports this. 

(Question Q20) 

The  most  common  cause  of  a  lack  of  compliance  with  DCAT-AP  is  a  lack  of  training,  awareness  or 
expertise on the standard. In other words, some data providers are unfamiliar with the requirements 
of DCAT-AP and do not know how to properly manage and structure data in line with the standards. 

Some countries note that some compliance issues relate to the need to map or integrate metadata 
from different systems or translate metadata based on a different standard from DCAT-AP. Denmark 
and  Lithuania  specifically  note  that  there  are  challenges  associated  with  mapping  or  converting 
geospatial datasets structured according to the Inspire standard to/into the DCAT-AP standard. 

Other  causes  include  the  cost  and  complexity  of  updating  the  national  platform  while  maintaining 
custom  settings when  the  DCAT-AP  specification  is  updated.  When  datasets  are  entered manually, 
metadata may be incomplete or incorrectly filled, leading to deviations from the standard. 

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6.5. Deployment quality and linked data 
This indicator examines the extent to which countries use a model, such as the Berners-Lee 5-star open 
data model or the FAIR principles, to assess the quality of data deployment. This indicator also assesses 
the  extent  to  which  data  is  available  under  an  open licence,  in  structured  and  machine-readable 
formats, with URIs and links to other data sources. 

Use of models for deployment quality 

A model for assessing data deployment is crucial because it enables national portal teams to judge 
systematically and adaptively whether a dataset is more or less likely to be reused, given the quality it 
offers portal users. Table 48 presents an overview of how countries responded to the question on this 
topic. 

Table 48: Countries’ responses to the question on the use of models for deployment quality 

EU-27 

EFTA 

Do you use a model to assess the quality of deployment of data in your country? 
24 Member States (89 %), all except Bulgaria, Hungary and the Netherlands, report 
using a model to assess the quality of deployment of data. 

All  participating  EFTA  countries  report  using  a  model  to  assess  the  quality  of 
deployment of data. 

Candidate 

Serbia and Ukraine report using a model to assess the quality of deployment of data. 
(Question Q23) 

The 5-star open data model is a framework designed to assess the quality and openness of data based 
on five progressive criteria. Each level of the model corresponds to a star, with more stars indicating 
higher levels of openness and usability. The 5-star open data model is the most frequently cited model 
used by countries for assessing data quality. Some countries, such as Cyprus and Ukraine, even report 
that using the 5-star model is written into their national guidelines and policies. 

Many countries also integrate the FAIR principles into their data quality assessments. The FAIR data 
principles state that it should be possible to find data, there should be information about how to gain 
access to the data, the data should be compatible with other data and it should be possible to reuse 
the  data.  Countries  including  Belgium,  Estonia,  Spain,  Italy,  Luxembourg  and  Finland  report 
incorporating both the 5-star model and the FAIR principles into their models for assessing the quality 
of deployment of data. 

Some  countries  utilise  different  assessment  techniques.  For  example,  Denmark  has  established  a 
‘common  language  for  data  quality’,  which  is  intended  as  a  shared  reference  point  for  discussions 
related to data quality issues. 

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Highlight from Spain – comprehensive data quality model 

In Spain, a comprehensive approach is utilised to ensure the quality of open data deployment by 
leveraging both the 5-star open data model and the FAIR principles. The 5-star open data model is 
used  to  classify  distributions  of  datasets  based  on  their  publication  format.  In  addition,  the 
Government  of  Spain’s  Data  Office  uses  the  FAIR  principles  as  a  basis  for  defining  the  guiding 
principles for the data and its infrastructures and facilitating its reuse. Furthermore, the national 
portal promotes the publication of open data that achieves at least the 3-star level on the scale (see 
an example of this promotion, which describes the process of transforming tabular datasets in CSV 
(3 stars) into linked and semantically enriched data (5 stars)). 

Activities for data providers to ensure high-quality data 

The  quality of  data  on  national  portals  depends  on the  quality  of  data  supplied  by  data  providers. 
Therefore, assisting data providers with skills and tools is one way to improve the quality of published 
data. Table 49 presents an overview of how countries responded to the question on this topic. 

Table 49: Countries’ responses to the question on activities for data providers to ensure high-quality 
data 

EU-27 

EFTA 

Do  you  conduct  activities  to  promote  and  familiarise  data  providers  with  ways  to 
ensure higher quality data? 
26 Member States (96 %), all except Bulgaria, report conducting activities to promote 
and familiarise data providers with ways to ensure higher quality data.  

All  participating  EFTA  countries  report  conducting  activities  to  promote  and 
familiarise data providers with ways to ensure higher quality data 

Candidate 

Albania, Serbia and Ukraine report conducting activities to promote and familiarise 
data providers with ways to ensure higher quality data. Albania is the most recent 
addition to this group. 

(Question Q24) 

Many countries use training programmes and workshops to educate data providers on best practices 
for data quality. This includes training on the 5-star open data model and FAIR principles. Estonia and 
Ukraine note that their general training schemes include theoretical knowledge and practical skills for 
effectively publishing datasets. Norway and Spain also report publishing blogs for data providers that 
disseminate best practices. Several countries have developed guidelines and best practices to assist 
data providers in understanding and achieving high data quality. 

Additionally,  many  countries  are  promoting  efforts  to  engage  with  data  providers  more,  providing 
feedback  on  their  datasets  and  sharing  best  practices.  For  example,  Belgium,  Greece  and  Poland 
report having regular consultations with data providers, working one-on-one  to improve their data 
quality. 

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Highlight from Sweden – the data ambassador programme 

In  Sweden,  the  data  ambassador  programme,  launched  by  the  Swedish  Agency  for  Digital 
Government,  is  a  pioneering  educational  initiative  aimed  at  enhancing  the  understanding  and 
implementation of open data practices among public sector employees. Developed in response to 
the  increasing  need  for  effective  data  sharing  following  the  enactment  of  the  Open  Data  Act  in 
August  2022, the  programme  targets  individuals  working  operationally with open  data  and  data 
sharing within public organisations. 

This digital learning initiative offers a self-paced format that includes recorded videos, references 
for  further  reading  and  short  knowledge  assessments,  focusing  on  fundamental  processes  and 
concepts of open data in alignment with the Open Data Act. By equipping participants with essential 
knowledge on how to share and utilise data effectively, the programme fosters an environment in 
which data sharing becomes a strategic resource. 

The  agency  plans  to  expand  the  programme  by  offering  additional  courses  tailored  to  various 
stakeholders,  including  subcontractors,  managers  and  legal  professionals.  This  initiative  aims  to 
strengthen  the  understanding  of  data  as  a  strategic  resource,  ultimately  promoting  higher  data 
quality across the public sector. 

Deployment quality 

Several  best  practices  can  enhance  the  accessibility  and  reusability  of  open  data.  These  include 
ensuring datasets are made available under an open data licence (e.g. CC) and having licences provided 
in  a  structured  format.  Additionally,  it  is  good  practice  to  ensure  that  datasets  are  in  an  open  and 
machine-readable format (e.g. CSV, JSON and XML) and to assign URIs to the datasets. Finally, datasets 
should  also  be  linked  to  various  sources,  which  through  the  use  of  URIs  can  expand  the  dataset’s 
context and relevance. Table 50 presents an overview of how countries responded to the questions on 
this topic. 

Table 50: Countries’ responses to questions on deployment quality 

EU-27 

What 
percentage of 
datasets are 
made 
available 
under an 
open licence? 

22 Member 
States (81 %) 
report that 
over 90 % of 
their datasets 
have an open 
licence. 

What 
percentage of 
licences are 
provided in a 
structured 
data format? 

19 Member 
States (70 %) 
report that 
over 90 % of 
their datasets 
have 
structured 
licence data. 

What 
percentage of 
datasets are 
provided in an 
open and 
machine-
readable 
format? 

17 Member 
States (63 %) 
report that 
over 90 % of 
their datasets 
are in a 
machine-
readable 
format. 

What 
percentage of 
datasets use 
URIs? 

What 
percentage of 
datasets link 
to other 
sources? 

8 Member 
States (30 %) 
report that 
over 90 % of 
their datasets 
use URIs. 

5 Member 
States (19 %) 
report that 
over 90 % of 
their datasets 
are linked to 
other sources. 

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What 
percentage of 
datasets are 
made 
available 
under an 
open licence? 

Switzerland 
reports that 
over 90 % of 
its datasets 
have an open 
licence. 

EFTA 

Candidate  Serbia and 

Ukraine 
report that 
over 90 % of 
their datasets 
have an open 
licence. 

What 
percentage of 
licences are 
provided in a 
structured 
data format? 

All three 
participating 
EFTA countries 
report that 
over 90 % of 
their datasets 
have 
structured 
licence data. 

Serbia reports 
that over 90 % 
of its datasets 
have 
structured 
licence data. 

What 
percentage of 
datasets are 
provided in an 
open and 
machine-
readable 
format? 

Iceland reports 
that over 90 % 
of its datasets 
are in a 
machine-
readable 
format. 

Serbia and 
Ukraine report 
that over 90 % 
of their 
datasets are in 
a machine-
readable 
format. 

What 
percentage of 
datasets use 
URIs? 

What 
percentage of 
datasets link 
to other 
sources? 

Norway 
reports that 
over 90 % of its 
datasets use 
URIs. 

Norway 
reports that 
over 90 % of its 
datasets are 
linked to other 
sources. 

None of the 
participating 
candidate 
countries 
reports using 
URIs. 

None of the 
participating 
candidate 
countries 
reports linking 
datasets to 
other sources. 

(Questions Q25, Q26, Q27, Q28 and Q29) 

6.6. Pilot indicator: automated tests of metadata quality 
Pilot indicator – automated tests 

In  addition  to  gathering  qualitative  data  about  metadata  quality,  such  quality  can  also  be 
quantitatively assessed. The MQA is a tool designed to evaluate the quality of metadata harvested 
by  data.europa.eu.  It  enables  data  providers  and  portals  to  assess  their  metadata  and  receive 
recommendations for improvement. 

The  MQA’s  methodology  (which  in  undergoing  a  recalibration)  examines  five  specific  questions, 
which focus on: 

• 

• 

• 

• 

• 

compliance with DCAT-AP and related standards, 

the disclosure of information beyond DCAT-AP requirements, 

the accessibility of referenced data, 

the machine readability of data formats 

the use of licences. 

As a pilot project in the ODM assessment, we analysed five indicators from the MQA, calculating 
summary  statistics  across  national  catalogues  that  were  findable  on  data.europa.eu.  Certain 
countries,  including  Albania,  Bosnia  and  Herzegovina,  Estonia,  Greece  and  Malta,  were  not 

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assessed, as their primary open data catalogues were not findable on data.europa.eu. The results 
presented  below  are  the  percentages  of  datasets  across  the  selected  catalogues  that  met  each 
criterion.  The  metrics  were  extracted  from  the  MQA  on  31 October  2024.  The  findings  did  not 
contribute to the countries’ maturity scores. 

The machine readability indicator evaluates if a distribution is in a machine-readable format based 
on data.europa.eu’s GitLab repository vocabulary. 

•  65 %  of  the  distributions  assessed  are  machine  readable.  Bulgaria  scored  100 %  on  this 

indicator. 

The  DCAT-AP  compliance  indicator  evaluates  metadata  conformity  with  the  DCAT-AP  standard 
using  the  shapes  constraint  language  (SHACL)  validation  from  data.europa.eu.  SHACL  is  a 
recommendation  from  the  World  Wide  Web  Consortium  and  is  used  for  validating  RDF  graphs 
against a set of shapes. 

•  21 % of the distributions assessed are DCAT-AP compliant, with Hungary scoring 100 % on 

this indicator. 

The download URL indicator evaluates whether direct access to data is provided via a download 
URL. 

•  35 %  of  the  distributions  assessed  included  a  direct  link,  with  France,  Italy,  Cyprus, 

Lithuania, Poland, Slovakia and Finland scoring 100 % on this indicator. 

The licence information indicator evaluates if distributions specify licence details, facilitating reuse. 

•  55 %  of  the  distributions  assessed  provide  licence  information,  with  Cyprus,  Czechia, 
Germany, Iceland, Italy, Luxembourg, the Netherlands, Spain  and Switzerland  achieving 
100 % on this indicator. 

The  licence  vocabulary  indicator  evaluates  the  accuracy  of  licence  specifications  (e.g.  correctly 
versioned  CC  licences).  The  specifications  are  derived  from  the  FAIR  principles.  The  MQA 
recommends and credits the usage of controlled vocabularies. The data.europa.eu portal publishes 
its controlled vocabularies on GitLab. The vocabularies are derived from the EU vocabularies. 

•  46 %  of  the  distributions  assessed  include  licence  information  that  matches  controlled 

vocabularies, with Bulgaria, Ireland, Cyprus and Portugal scoring 100 % on this indicator.  

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Chapter 7: Open data impact 

The open data directive  (Directive  (EU) 2019/1024)  and the  implementing regulation on high-value 
datasets (HVDs) (Regulation (EU) 2023/138) encourage EU Member States to promote the reuse of 
public sector information, aiming to generate economic, environmental and societal benefits. Open 
datasets tend to be further processed to create new insights or solutions known as reuse cases. This 
typically involves transforming or integrating the data with other sources and using specialised tools 
or analytical methods to extract value. This is what can be  referred to as the impact of open data. 
Impact is realised when open data is repurposed to create benefits in various fields. 

The  impact  dimension  of  the  open  data  maturity  (ODM)  assessment  is  designed  to  encourage 
countries to implement mechanisms for monitoring open data reuse and to better understand and 
address the needs of data users. Hence, the impact dimension evaluates how well countries define 
and measure data reuse, the steps taken to assess reuse and user needs, and the presence of reuse 
examples in the domains of government, society, the environment and the economy. Table 51 outlines 
the key components of this dimension. 

Table 51: Indicators of the impact dimension 

Indicator 

Strategic awareness 

Measuring reuse 

Created impact 

social 

•  governmental 
• 
•  environmental 
•  economic 

Key elements 

There is a national definition of open data reuse. Mechanisms are in 
place at the national, regional or local level to monitor and foster open 
data reuse, including in relation to HVDs. A methodology exists to 
measure the impact derived from reusing open data. 

Tools are in place to understand which datasets are reused and how. 
There is a process for gathering and classifying reuse cases 
systematically. Activities are performed to better understand reusers’ 
needs. 

The impact created by open data has been systematically studied, and 
reuse examples exist that showcase the impact of open data in the 
governmental, social, environmental and economic domains. 

This  chapter  will  first  present  overall  performance  on  the  impact  dimension  and  then  provide  a 
summary of the results and best practices for each indicator. 

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Contents 

7.1. Overall performance on the impact dimension ..................................................................... 110 

7.2. Strategic awareness ................................................................................................................. 114 

Definition of open data reuse ..................................................................................................... 114 

Monitoring open data reuse ....................................................................................................... 115 

High-value datasets ..................................................................................................................... 117 

Defining and measuring the impact of open data ....................................................................... 117 

Collaboration to create open data impact .................................................................................. 120 

7.3. Measuring reuse ...................................................................................................................... 121 

The reuse of datasets and reusers’ needs ................................................................................... 121 

Gathering and classifying reuse cases ......................................................................................... 122 

7.4. Created impact ........................................................................................................................ 123 

Governmental impact .................................................................................................................. 123 

Social impact................................................................................................................................ 127 

Environmental impact ................................................................................................................. 133 

Economic impact ......................................................................................................................... 136 

7.1. Overall performance on the impact dimension 
In 2024, the impact dimension is the third most mature dimension of the ODM assessment, with the 
EU-27 scoring 80 % on average (Figure 16). Maturity in this dimension has grown during 2022–2024, 
increasing by 6 percentage points (pp) between 2022 and 2023 and by 4 pp between 2023 and 2024. 
This  increase  at  the  dimension  level  has  been  driven  by  improvements  in  all  three  underlying 
indicators. Like the dimension overall, the indicators have demonstrated stable growth during 2022–
2024, with the ‘measuring reuse’ indicator and the ‘strategic awareness’ indicator reaching 88 %, an 
increase of 7 pp and 5 pp on 2023, respectively., and the ‘created impact’ indicator reaching 75 % (an 
increase of 3 pp on 2023). The ‘measuring reuse’ indicator has grown the most since 2023, highlighting 
countries’ efforts to set up methodologies for collecting and classifying reuse cases and to enhance 
activities aimed at understanding reuser requirements. 

In  terms  of  individual  country  performance,  11  countries  reported  performing  all  the  activities 
investigated in the questionnaire, scoring 100 % on this dimension (Figure 17). Denmark and Ireland 
followed closely, reaching a nearly perfect score of 97 % and scoring 100 % on the ‘strategic awareness’ 
indicator.  Ukraine  is  the  only  non-EU country  to  have  scored 100 %  on this  dimension.  Overall, 18 
countries scored above the EU average of 80 %. 

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Figure 16: The EU-27 average score on the impact dimension has risen steadily during 2022–2024 

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Figure 17: Twenty-two participating countries improved their score on the impact dimension in 2024. 
(EFTA: European Free Trade Association; YoY: year-on-year). 

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Highlight from France – measuring the impact of open data 
Measuring the impact of open data presents a challenge, primarily due to the lack of a standardised 
definition of open data impact and the difficulty of quantifying the effects of open data reuse. To 
address this, many countries have developed standardised frameworks that combine qualitative and 
quantitative indicators to make the impact of open data more tangible. In several instances, these 
national frameworks have drawn inspiration from, or been aligned with, efforts undertaken at the 
EU level, particularly through initiatives like data.europa.eu. 

In France, the data.gouv.fr team conducted an extensive impact survey in 2023 to measure how 
open data influences various sectors. The survey was guided by a methodology developed in France 
for  impact  measurement,  which  was  inspired  by  EU-level  work,  specifically  the  indicators  for  an 
open data impact assessment framework. This framework is structured to measure the effects of 
open  data  on multiple  dimensions,  including  governmental, environmental,  social  and  economic 
impacts. The two main components of the framework are as follows. 

•  Outputs.  The  study  measured  indicators  like  the  number of  datasets,  views,  downloads, 

reuses and discussions in 2023, helping to quantify data usage and engagement. 

•  Outcomes.  Reuse  cases  were  selected  from  the  data.gouv.fr  reuse  catalogue,  the 
beta.gouv.fr platform for digital public services, and research publications. These cases were 
chosen based on their potential impact, the availability of information and their relevance 
across the four impact categories. 

For  each  use  case,  the  survey  team  analysed  the  specific  impacts  of  data  reuse,  sometimes 
conducting interviews with the creators to better understand the services and benefits. The findings 
are presented in a paper that can be downloaded from data.gouv.fr. 

Read more about this trend in Section 7.2. 

Latvia (+ 21 pp), Croatia (+ 17 pp), Serbia (+ 16 pp), and Greece (+ 16 pp) are countries that showed 
the most significant year-on-year improvements in the impact dimension. Greece’s improved maturity 
relates  primarily  to  large  increases  in  the  ‘strategic  awareness’  and  ‘measuring  reuse’  indicators, 
because Greece now reports having set up monitoring mechanisms to collect and classify reuse cases. 
Like  many  countries,  Greece  has  launched  several  initiatives  to  monitor  open  data  reuse,  such  as 
actively involving academic institutions and the private sector in performing studies and analyses on 
open data usage. Additionally, efforts to increase public awareness are evident through the workshops, 
open dialogue sessions and hackathons that have been organised and that foster a culture of open 
data across different sectors. In future years, Greece can use these methods to gain a better overview 
of existing reuse cases and further improve its ODM maturity score. 

Highlight from Greece – the Open Data Hackathon 
An important practice observed in this year’s report is organising hackathons that involve numerous 
stakeholders to foster a culture of reusing open data across different sectors. 

For example, the Open Data Hackathon in Greece is an initiative to promote innovation using open 
data. The event encourages participants – developers, entrepreneurs, students and professionals –
to  create  prototype  applications  addressing  challenges  related  to  digital  transformation  across 
various sectors like energy, transport and real estate. It aims to foster collaboration between public 
and private sectors, create an innovation ecosystem and improve citizen services. The hackathon 
includes  a  mix  of  participants  from  different  fields  and  offers  mentorship,  with  prizes  and 
opportunities for those who design the best solutions. 

Read more about this trend in Section 7.2. 

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Latvia’s improved maturity is primarily driven by increased awareness of reuse cases that demonstrate 
open  data  impact,  particularly  in  the  environmental  and  economic  sectors.  The  country  has  made 
significant strides in monitoring environmental impact, a trend observed in several countries. Many 
countries,  including  Latvia,  have  also  introduced  initiatives  to  raise  public  awareness  of  open  data 
through official guidelines for both the public and government bodies. For example, Latvia’s ‘Open by 
default’  guideline  sets the standard at making all data open unless there is a strong reason not to, 
encouraging widespread data transparency and reuse. 

Highlight from Latvia – the transport website 
This  year,  a  generalised  trend  across  countries  is  the  reporting  of  reuse  cases  that  focus  on 
monitoring air and water quality, carbon dioxide emissions and the transport sector. For example, 
the website  transportdata.gov.lv  in  Latvia  serves  as a platform for open transport data. It offers 
various datasets, including traffic statistics, public transport schedules, infrastructure information 
and vehicle registration data. The website provides interactive maps to visualise transport datasets. 
Users can also find analytical tools they can use to explore and interpret the data more effectively. 
This functionality enhances the usability of the datasets, allowing for better insights and informed 
decision-making regarding transport planning and development. 

This  resource  is  useful  for  researchers,  developers  and  policymakers,  as  it  enables  informed 
decision-making, promotes transparency and encourages innovation in transport solutions. Users 
can access and utilise these datasets for analysis and application development, which benefits public 
services and urban planning. 

Read more about this trend in Section 7.4. 

7.2. Strategic awareness 

This  indicator  assesses  how  well  countries  define  the  reuse  and  impact  of  open  data  and  their 
readiness to measure impact using monitoring systems and research methods, particularly for HVDs. 
It examines the actions taken to generate open data impact. In essence, strategic awareness involves 
establishing the essential foundations needed to evaluate the effectiveness of open data initiatives. 

Definition of open data reuse 

In general, open data reuse refers to using public sector information for purposes other than those for 
which  it  was  originally  created.  Table 52  presents  an  overview  of  how  countries  responded  to  the 
questions on this topic. 

Table 52: Countries’ responses to questions on definition of open data reuse 

Do you have a definition of open data reuse in your country? 

EU-27 

EFTA 

Like in 2023, 26 Member States (96 %), all except Finland, report having a definition 
of open data reuse.  

Iceland and Norway report having a definition of open data reuse. This has remained 
stable since 2023. 

Candidate 

Albania, Serbia and Ukraine report having a definition of open data reuse. This is the 
same as in 2023. 

(Question I1) 

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The definition of open data reuse varies across countries. Commonalities exist, such as the emphasis 
on reusing public data for a purpose other than the originally intended one and enabling innovation 
through  the  development  of  applications,  analyses  or  services  that  benefit  the  public.  However, 
differences emerge in the legal frameworks, the scope of data included and the conditions of use. For 
example, Ireland’s definition of reuse follows the open data directive, defining it as the use of public 
sector documents by individuals or legal entities. Data is considered open if anyone can freely use, 
reuse and redistribute it, subject to minimal conditions like attribution. 

‘Public information contained in documents communicated or published by the administrations 
mentioned in the first paragraph of Article L. 300-2 may be used by any person who wishes to do 
so for purposes other than those of the public service mission for which the documents were 
produced or received’ 

France, Code of Relations between the Public and the Administration 

Some countries stress creative and open reuse, while others highlight specific legal guidelines tied to 
national or EU directives. For example, in Slovakia, the reuse of open data is primarily defined as the 
creative  use  of  open  data  by  various  sectors,  including  non-governmental  organisations  and 

‘The  use  by  natural  or  legal  persons  of  documents  held  by  public  administrations  or  bodies 
governed by public law for commercial purposes or for non-commercial purposes other than the 
institutional  purposes  for  which  the  documents  were  produced,  with  the  exception  of  the 
exchange of documents between public administrations’ 

Italy, Legislative Decree 200 of 8 November 2021 transposing the open data directive 

universities, to generate new solutions like applications, analyses or software, improving transparency, 
efficiency and innovation. 

Countries sometimes include specific qualifications in their definitions. For example, Bulgaria explicitly 
excludes the internal exchange of documents within public bodies from its definition. Countries also 
sometimes link their definition to multiple frameworks. For instance, Austria noted that reuse is guided 
by the principles of open government and governed by the Creative Commons licence CC BY 4.0. 

Monitoring open data reuse 

Monitoring how open data is reused and encouraging public bodies to track the reuse of their own 
datasets can help inform strategies to enhance the reuse of open data. Table 53 presents an overview 
of how countries responded to the questions on this topic. 

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Table 53: Countries’ responses to questions on monitoring open data reuse 

Are there any processes in place to 
monitor the level of reuse of your 
country’s open data? 

Are there any activities in place to 
encourage public bodies to monitor the 
reuse of their own published data? 

EU-27 

EFTA 

25 Member States (93 %), all except 
Croatia and Finland, report having 
processes in place to monitor the level 
of reuse. 

All three participating EFTA countries 
report having processes in place to 
monitor the level of reuse. Switzerland 
is the latest country to report doing 
this.  

23 Member States (85 %) report a strong 
focus on encouraging public bodies to 
monitor data reuse. This represents a two-
country increase compared with 2023, with 
Finland and Greece being the latest 
additions. 

Iceland and Switzerland report 
encouraging public bodies to measure the 
reuse of their own open datasets. 

Candidate  Like in 2023, Serbia and Ukraine report 

having processes in place to monitor 
the level of reuse. 

Like in 2023, Serbia and Ukraine report 
encouraging public bodies to measure the 
impact of open data.  

(Questions I2, I3) 

Countries approach monitoring the reuse of open data differently. Some countries have established 
frameworks and methodologies for tracking reuse, while others rely on informal feedback mechanisms 
or  community  contributions.  Many  countries  emphasise  the  importance  of  monitoring  to  improve 
open data quality and foster better services for users. 

Sweden noted that its monitoring of reuse involves collecting qualitative feedback through events and 
social  media.  Additionally,  the  national  data  portal  enables  users  to  share  their  reuse  cases  and 
provides download statistics as a measure of reuse. In Ukraine, monitoring of the level of open data 
reuse is supported by legislative mechanisms that focus on various aspects of open data development, 
including policy, capacity and quality. The Ministry of Digital Transformation maintains a catalogue of 
applications that utilise open data, updated regularly by users. 

Highlight from Slovenia – using Matomo to upgrade the monitoring framework 
Slovenia has made significant strides in monitoring the reuse of open data through its open data 
portal  (the  Open  Data  of  Slovenia  (OPSI)  portal).  It  is  upgrading  its  monitoring  framework  and 
utilising Matomo analytics. The Surveying and Mapping Authority (GURS) has agreements in place 
to  facilitate  monitoring.  Data  use  has  been  systematically  tracked  since  2005,  with  advanced 
analytics employed to understand user needs.  

Furthermore, countries implement various activities to encourage public bodies to monitor the reuse 
of  their  published  open  data.  These  activities  include  training  programmes,  workshops  and  direct 
communication  with  public  entities  to  foster  awareness  of  data  impact  and  to  encourage  them  to 
undertake  monitoring  practices.  Many  countries  have  established  frameworks  or  organised  events 
that bring together different stakeholders to share knowledge, tools and incentives to promote the 
effective monitoring of open data reuse. 

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For example, Cyprus has implemented a structured training programme for public sector information 
liaison  officers,  which  includes  a  module  dedicated to  understanding  and  measuring  the  impact  of 
open data. The open data team also supports events that highlight government-to-government reuse, 
fostering awareness among public sector bodies. Moreover, Finland’s operating model for sharing data 
includes specific guidance and instructions for public bodies on monitoring data reuse, thus helping to 
create a structured approach to assessing the impact of their published data. 

High-value datasets 

Having robust processes in place to monitor and measure the reuse of HVDs can support measures 
and strategies applying the implementing regulation on HVDs. Table 54 presents an overview of how 
countries responded to the questions on this topic.  

Table 54: Countries’ responses to the question on HVDs 

Does your country have processes in place to monitor and measure the level of reuse of HVDs? 

EU-27 

19 Member States (70 %) report having processes in place to monitor the reuse of 
HVDs. 

(Question I4) 

Non-EU countries were not surveyed on this question, since Commission Implementing Regulation (EU) 2023/138 
on HVDs applies only to EU Member States. 

Processes for monitoring and measuring the reuse of HVDs often involve using national portals for data 
management, consulting legislative requirements on metadata provision and implementing structured 
reporting mechanisms. For example, in Hungary, government bodies monitor the availability and reuse 
of HVDs primarily through the national open data portal. Act CI of 2023 mandates that all public bodies 
provide metadata to the national portal, facilitating oversight. The National Data Asset Management 
Agency serves as a central point for requests related to HVDs, and, from 2026, the agency will provide 
its own HVDs. 

As  another  example,  Romania’s  methodological  guidelines  include  templates  for  yearly  reporting, 
mandating  institutions  to  monitor  the  reuse  of  HVDs  through  various  approaches.  This  structured 
approach  aims  to  ensure  comprehensive  tracking  of  data  usage  and  compliance  with  open  data 
standards. 

Furthermore, several countries are using the same processes to monitor HVDs as they do for other 
types of datasets. However, as noted by Greece, in some cases, datasets must still be denoted as HVDs 
before their impact can be fully monitored. 

Defining and measuring the impact of open data 

There is no universal definition of open data impact, particularly since open data can have an impact 
in diverse domains. Specifying what the impact of open data means in the national context can enable 
better measurement of the effectiveness of policies and other implementation measures in achieving 
the envisaged impact. Table 55 presents an overview of how countries responded to the questions on 
this topic. 

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Table 55: Countries’ responses to questions on defining and measuring the impact of open data 

Has your government specified what 
‘impact of open data’ means? 

EU-27 

25 Member States (93 %) report having 
a definition of open data impact, with 
Greece being the latest addition to the 
group. 

Do you have a methodology in place to 
measure the impact of open data in your 
country? 

23 Member States (85 %) report having a 
methodology in place to measure the 
impact of open data, with Greece and 
Hungary being the latest countries to 
report having such a methodology. 

EFTA 

All three participating EFTA countries 
report having a definition of open data 
impact. 

Norway and Switzerland report having a 
methodology in place to measure the 
impact of open data. 

Candidate  Albania, Serbia and Ukraine report 

having a definition of open data impact, 
with Serbia being the latest addition. 

Albania, Serbia and Ukraine report having 
a methodology in place to measure the 
impact of open data. 

(Questions I5 and I6) 

Countries have made various attempts to measure the impact of open data. These efforts are usually 
integrated into a general national strategy on open data and have as their basis the methodological 
collection of open data through a variety of sources and the analysis of this data through quantitative 
indicators. While some countries apply the same methodology to all types of open data, others use a 
specific methodology according to the category of data they are dealing with. 

Highlight from Spain – the Aporta initiative 
Spain’s approach to defining the impact of open data is framed within the Aporta initiative, which 
serves as the country’s national strategy on open data. There follows a detailed breakdown. 

1.  Current definition within the Aporta initiative 

According to the Aporta initiative strategy document (p. 5), impact is understood as: ‘any positive 
effect or benefit, obtained directly or indirectly for individuals, communities or society, which occurs 
over a certain period and results from the development of various activities characterised by the 
use  of  open  data  toward  a  specific  goal’.  This  definition  encompasses  both  direct  and  indirect 
benefits and highlights that open data usage can have a long-term positive influence on different 
sectors of society. 

2.  Measuring impact 

In  practice,  Spain  considers  it  essential  to  evaluate  open  data’s  impact  using  both  quantitative 
measures (e.g. data usage statistics, number of datasets released) and qualitative measures (e.g. 
societal and community benefits). This dual approach helps capture the volume of data reused and 
its broader effects on society, such as transparency, innovation and public service improvements. 
For more context, see the discussion on the Aporta blog ‘Measuring the impact of open data’. 

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3.  Future developments 

The  new  national  open  data  strategy,  which  is  currently  in  development,  seeks  to  refine  this 
approach even further. It recognises the need to evolve from a largely quantitative framework to a 
more  comprehensive  approach that incorporates qualitative  measures of open data impact. The 
goal is to create a more nuanced and accurate understanding of how open data benefits society 
beyond basic metrics. For the latest updates, refer to the draft of the new strategy. 

With regard to monitoring the  reuse of open data,  Sweden  noted the  importance  of a user-driven 
process for opening up data and maintaining continuous user dialogues. It collects insights into the 
reuse of open data through the following efforts. 

•  Seminars. Public events where stakeholders discuss the importance and effects of open data. 
•  National projects. These aim to boost the use of open and shared data. 
•  Dialogues  and  networking.  Engagement  with  public  organisations  that  release  open  data 

helps track reuse and impact. 

•  Social media groups. Monitoring relevant groups to gain insights into how data is used. 
•  Open data portals. Public bodies, including at the local level, monitor application programming 

interface usage and apply web analytics to understand how the data is being reused. 

Taking a different approach, Italy has incorporated methodologies for measuring the impact of open 
data  into  broader  ICT-related  initiatives.  The  three-year  plan  for  ICT  in  the  public  administration 
includes specific actions on data and open data, which are measured annually. The plan’s monitoring 
platform  provides  insights  into  the  extent  of  open  data  usage  and  its  impact  on  digital  services. 
Progress on the plan is monitored through a dedicated portal, where relevant data is available in an 
open format. By analysing the fulfilment of objectives set in the plan, the government can measure 
the influence of open data on various sectors. This approach provides a structured way to measure 
both  the  development  and  the  reuse  of  open  data,  focusing  on  real-world  applications  and  digital 
services created through open data access. 

Highlight from Poland – the impact of open data on entrepreneurship 
Poland has developed a methodology for a nationwide study on the size and characteristics of the 
public data reuse market in Poland. This has enabled it to define key parameters for assessing the 
impact  of  open  data  on  entrepreneurship.  With  some  modifications  and  further  testing,  these 
parameters  can  be  adapted  to  measure  the  effects  of  open  data  on  other  economic  and 
sociocultural areas, whether for specific social groups or society as a whole. 

Poland  conducted  the  study  using  a  quantitative  survey  through  computer-assisted  telephone 
interviews with representatives of companies involved in data management or analysis, or those in 
other types of companies who were best informed about the company’s data usage. The study team 
employed a stratified random sampling method to ensure representativeness, accounting for four 
business size categories and regional divisions across provinces. This approach meant that they were 
able to generalise their findings to the entire population of entrepreneurs. A total of 600 interviews 
were conducted. 

Moving  forward,  Poland  plans  to  apply  this  methodology,  with  necessary  adjustments,  to  other 
social groups, enabling it to test and refine open data impact indicators. Thus, it views this survey 
among entrepreneurs as a pilot for a broader framework to measure the impact of open data. 

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Collaboration to create open data impact 

One  way  to  create  impact  with  open  data  is  for  the  public  sector  to  work  together  with  other 
stakeholders.  Table 56  presents  an  overview  of  how  countries  responded  to  the  questions  on  this 
topic. 

Table 56: Countries’ responses to questions on collaboration to create open data impact 

Is there collaboration between government and civil society or academia to create open data impact 
in your country? 

EU-27 

EFTA 

25 Member States (93 %) report that they ensure collaboration between government 
and civil society or academia to create open data impact. Unlike in 2023, Germany 
and Malta did not report doing this in 2024. 

All three participating EFTA countries ensure collaboration between different parties 
to create open data impact. 

Candidate 

All four participating candidate countries ensure collaboration between different 
parties to create open data impact. 

(Question I7)  

Collaboration among a diverse range of stakeholders is essential for maximising the benefits of open 
data. Fostering a robust open data culture and promoting a wide array of data collection efforts can 
increase overall impact. This year, numerous countries reported improved collaboration between the 
private and public sectors and educational institutions. These partnerships have led to initiatives such 
as hackathons, webinars and other events aimed at encouraging the innovative reuse of open data 
across various fields. 

Highlight from Ireland – Open Data Engagement Fund 
The Irish 2023/2024 Open Data Engagement Fund is an initiative designed to enhance the use and 
accessibility of open data in Ireland. With a total funding pool of € 30 000, this programme invites 
applications from a broad range of participants – including individuals, businesses, public bodies and 
civil-society groups – for support for projects that promote innovative uses of datasets available on 
the national open data portal. The fund aims to foster transparency, drive public engagement and 
encourage  collaboration  across  various  sectors  by  funding  outreach  activities,  application 
development and research that illustrates the potential benefits of open data. 

The  initiative  emphasises  the  strategic  goal  of  maximising  the  impact  of open  data  in  improving 
public service  efficiency and informed decision-making. By  prioritising projects that demonstrate 
tangible benefits, the fund seeks to raise awareness about the available datasets and encourage the 
development of solutions that address current societal challenges. 

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7.3. Measuring reuse 

This indicator assesses the actions taken to map reuse, the methodologies for collecting and classifying 
reuse cases, and the activities performed to understand the requirements of reusers. 

The reuse of datasets and reusers’ needs 

Conducting activities to document which open datasets are reused and how, and what the needs of 
reusers are, can help public  bodies devise approaches to further stimulate the reuse of open data. 
Table 57 presents an overview of how countries responded to the questions on this topic. 

Table 57: Countries’ responses to questions on reuse of datasets and reusers’ needs 

Have any public bodies in your country 
launched or performed any activities in 
the past year to understand which 
(open) datasets are reused and how? 

EU-27 

26 Member States (96 %), all except 
Malta, report performing activities to 
understand which datasets are being 
reused and how. 

Have any public bodies in your country 
launched or performed any activities in the 
past year to better understand reusers’ 
needs in order to further stimulate the 
reuse of open data? 

24 Member States (89 %) report that public 
bodies perform activities to better 
understand reusers’ needs. This is an 
increase of one country, Romania, from 
2023. 

EFTA 

All three participating EFTA countries 
report performing activities to 
understand which datasets are being 
reused and how. 

Candidate  All participating candidate countries, 

except Bosnia and Herzegovina, report 
performing activities to understand 
which datasets are being reused and 
how. 

Norway and Switzerland report that public 
bodies perform activities to better 
understand reusers’ needs.  

Serbia and Ukraine report performing 
activities to better understand reusers’ 
needs. 

(Questions I8 and I9) 

The most common activity performed to understand how datasets are reused is running interviews or 
workshops with reusers (25 Member States; 93 %), followed by conducting surveys (19 Member States; 
70 %)  and  using  web  analytics  (18  Member  States;  67 %).  Similarly,  the  most  common  activity 
performed to understand reuser needs was feedback sessions with portal users (21 Member States; 
78 %),  followed  by  sentiment  analysis  of  social  media  (13  Member  States;  48 %).  For  example, 
Finland’s  Helsinki Region Infoshare (HRI) conducts  an  annual user  survey  to gather feedback  on its 
services.  Additionally,  a  separate  survey  was  conducted  in  2024  among  employees  of  the  City  of 
Helsinki to assess their awareness of and experiences with HRI, revealing that, while few knew about 
HRI, those who did had had positive experiences. 

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Gathering and classifying reuse cases 

Public bodies can develop systematic ways of gathering and classifying reuse cases to understand how 
datasets are reused and what impact they can potentially create.  Table 58 presents an overview of 
how countries responded to the questions on this topic. 

Table 58: Countries’ responses to questions on gathering and classifying reuse cases 

EU-27 

EFTA 

Have any public bodies in your country 
developed any systematic way of 
gathering reuse cases? 

Are there any public bodies in your country 
that have developed a systematic way of 
classifying the gathered reuse cases? 

24 Member States (89 %) report that 
public bodies have developed 
systematic ways of gathering reuse 
cases. This is an increase of three 
countries, Greece, Latvia and Romania, 
from 2023.  

Norway and Switzerland report that 
public bodies have developed 
systematic ways of gathering reuse 
cases. 

18 Member States (67 %) report that public 
bodies have developed systematic ways of 
classifying reuse cases. This is an increase 
of three countries, Greece, Portugal and 
Slovakia, from 2023. 

Norway and Switzerland report that public 
bodies have developed systematic ways of 
classifying reuse cases.  

Candidate  Serbia and Ukraine report that public 

bodies have developed systematic ways 
of gathering reuse cases. 

Serbia and Ukraine report that public 
bodies have developed systematic ways of 
classifying reuse cases. 

(Questions I10 and I11) 

In 2024, the emphasis on data  reuse  has  increased, as indicated by the development of innovative 
strategies  that  promote  collaboration  and  community  involvement.  Key  trends  include  systematic 
documentation  of  reuse  cases  through  user  submissions  and  interviews,  centralised  portals 
showcasing  best  practices  and  the  implementation  of  user-driven  tagging  systems  for  easier 
navigation. These initiatives reflect a growing recognition of data reuse as a vital driver of innovation 
and collaboration across various sectors. 

For example, Cyprus outlined its multifaceted approach to gathering reuse cases in the country’s latest 
impact survey. The mechanism includes a range of activities designed to systematically identify and 
collect reuse cases while fostering a more engaged and collaborative data ecosystem. These activities 
include: 

•  annual desktop studies that actively search for and document examples of data reuse; 
•  an online submission form through which users can submit their applications and reuse cases, 

• 

• 

which are then showcased on various data portals; 
interviews  with  key  data  reusers,  providing  insights  into  how  data  is  being  utilised  and 
repurposed in innovative ways; 
leveraging social media groups to actively encourage discussions and sharing of reuse cases 
among the community. 

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In Hungary, a central function of the national open data portal is the collection and presentation of 
applications  and  visualisations  that  showcase  data  reuse.  This  process  involves  establishing 
cooperation agreements with public authorities, from which the agency gathers examples of how open 
data  is  being  reused.  By  facilitating  the  documentation  of  such  cases,  the  portal  highlights  best 
practices  and  successful  applications,  creating  a  valuable  resource  for  both  public  and  private 
stakeholders.  The  portal  also  provides  a  platform  where  reuse  examples  are  regularly  published, 
ensuring transparency and promoting further reuse of data. 

Highlight from Luxembourg – the Luxembourgish open data platform 
To  organise  reuse  cases  on  its  portal,  Luxembourg  uses  thematic  categories  and  tags  to  make 
navigating and identifying relevant examples easier. Each reuse case is linked to a specific topic, such 
as  agriculture,  economy  and  finance,  or  environment  and  climate.  This  enables  users  to  browse 
reuse cases by sector of interest. Additionally, the portal supports user-generated tags, providing 
more flexibility in how reuse cases are classified. This tagging system enables users to add relevant 
keywords that further describe the nature of the reuse, creating a more detailed and customisable 
search  experience.  By  combining  these  thematic  categories  with  user-driven  tags,  Luxembourg 
ensures  that  the  reuse  cases  are  systematically  classified  and  easily  searchable  by  the  broader 
public. 

7.4. Created impact 

The ‘created impact’ indicator assesses the presence of data that provides evidence on the impact that 
open data is creating in a country (e.g. in the form of research studies, statistics or impact assessments) 
and the presence of reuse case examples (e.g. data applications, digital services or analysis used for 
decision-making). The  ‘created  impact’  indicator  is evaluated  in  four  impact  domains:  government, 
society, the environment and the economy. 

Governmental impact 

The ‘governmental impact’ subindicator evaluates the presence of research data on open data impact 
and reuse cases that pertain to (1) the efficiency and effectiveness of the government in delivering 
public services, (2) the transparency and accountability of public administrations, (3) the policymaking 
process and (4) decision-making processes in public administrations. Table 59 presents an overview of 
how countries responded to the questions on this topic. 

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Table 59: Countries’ responses to questions on governmental impact 

Is there data 
on the impact 
created by 
open data on 
governmental 
challenges? 

Is there a reuse 
case example 
related to the 
efficiency and 
effectiveness of 
government 
operations? 

Is there a reuse 
case example 
related to the 
transparency 
and 
accountability of 
public 
administrations? 

Is there a 
reuse case 
example 
related to the 
policymaking 
process? 

Is there a reuse 
case example 
related to 
decision-making 
processes in 
public 
administrations? 

EU-27 

EFTA 

17 Member 
States (63 %) 
report having 
such data 
available. This 
is an increase 
of three 
countries 
from 2023. 

Norway 
reports having 
such data 
available.  

23 Member 
States (85 %) 
gave an example 
of a reuse case 
on this topic. 

24 Member 
States (89 %) 
gave an example 
of a reuse case 
on this topic. 

21 Member 
States (78 %) 
gave an 
example of a 
reuse case on 
this topic. 

21 Member 
States (78 %) 
gave an example 
of a reuse case on 
this topic. 

Like in 2023, all 
three 
participating 
EFTA countries 
gave an example 
of a reuse case 
on this topic. 

All three 
participating 
EFTA countries 
gave an example 
of a reuse case 
on this topic, 
with Iceland 
being the latest 
addition. 

All three 
participating EFTA 
countries gave an 
example of a 
reuse case on this 
topic, with 
Iceland being the 
latest addition. 

All three 
participating 
EFTA 
countries gave 
an example of 
a reuse case 
on this topic, 
with Iceland 
being the 
latest 
addition. 

Candidate 

Ukraine 
reports having 
such data 
available. 

Serbia and 
Ukraine gave an 
example of a 
reuse case on 
this topic. 

Serbia and 
Ukraine gave an 
example of a 
reuse case on 
this topic. 

Serbia and 
Ukraine gave 
an example of 
a reuse case 
on this topic. 

Serbia and 
Ukraine gave an 
example of a 
reuse case on this 
topic. 

(Questions I12, I13, I14, I15 and I16) 

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The following are some interesting reuse cases reported on this topic. 

Reuse case example from Serbia – the Open Budgets platform 
Subdomain 

Transparency and accountability. 

Functioning and purpose 

The Open Budgets platform is an open data portal providing access to Serbia’s detailed public budget 
information.  It  is  a  government  initiative  aimed  at  promoting  financial  transparency  by enabling 
users to explore how public money is being allocated and spent. The platform centralises data from 
around 200 national and local budgets, making it easily accessible and understandable for a wide 
audience. The portal enables users to: 

•  view and download budgetary data in various formats (e.g. charts, tables, raw data); 
•  explore  different  levels  of  budgetary  information,  from  overall  national  expenditures  to 

specific sectoral and municipal allocations; 
track historical trends and changes in budget planning and execution. 

• 

Once  a  specific  region  is  selected,  the  user  can  delve  into  the  municipality’s  revenues  or 
expenditures. For example, Figure 18: Serbia’s Open Budgets platform.displays the expenditure for 
the municipality of Belgrade. Here, the user can see where the budget comes from, which areas it is 
allocated to and how it is spent. 

Figure 18: Serbia’s Open Budgets platform 

Target group 

The users target are very diverse. The website provides instructions for using the platform in the 
form of video tutorials for citizens and local self-government units. 

Datasets used 

The datasets used include national budget data, local government budget data, historical budget 
data and data on sector-specific spending. All users who have created a visualisation, application or 
other use case that could enhance the user experience or the data provided by the portal are invited 
to contact the open data team at opendata@ite.gov.rs. 

Impact 

The platform plays a transformative role in governance by enhancing public oversight and fostering 
informed  policy  discussions.  By  providing  accessible  budget  data,  it  empowers  citizens  and  civil 
society  to  monitor  government  spending,  promoting  accountability  and  responsible  fiscal 
management. This transparency builds trust between citizens and the government, and it enables 
researchers and policymakers to engage in meaningful discourse on fiscal policies. By helping them 

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to  understand  budget  allocations,  the  platform  encourages  citizens  to  participate  actively  in 
democratic processes, advocating for effective governance, thus ensuring that their voices are heard 
in budgetary decision-making. 

Reuse case example from Spain – the digital twin of Denia 
Subdomain 

Decision-making processes in public administrations. 

Functioning and purpose 

The city of Denia, in Alicante, Spain, has developed a digital twin, a virtual model of the city that 
integrates real-time data to help the local government analyse patterns and trends in tourism. This 
tool uses public datasets to simulate Denia’s physical environment and tourism dynamics, enabling 
city  planners  to  assess  accessibility,  plan  new  infrastructure  and  make  data-driven  decisions  to 
manage tourism more effectively. 

The  digital  twin  provides  detailed  insights  into  tourists’  movement,  behaviour  and  spending 
patterns,  making  it  possible  to  better  allocate  resources  and  improve  public  services.  By 
understanding  where  national  and  international  visitors  concentrate,  the  model  helps  the  local 
government  and  businesses  optimise  services,  promote  areas  and  forecast  demand  for  public 
amenities. The primary goal of Denia’s digital twin is to improve the city’s tourism management by: 

identifying patterns and trends in tourist behaviour; 

• 
•  assessing the accessibility of tourism resources, such as infrastructure, accommodation and 

tourist attractions; 

•  planning and optimising new tourism-related infrastructures based on data-driven insights; 
•  analysing visitor movement, traffic and spending habits to make more informed decisions 

about resource allocation and service provision; 

•  enhancing the overall tourism experience while optimising city planning. 

Target group 

The target groups for the digital twin initiative include local government officials, tourism agencies, 
civil engineers, researchers and citizens. 

Datasets 

The digital twin of Denia relies on several key datasets to construct and update its model: 

•  Directorate-General  of  Cadastre  dataset.  The  dataset  provides  detailed  information  on 
buildings  and  property  layouts  in  Denia,  which  is  useful  for  urban  mapping  and 
infrastructure analysis. 

•  PNOA-LiDAR dataset. Light detection and ranging technology is used to create detailed 3D 

models of Denia’s landscape, giving insights into topography and urban structures. 

•  Tourism accommodation data from the open data portal of the Valencian Community. The 

dataset lists hotels and accommodation, helping to map tourism hotspots. 

Impact 

Reusing open data significantly improves decision-making in the public sector, especially in tourism 
management and infrastructure planning. By utilising a digital twin, Denia can monitor tourist flow 
and  analyse  traffic  and  spending  patterns,  leading  to  better  management  of  tourism  resources, 
transport,  healthcare  and  waste  management.  Ultimately,  informed  resource  allocation  and 
promotion  of  key  areas  can  stimulate  economic  growth,  attract  new  businesses  and  enhance 
services for both residents and visitors, fostering a more sustainable and vibrant community. 

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Social impact 

The  ‘social  impact’  subindicator evaluates the  presence  of  research  data on open  data  impact  and 
reuse cases that pertain to (1) marginalised groups and inequality, (2) urban housing, (3) health and 
well-being and (4) education and skills. Table 60 presents an overview of how countries responded to 
the questions on this topic. 

Table 60: Countries’ responses to questions on social impact 

Is there a 
reuse case 
example 
related to 
marginalised 
groups and 
inequality? 

19 Member 
States (70 %) 
gave an 
example of a 
reuse case on 
this topic. 

Is there a reuse 
case example 
related to 
urban housing? 

Is there a 
reuse case 
example 
related to 
health and 
well-being? 

Is there a reuse 
case example 
related to 
education and 
skills? 

22 Member 
States (81 %) 
gave an 
example of a 
reuse case on 
this topic. 

23 Member 
States (85 %) 
gave an 
example of a 
reuse case on 
this topic. 

21 Member 
States (78 %) 
gave an 
example of a 
reuse case on 
this topic. 

EU-27 

Is there data 
on the impact 
created by 
open data on 
social 
challenges? 

14 Member 
States (52 %) 
report having 
such data 
available. 
Belgium, 
Finland, Spain 
and Slovenia 
are the latest 
additions. 

EFTA 

Norway 
reports having 
such data 
available. 

Norway gave 
an example of 
a reuse case 
on this topic. 

Norway and 
Switzerland 
gave an 
example of a 
reuse case on 
this topic. 

Norway and 
Switzerland 
gave an 
example of a 
reuse case on 
this topic. 

Iceland and 
Switzerland 
gave an 
example of a 
reuse case on 
this topic, with 
Iceland being 
the latest 
addition. 

Candidate  Serbia and 

Ukraine 
report having 
such data 
available. 
Serbia is the 
latest 
addition. 

Serbia and 
Ukraine gave 
an example of 
a reuse case 
on this topic. 

Serbia and 
Ukraine gave 
an example of a 
reuse case on 
this topic. 

Serbia and 
Ukraine gave 
an example of 
a reuse case 
on this topic. 

Serbia and 
Ukraine gave 
an example of a 
reuse case on 
this topic. 

(Questions I17, I18, I18, I20 and I21) 

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The following are some interesting reuse cases reported on this topic. 

Reuse case example from Denmark – the Integration Barometer 
Subdomain 

Marginalised groups and inequality. 

Functioning and purpose 

The Integration Barometer is an online tool developed by the Danish Ministry of Immigration and 
Integration  to  track  the  progress  of  foreigners’  integration  into  Danish  society.  It  monitors  key 
metrics related to social, economic and cultural integration. The platform collects and presents data 
across nine core indicators at both the national and municipal levels, providing a comprehensive 
view of how well integration policies are working in various regions of Denmark. 

The barometer serves as a transparent, data-driven resource for policymakers, researchers and the 
public, enabling them to understand how immigrants are integrating into Danish society and where 
additional efforts may be needed. The main objectives of the Integration Barometer are to: 

•  monitor and track the success of integration initiatives across Denmark; 
•  provide a clear and actionable overview of the integration process for foreigners in areas 

such as employment, education, social engagement and health; 

•  enable policymakers to identify areas where integration efforts are succeeding and where 

progress is lacking, helping to shape targeted policies and interventions; 

•  promote transparency and accountability by making integration data publicly available to 

all stakeholders. 

Target group 

The  target  groups  for  the  integration  barometer  include  policymakers  and  government  agencies 
responsible  for  immigration  and  integration  policies  at  both  the  national  and  municipal  levels. 
Municipal authorities can monitor integration trends in their areas and adjust policies as needed. 
Citizens and immigrant communities benefit from access to this data, which helps them to gain an 
understanding of progress on integration in communities across Denmark. 

Datasets 

The Integration Barometer compiles data from multiple national and municipal sources to monitor 
nine key indicators of immigrant integration in Denmark. These indicators include the employment 
rate, comparing the job status of immigrants with that of the native population; education levels, 
focusing on enrolment and attainment in primary, secondary and higher education; and language 
proficiency, which measures immigrants’ ability to learn and use Danish. Additionally, the barometer 
tracks  housing conditions, health outcomes, access  to healthcare  services,  and political and civic 
participation  in  local  and  national  processes.  It  also  monitors  crime  rates  within  immigrant 
communities, assesses social inclusion to determine how accepted immigrants feel in Danish society 
and evaluates experiences of discrimination across various aspects of life. 

Impact 

The  Integration  Barometer  has  a  significant  impact  on  immigrant  integration  in  Denmark  by 
promoting data-driven policy decisions. It enables decision-makers to identify both successful areas 
and  those  needing  improvement,  fostering  the  development  of  targeted  integration  policies 
Additionally, the barometer enhances public understanding of the complexities of integration and 
the progress made, contributing to more informed public debates. Ultimately, the insights provided 
support organisations and initiatives that seek to assist immigrant communities and promote more 
inclusive and effective integration efforts. 

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Reuse case example from Lithuania – the Patient Waiting Time Dashboard 
Subdomain 

Health and well-being. 

Functioning and purpose 

The Patient Waiting Time Dashboard is an online tool developed by the Lithuanian Ministry of Health 
(
in 

the  State  Patient  Fund  and 

the  State  Data  Agency 

collaboration  with 

Figure 19). This dashboard uses real-time data from the advance patient registration information 
system  to  monitor  and  display  waiting  times  for  medical  appointments  across  the  country.  It 
provides an easy-to-use interface  enabling health administrators, policymakers and the public to 
track queue dynamics, identify bottlenecks in the healthcare system and assess the effectiveness of 
any  measures  aimed  at  reducing  patient  waiting  times.  The  tool  is  part  of  an  effort  to  improve 
transparency  and  efficiency  in  Lithuania’s  healthcare  system  by  making  relevant  data  readily 
accessible to all stakeholders. The Patient Waiting Time Dashboard was created with the aims of: 

•  monitoring  patient  waiting  times  for  doctor  appointments  in  real-time  across healthcare 

• 

facilities in Lithuania; 
identifying problematic areas where waiting times are disproportionately long, thus helping 
the health authorities to target resources more effectively; 

•  providing 

insights 

into  how 

implemented  measures  (e.g.  policy  changes,  staffing 

• 

• 

adjustments) are affecting the efficiency of the healthcare system; 
improving the overall quality of healthcare services by enabling data-driven decision-making 
and planning; 
increasing transparency and enabling patients and the general public to stay informed about 
the state of healthcare accessibility. 

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Figure 19: The home page of the Patient Waiting Time Dashboard 

Target group 

The Patient Waiting Time Dashboard is a valuable tool for various stakeholders in the healthcare 
system.  It  helps  policymakers  and  government  authorities  to  manage  healthcare  services  and 
implement policies to reduce waiting times. Healthcare providers and administrators can monitor 
and  enhance  patient  scheduling  and  appointment  systems. Patients  benefit  from  accessing  real-
time  information  on  waiting  times  at  different  facilities,  which  enables  them  to  make  informed 
healthcare choices. Researchers can use the data for studies on healthcare efficiency and resource 
allocation. 

Datasets 

The Patient Waiting Time Dashboard integrates multiple datasets to provide comprehensive insights 
into  patient  waiting  times.  The  datasets  used  are  accessible  via  Lithuania’s  open  data  platform: 
Dataset on waiting times, Healthcare facility data, and Policy effectiveness tracking. 

Impact 

The Patient Waiting Time Dashboard enhances healthcare accessibility by identifying long waiting 
times  and  bottlenecks,  enabling  the  Ministry  of  Health  to  take  targeted  actions  to  improve 
situations. It facilitates data-driven policymaking, helping the health authorities to make timely and 
informed decisions on resource allocation and staffing. The dashboard increases transparency and 
public trust by providing patients with accurate, up-to-date waiting time information, empowering 
better healthcare choices. It also promotes accountability, enabling hospitals and providers to be 
held accountable for their efficiency while tracking improvements. Overall, it improves planning and 
resource allocation by offering a clear picture of patient flow and facility usage, guiding investment 
to where it is most needed. 

Reuse case example from Ukraine – an online resource on wartime higher education 
Subdomain 

Education and skills. 

Functioning and purpose 

Higher Education in Wartime is an online platform developed using open data from the Unified State 
Electronic Database on Education (Figure 20). This tool was designed to analyse and report on the 
state of higher education institutions in Ukraine during wartime. It leverages open data to provide 
a detailed overview of how universities and other educational establishments have been impacted 

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by  the  ongoing  conflict,  offering  insights  into  disruptions,  relocations  and  adjustments  made  to 
continue  providing  education  during  this  challenging  time.  The  resource  is  primarily  aimed  at 
journalists, researchers and educators interested in using open data to produce fact-based reports 
on education in Ukraine. The primary objectives of this project are to: 

•  provide  transparent,  data-driven  reports  on  how  the  war  in  Ukraine  has  affected  the 

country’s higher education system; 

•  highlight  the  challenges  faced  and  adaptations  made  by  universities  during  wartime, 
including relocations, changes in student enrolment and changes in access to educational 
resources; 

•  offer a reliable source of information for journalists and researchers covering education and 

• 

its intersection with conflict and crisis; 
support  public  awareness  and  policy  discussions  on  the  future  of  higher  education  in 
Ukraine during and after the conflict. 

Figure 20: Some of the interactive features of the platform Higher Education in Wartime 

Target group 

The  platform  serves  multiple  stakeholders  in  the  education  sector:  journalists,  researchers  and 
academics, education policymakers and students. 

Datasets 

The platform draws on the Unified State Electronic Database on Education, which includes data on 
institutions forced to relocate due to conflict, student enrolment figures reflecting wartime changes 
and  institutional  adaptation  insights  detailing  how  universities  manage  operations  and  support 
displaced  students.  These  datasets  are  publicly  available  through  Ukraine’s  open  data  initiative, 
providing a comprehensive view of the higher education landscape during the war. 

Impact 

The  platform  enables  fact-based  reporting  on  higher  education  in  wartime,  enhancing  public 
understanding of the crisis. It supports policy decisions by providing insights critical for designing 

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interventions  to  assist  universities  and  students.  Additionally,  it  raises  public  awareness  of  the 
challenges  faced  by educational  institutions  in  Ukraine,  informing  both  the  Ukrainian  public  and 
international  communities.  Finally,  the  resource  promotes  educational  continuity  by  showcasing 
successful  strategies  for  maintaining  education  during  disruption,  offering  valuable  lessons  for 
future crises. 

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Environmental impact 

The ‘environmental impact’ subindicator evaluates the presence of research data on open data impact 
and reuse cases that pertain to (1) biodiversity, (2) environmentally friendly cities, (3) climate change 
and connected disasters and (4) energy consumption and the switch to renewables. Table 61 presents 
an overview of how countries responded to the questions on this topic. 

Table 61: Countries’ responses to questions on environmental impact 

Is there data 
on the impact 
created by 
open data on 
environmental 
challenges? 

15 Member 
States (56 %) 
report having 
such data 
available. 
Denmark, 
Ireland, Latvia 
Portugal and 
Slovenia 
report this for 
the first time. 

Norway 
reports having 
such data. 

EU-27 

EFTA 

Is there a 
reuse case 
example 
related to 
biodiversity? 

Is there a reuse 
case example 
related to 
environmentally 
friendly cities? 

24 Member 
States (89 %) 
gave an 
example of a 
reuse case on 
this topic. 

24 Member 
States (89 %) 
gave an 
example of a 
reuse case on 
this topic. 

All three 
participating 
EFTA countries 
gave an 
example of a 
reuse case on 
this topic. 

All three 
participating 
EFTA countries 
gave an 
example of a 
reuse case on 
this topic. 

Candidate  Ukraine 

reports having 
such data. 

Serbia and 
Ukraine gave 
an example of 
a reuse case 
on this topic. 

Serbia and 
Ukraine gave an 
example of a 
reuse case on 
this topic. 

Is there a 
reuse case 
example 
related to 
climate 
change and 
connected 
disasters? 

23 (85 %) 
gave an 
example of a 
reuse case on 
this topic, 
with Hungary 
and Latvia 
being the 
latest 
additions. 

All three 
participating 
EFTA 
countries 
gave an 
example of a 
reuse case on 
this topic. 

Serbia and 
Ukraine gave 
an example 
of a reuse 
case on this 
topic. 

Is there a reuse 
case example 
related to 
energy 
consumption 
and the switch 
to renewables? 

24 Member 
States (89 %) 
gave an 
example of a 
reuse case on 
this topic. This 
is an increase of 
four countries, 
Belgium, 
Croatia, Finland 
and Latvia, 
from 2023. 

All three 
participating 
EFTA countries 
gave an 
example of a 
reuse case on 
this topic. 

Serbia and 
Ukraine gave 
an example of a 
reuse case on 
this topic. 

(Questions I22, I23, I24, I25 and I26) 

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The following are some interesting reuse cases reported on this topic. 

Reuse case example from Serbia – climate monitoring and grading system 
Subdomain 

Climate change and connected disasters. 

Functioning and purpose 

The climate monitoring and grading system is an initiative aimed at tracking progress in the fight 
against climate change while presenting information on the effects of climate change in the form of 
related disasters, such as rising sea levels and global warming. This project provides an overview of 
climate-related  data  and  assessments,  utilising  open  data  from  Norway  and  other  countries.  It 
incorporates  a  grading  system  that  encourages  the  achievement  of  green  results,  which  in  turn 
influences policy decisions regarding climate change mitigation and adaptation. The main objectives 
of this initiative include the following. 

•  Tracking climate  progress.  Monitoring  and  reporting  on  advancements  in  climate  action 

and their effectiveness in mitigating climate change. 

•  Disaster impact assessment. Evaluating and communicating the consequences of climate 

change, particularly related to environmental disasters like rising sea levels. 

•  Policy guidance.  Using the grading system as a benchmark for setting goals and shaping 

policies aimed at achieving sustainable and environmentally friendly outcomes. 

Target group 

The initiative targets several key stakeholders: policymakers and government officials, researchers 
and academics, environmental organisations and non-governmental organisations, and the general 
public, who can use the data to enhance their understanding of climate change issues and engage 
with the measures being taken to address them. 

Datasets used 

The project utilises a variety of open datasets, including Norwegian climate data related to climate 
indicators,  emissions  and  environmental  assessments;  international  climate  data  from  other 
countries,  providing  comparative  insights  into  global  climate  efforts;  and  sea  level  and  global 
warming  data  that  tracks  changes  in  sea  levels  and  temperature  patterns,  illustrating  the  direct 
impacts of climate change. 

Impact 

The initiative promotes informed policy decisions by providing clear data and grading results that 
help  policymakers  align  their  strategies  with  climate  goals.  It  increases  accountability,  thus 
motivating  governments  and  other  organisations to achieve  green  results  and adopt  sustainable 
practices. By making climate data accessible, it fosters public awareness about the significance of 
climate action and the effects of climate change, resulting in a more informed citizenry. Finally, the 
initiative encourages collaboration and data sharing among countries and organisations, facilitating 
a unified approach to tackling global climate challenges. 

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Reuse case example from Sweden – Klimatkollen (Climate Check-Up) 
Subdomain 

Energy consumption and the switch to renewables. 

Functioning and purpose 

Klimatkollen (Climate Check-Up) is a web service that provides citizens with access to information 
about  carbon  emissions  in  Swedish  municipalities,  specifically  in  relation  to  the  carbon  dioxide 
budget established by the Paris Agreement. The platform aims to raise awareness about climate 
change  and  promote  community  engagement  in  sustainability  efforts.  By  making  public  data 
accessible, it empowers individuals and local governments to understand and address their carbon 
footprints. The primary objectives of the Klimatkollen initiative are as follows. 

•  Raising  awareness.  To  educate  citizens  about  the  levels  of  carbon  emissions  in  their 
municipalities and the importance of reducing these emissions to meet climate goals. 
•  Promoting  transparency.  To  provide  accessible  information  on  carbon  emissions  and 

sustainability efforts, fostering accountability among local governments. 

•  Encouraging action. To motivate individuals and communities to take action to reduce their 

carbon footprints and support climate-friendly policies. 

As  exemplified  in  Figure 21,  the  platform  analyses  the  emissions  of  both  businesses  and 
municipalities. In the former case, the data was used to conduct an analysis of 150 major Swedish 
companies’  climate  reporting.  In  the  latter  case, the platform  displays  an  interactive  map  of  the 
entire country, showing the changes in several climate indicators since the Paris Agreement. The 
indicators include, for example, carbon dioxide emissions and budgets to electric car and bike usage. 
The data can be consulted and downloaded freely. 

Figure 21: Overview of businesses’ carbon emissions and their distribution within Sweden 

Target group 

Klimatkollen  serves  several  key  stakeholders:  citizens 
in  understanding  their 
municipality’s  carbon  emissions;  local  governments,  which  can  assess  their  performance; 
researchers and activists; and educational institutions. 

interested 

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Datasets used 

Klimatkollen relies on various public datasets to provide accurate information on carbon emissions. 
Users can find specific details about these datasets by visiting the data sources and methods section 
of the website and selecting ‘Om våra källor’ (‘About our sources’). 

Impact 

Klimatkollen  promotes  an  informed  citizenry  by  providing  clear,  accessible  information  about 
carbon emissions, empowering individuals to understand their impact on the climate. It increases 
local-level accountability by encouraging municipalities to be transparent about their emissions and 
engage  in  climate  action.  The  platform  supports  data-driven  decision-making  for  policymakers, 
aligning  local  actions  with  national  and  international  climate  goals.  Additionally,  by  raising 
awareness  of  climate  issues,  it  fosters  community  engagement  and  encourages  collective  action 
towards sustainability. 

Economic impact 

The ‘economic impact’ subindicator evaluates the presence of research data on open data impact and 
reuse  cases  that  pertain  to  (1)  employment,  (2)  innovation  and  adoption  of  new  technologies,  (3) 
entrepreneurship and business creation and (4) productivity. Table 62 presents an overview of how 
countries responded to the questions on this topic. 

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Table 62: Countries’ responses to questions on economic impact 

EU-27 

EFTA 

Is there data 
on the 
impact 
created by 
open data on 
economic 
challenges? 

16 Member 
States (59 %) 
report having 
such data 
available. 
This is an 
increase of 
two countries 
from 2023. 

Norway 
reports 
having such 
data 
available. 

Is there a 
reuse case 
example 
related to 
employment? 

Is there a reuse 
case example 
related to 
innovation 
and new 
technologies? 

Is there a reuse 
case example 
related to 
entrepreneurship 
and business 
creation? 

Is there a reuse 
case example 
related to 
productivity? 

21 Member 
States (78 %) 
gave an 
example of a 
reuse case on 
this topic. 
This is an 
increase of 
four countries 
from 2023. 

None of the 
participating 
EFTA 
countries 
gave an 
example of a 
reuse case on 
this topic. 

21 Member 
States (78 %) 
gave an 
example of a 
reuse case on 
this topic. 

19 Member 
States (70 %) 
gave an example 
of a reuse case 
on this topic. This 
is an increase of 
two countries 
from 2023.  

17 Member 
States (63 %) 
gave an 
example of a 
reuse case on 
this topic. 

Iceland and 
Switzerland 
gave an 
example of a 
reuse case on 
this topic. 

All three 
participating 
EFTA countries 
gave an example 
of a reuse case 
on this topic, 
with Iceland as 
the latest 
addition. 

None of the 
participating 
EFTA countries 
gave an 
example of a 
reuse case on 
this topic. 

Candidate  Ukraine 
reports 
having such 
data 
available. 

Serbia and 
Ukraine gave 
an example of 
a reuse case 
on this topic. 

Serbia and 
Ukraine gave 
an example of 
a reuse case 
on this topic. 

Serbia and 
Ukraine gave an 
example of a 
reuse case on 
this topic. 

Serbia and 
Ukraine gave 
an example of 
a reuse case 
on this topic. 

(Questions I27, I28, I29, I30 and I31) 

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The following are some interesting reuse cases reported on this topic. 

Reuse case example from France – La Bonne Alternance and Emplois de l’inclusion 
Subdomain 

Employment. 

Functioning and purpose 

This  initiative  encompasses  two  interconnected  services  aimed  at  fostering  job  creation  and 
improving  access  to employment  opportunities:  La bonne  alternance  and  Emplois  de  l’inclusion. 
Both services leverage open data and digital tools to connect jobseekers with training centres and 
employers, focusing particularly on supporting young people and vulnerable individuals in finding 
meaningful work. 

La bonne alternance is a digital public service designed to connect young people, apprenticeship 
training centres (CFAs) and companies (Figure 22). The platform provides a range of features to 
facilitate the apprenticeship process and improve job access for youth, including: 

a feature enabling small and medium-sized enterprises (SMEs) and CFAs to post job offers; 
a service that connects young people with CFAs; 
a feature enabling jobseekers to submit applications directly through the platform; 

• 
• 
• 
•  modules  to  support  communication  with  CFAs  and  provide  assistance  in  finding  host 

companies. 

Achievements since the beginning of 2024 include the following: 

•  12 171 job offers have been posted; 
•  538 745 applications have been submitted; 
•  48 942 contacts with CFAs have been established. 

Figure 22: The home page of the website La bonne alternance 

Emplois de l’inclusion, is another service that utilises open employment data to connect jobseekers 
with social enterprises. This initiative is aimed at helping vulnerable individuals access employment 
and training opportunities, facilitating their social integration through work. Key accomplishments 
include the following: 

•  1 150 687 candidates have been hired through the service; 

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•  5 386 social enterprises have participated in recruitment. 

The overarching goals of these services are set out below. 

• 

• 

• 

Job creation. To facilitate job placements and enhance employment opportunities for young 
people and vulnerable populations. 
Improving accessibility. To streamline the connection between jobseekers and employers, 
particularly for those experiencing barriers to employment. 
Support for vulnerable individuals. To provide targeted assistance and resources for people 
from disadvantaged backgrounds to aid their integration into the workforce. 

Target group 

The platforms cater to young jobseekers looking for apprenticeships and placements, SMEs seeking 
to recruit young talent, social enterprises seeking to hire vulnerable people and the CFAs, which 
support the professional development of young people. 

Datasets used 

The  services  utilise  datasets  including  apprenticeship  training  offers,  job  offers  from  SMEs  and 
social  enterprises,  and  employment  data  on  candidates  and  hiring  statistics.  For  more  detailed 
insights,  refer  to  the  report  Measuring  the  Impact  of  Open  Data:  Analyzing  governmental, 
environmental, social and economic impacts dimensions in France. 

Impact 

The  platforms  enhance  employment  opportunities  for  young  people  and  vulnerable  individuals, 
aiding  their  integration  into  the  workforce.  They  promote  inclusivity  by  focusing  on  social 
enterprises  and  marginalised  groups,  and  data-driven  insights  ensure  continuous  improvement. 
Additionally,  the  platforms  foster  community  engagement  by  connecting  employers,  training 
centres and jobseekers, creating a supportive employment ecosystem. 

Reuse case example from Slovenia – Sentinel Hub 
Subdomain 

Entrepreneurship and business creation. 

Functioning and purpose 

Sentinel  Hub  is  an  advanced  geospatial  data-processing  engine  that  facilitates  access  to, 
visualisation  of  and  analysis  of  vast  amounts  of  satellite  imagery  and  Earth  observation  data 
(Figure 23). Sentinel Hub enables users to leverage open satellite data, including imagery from the 
Sentinel and Landsat missions. It is designed to support application developers and researchers, with 
a user-friendly interface for browsing and processing satellite data at scale. The primary objectives 
of Sentinel Hub include the following. 

•  Data accessibility. To provide easy access to satellite imagery and Earth observation data 

• 

for a wide range of applications, from agriculture to urban planning. 
Supporting innovation. To empower developers and researchers to build innovative 
applications using satellite data and machine learning. 

•  Enhancing decision-making. To assist stakeholders in various sectors in making informed 

decisions based on accurate and timely satellite imagery. 

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Figure 23: The functionalities of Sentinel Hub 

Target group 

Sentinel Hub serves developers and researchers, policymakers and businesses in sectors such as 
agriculture; these target groups use satellite data for applications such as environmental 
monitoring and urban planning. 

Datasets used 

Sentinel Hub leverages key datasets including Sentinel data from the Copernicus programme, 
Landsat imagery for historical land-use analysis and open Earth observation data, which ensures 
broad accessibility and fosters innovation (Figure 24). 

Figure 24: Overview of the data sources used by Sentinel Hub 

Impact 

Sentinel  Hub  revolutionises  Earth  observation  by  transforming  access  to  satellite  data,  enabling 
faster  and  more  efficient  space  applications.  It  accelerates  innovation  across  sectors  by  making 
satellite imagery easily accessible, supports real-time data processing for timely decision-making, 
and offers global scalability, enabling users to process and visualise data on a global scale. 

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Chapter 8: Maturity-based clustering and recommendations 

In  this  chapter,  the  participating  countries  are  grouped  into  four  clusters  based  on  their  overall 
maturity  scores.  Clustering  countries  on  their  level  of  open  data  maturity  (ODM)  helps  to  identify 
affinities.  Countries  in  the  same  cluster  can  discuss  strategies  to  overcome  shared  challenges. 
Moreover, countries in less mature clusters can learn from those in more mature clusters. Clustering 
also enables more focused recommendations to be formulated for each group of countries. 

8.1. Clustering 

To group the countries into clusters, the overall maturity scores were plotted from lowest to highest. 
Groups  were  demarcated  where  observable  gaps  in  the  ordered  scores  were  identified.  From  the 
lowest  to  the  highest  performing,  the  four  clusters  are  beginners,  followers,  fast-trackers  and 
trendsetters. The clusters are visualised in Figure 25. 

The distribution of composite maturity scores is skewed towards higher scores. The clusters are as 
follows. 

•  Trendsetters (94–100 %). Cyprus (CY), Estonia (EE), Italy (IT), Czechia (CZ), Lithuania (LT), 

Spain (ES), Ireland (IE), Slovakia (SK), Ukraine (UA), Poland (PL) and France (FR). 

•  Fast-trackers (83–90 %). Luxembourg (LU), Serbia (RS), Austria (AT), Norway (NO), Portugal 

(PT), Slovenia (SI), Latvia (LV) and Denmark (DK). 

•  Followers (74–80 %). Belgium (BE), Germany (DE), Hungary (HU), Finland (FI), the 

Netherlands (NL), Sweden (SE) and Switzerland (CH). 

•  Beginners (15–69 %). Bosnia and Herzegovina (BA), Albania (AL), Malta (MT), Iceland (IS), 

Greece (EL), Bulgaria (BG), Croatia (HR) and Romania (RO). 

Figure 25: Four-group clustering of participating countries based on overall maturity score 

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8.2. Recommendations 

Countries can use the following general advice to improve on their current ODM methodologies. 

Trendsetters 

Maintain the ecosystem, experiment and share knowledge 

Cluster characteristics 

The country has an advanced open data policy in place, with substantial coordination of open data 
activities at all levels of government. The national portal provides a wide range of features and 
caters to the needs of advanced users and publishers. 

The quality of metadata accompanying open data in the country is very high, with various initiatives 
in place to ensure the publication of high-quality metadata and compliance with DCAT-AP. 

Open  data  is  taken  up  and  reused  for  various  purposes,  creating  impact  in  several  domains. 
Activities to measure reuse  are conducted, with methodologies in place to assess the impact in 
different domains. Few or no limitations on publication or reuse are observable. 

1.  Enhance  and  consolidate  the  open  data  ecosystems  you  support  by  developing  thematic 
communities of providers and reusers. Continue to prioritise the categories specified as high-value 
datasets (HVDs). 

2.  Steer  the  network  of  open  data  officers  to  enable  data-driven  policymaking  at  their  level  of 
government, delegating and decentralising monitoring activities. Keep consistent the connection 
between the  national  strategy  and objectives  and  the  needs of  agencies  and  local  authorities, 
which will gain prominence over time. 

3.  Decide on and develop a strategy to ensure the sustainability of the national and local open data 
portal infrastructures. Experiment with alternative funding models. Share the outcomes of your 
experimentation with other countries. 

4.  Collaborate with other national data teams, universities, research institutions and data.europa.eu 
to  develop  an  impact  assessment  framework.  In  addition,  start  developing  country-specific 
metrics to measure impact beyond outputs. Consider options to assess both open data and data 
altruism initiatives. Operationalise monitoring the metrics and evaluating impact. Rely on a mix of 
methods (e.g. ex ante and ex post analyses, structured/semi-structured interviews, use cases, log 
analyses from the national portal) to gain a variety of insights. Improve your methods iteratively 
over time. 

5.  Continue to assess the impact of open data across sectors at both the micro- and macroeconomic 
levels. Showcase open data reuse cases in the economic, environmental and social domains to 
enhance and measure the impact of open data and to create an open data culture. Ensure that 
this impact is measured objectively by clearly defining open data impact. Repeat the assessments 
annually or biannually to observe change and refine activities and goals. Leverage the momentum 
created by showcasing the results to rally stronger political support. 

6.  Harness the wisdom of the crowd by enabling the broader open data community to contribute 
more to national open data programmes. Enable reusers to upload their own data and showcase 
their  ideas  and  creations  on  the  national  portal.  Ensure  that  publishers  improve  their  data 
publication based on reusers’ feedback and ratings. 

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7.  Continue to improve the quality of data and its metadata by boosting the use of tools on your 
portal (e.g. for metadata validation). Explore the use of tools powered by artificial intelligence to 
improve metadata quality. Enable automated notifications to publishers to alert them to issues. 
Provide tools to convert data into alternative formats, possibly replacing non-machine-readable, 
proprietary formats. Invest in the portal so that you can use new workflows and tools that enable 
a better understanding of your reusers’ profiles and needs while preserving their privacy. 

8.  After  establishing  an  effective  system  for  labelling  and  filtering  HVDs  on  the  portal,  focus  on 
maintaining this system and regularly monitoring dataset usage. Prioritise understanding reuse 
cases of HVDs and their potential positive impact on society. As part of these efforts, publish and 
promote successful reuse cases on the portal and regularly interact with data providers and users 
to better understand their needs and explore potential applications of these datasets. 

9.  Evaluate options for extending the open data portal such that it serves as a public register of data 
altruism organisations, or advise your government on which approach would best support the 
new initiatives in this area. Although the ODM assessment focuses on the open data directive 
(Directive (EU) 2019/1024), open data portals can be leveraged in efforts to implement other EU 
legislation,  such  as  the  Data  Governance  Act  (Regulation  (EU)  2022/868)  and  the  Data  Act 
(Regulation (EU) 2023/2854). For example, open data portals can be used to increase the visibility 
of  public  sector  information,  including  protected  data.  Particularly  for  real-time  data,  link  to 
various  sources  and  evaluate  means  of  incentivising  custodians  of  real-time  data  to  publish 
beyond the minimum legislative requirements. 

10. Work with training institutions to provide advanced open data courses and training, and tailor 
training  curricula  to  cover  more  advanced  topics.  Such  training  can  include  guidance  on 
compliance  with  open  data  laws  and  education  on  data  literacy.  Make  such  courses  formally 
recognised and provide certification upon successful completion. 

11. Share your knowledge and the results of your experimentation with other countries to enable 
them to learn from your best practices and contribute to your research, for example in shared 
areas of focus or areas where you experience similar barriers. Reach out and cooperate with other 
countries to develop solutions to common challenges, including basic, reusable elements such as 
open-source software that your platforms can share (e.g. portal extensions). 

Fast-trackers 

Graduate from traction to impact 

Cluster characteristics 

The country shows a good level of maturity in all dimensions. Overall, the country demonstrates 
that it undertakes activities to boost data publication, with a strategic approach to increasing the 
quality of published metadata and increasing compliance with quality standards. 

The  national  portal  provides  a  good  level  of  functionalities  that  cover  the  needs  of  basic  and 
advanced users. 

Substantial efforts are made to monitor the impact of open data. However, some issues in data 
publication or creating impact can still be observed, although measures are in place to tackle them. 

1.  Assist  in  the  development  of open  data  initiatives  at  the  local  and  regional  levels  and  seek  to 

achieve better coordination with local and regional open data teams. 

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2.  Activate the network of open data officers and enable them to set up monitoring activities within 
their organisation (e.g. by developing plans for data publication and monitoring practices). Track 
progress against these plans and assist open data officers in alleviating barriers to data publication 
identified in their organisations. 

3.  Ensure that existing open data courses and training materials are promoted and used. Cooperate 
with training organisations to develop new course offerings tailored to the needs of your national, 
regional  and  local  administrations.  Make  such  courses  formally  recognised  and  provide 
certification  upon  successful  completion.  Ensure  that  financial  resources  are  allocated  at  all 
administrative levels to enable more civil servants to benefit from training. 

4.  Focus  on  organising  activities  that  better  target  the  delivery  of  sustainable  solutions.  Move 
beyond  creativity-stimulating  competition  formats  (e.g.  hackathons)  to  formats  that  provide 
opportunities  for  the  medium-  to  long-term  engagement  of  businesses.  Ensure  funding  and 
political sponsorship (e.g. by having an organisation serve as patron) for the winning ideas. 

5.  Promote and follow up on the performance of products and services built on open data. Develop 
strategic  awareness  of  reuse  and  impact.  Focus  resources  on  a  relevant  field  or  sector  to 
demonstrate impact, and use the specifications on HVDs for prioritisation. Set up thematic work 
groups in these areas. Create a framework for knowledge exchange and enable the development 
of a community of practice made up of providers and reusers. Increase your knowledge on the 
publication and reuse of data in the domain you have chosen to focus on and start thinking about 
a definition of impact in this field that can be operationalised through metrics. 

6.  Monitor access to and usage of the portal and enhance knowledge in your team of the profiles of 
your portal’s typical users. Update the portal to better engage your audience. Include features 
that enable online interaction between data publishers and reusers. Showcase reuse examples 
prominently on the national portal and promote the datasets used to develop those reuse cases. 
Consider opportunities to promote the dataset developers as well. Enable the insights obtained 
from monitoring to flow into improving the portal features, access to data and the variety of data 
published in your country. 

7.  Establish  and  maintain  a  data  inventory  to  ensure  interoperability  across  systems  and  reduce 
redundant  data  collection.  Conduct  regular  data  audits  to  ensure  that  data  is  up  to  date  and 
accurate. 

8.  Enhance the national portal’s promotion of HVDs by adding advanced filtering options, allowing 
users to easily navigate to and explore datasets across the six HVD categories. Create dedicated 
sections on the portal where users can browse all available HVDs, learn about their importance 
and stay informed on the latest advancements in the field. As a best practice, consider studying 
the applications of these HVDs in depth to identify impactful reuse cases and showcase them on 
the portal to drive broader awareness and engagement. 

9.  Address any requirements relating to implementing the open data directive in your country that 
have not yet been addressed or are lagging behind in terms of features by revising and enhancing 
the portal’s support for real-time data sources. Identify the primary real-time data holders and 
promote  the  publication  of  their  data  beyond  the  minimum  requirements  specified  by  law. 
Understand the concerns about and the costs of publication and work with publishers to facilitate 
the data publication process. Become aware of the requirements of the Data Governance Act and 
the Data Act and start exploring options to address them. 

10. Think of ways to ensure the portal’s sustainability by enabling more contributions from the open 
data community (e.g. submitted datasets, reuse cases developed, news articles and blog posts 
written by the community), by providing value-added features and by exploring additional funding 
options. 

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11. Enforce  minimum  standards  on  the  quality  of  data  by  using  analytics  tools  to  monitor  data 
publication –  for  both  metadata  (compliance  with  DCAT-AP)  and  data  (publication  formats). 
Develop validation processes for your national portal and report back to data providers. Act on 
the findings and provide tailored assistance to publishers to increase the quality of publication of 
both metadata and data. Explore the use of tools powered by artificial intelligence to improve 
metadata quality. 

Followers 

Strengthen governance, boost engagement 

Cluster characteristics 

The country has an open data policy in place that is supported by implemented measures. There is 
coordination on these activities. The portal has standard features but also some features that cater 
to the needs of more advanced users. 

Some  activities  are  conducted  to  boost  the  publication  of  high-quality  metadata  from  different 
providers; however, often, a systematic approach to ensuring high publication quality across the 
board is lacking. 

Limited activities are performed to monitor reuse and measure the impact of open data. Several 
limitations in terms of data publication and reuse still exist. 

1.  Update the national strategy on open data to reflect technical and policy developments at the EU 
level. If you have not yet done so, develop a definition of open data impact, setting up a framework 
to measure the benefits for society of reusing open data. 

2.  Set  up  a  governance  structure  that  accounts  for  the  characteristics  of  your  country.  Engage 
potential reuse groups (e.g. data-gathering companies, research institutions, non-governmental 
organisations) in open data governance in your country. This will enable co-ownership around a 
common vision and buy-in for the actions of each sector. 

3.  Develop a yearly plan for online activities (e.g. events, conferences) to promote open data. Focus 
on  competition  formats  that  encourage  publication  and  reuse  by  both  the  public  and  private 
sectors. Experiment with formats that both leverage creativity (e.g. hackathons) and enable the 
development  of  business  opportunities  in  the  medium  to  long  term  (e.g.  data  challenge 
competitions). Ensure funding and political sponsorship for the winning ideas. Promote and follow 
up on the performance of products and services developed. 

4.  Analyse user behaviour on the data portal responsibly, ensuring user privacy and being explicit 
about how insights will be used. Identify communities of reusers and conduct awareness-raising 
activities  around  open  data  within  these  groups  (e.g.  universities,  data  start-ups  and  data 
companies, research institutes, non-governmental organisations and journalists). 

5.  Encourage the network of open data liaison officers to set up data publication plans and monitor 
progress  against  these  plans.  Enable  the  open  data  officers  to  exchange  knowledge  and 
experiences between public sector bodies and with the broader network of reusers. Deepen the 
understanding within the network of open data officers of the benefits of open data reuse by the 
public sector. 

6.  Ensure that existing open data courses and training materials are leveraged and cooperate with 
public  administrations  and  training  organisations  to  develop  open  data  training  curricula  for 

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national, regional and local administrations. Enable such courses to be formally recognised and 
provide  certification  upon  completion.  Ensure  that  financial  resources  are  allocated  at  all 
administrative levels to training activities for civil servants working with data. 

7.  Enable  meet-ups  and  engagement  between  reusers  and  publishers.  Develop  a  deeper 
understanding of the demand side of open data and work with data providers to prioritise data 
publication accordingly. Focus on fostering open data reuse by the public and private sectors and 
encourage the  open data community to share their reuse cases. Promote  these  open data use 
cases more  prominently on the  national portal, ideally in a section directly accessible  from the 
home page. 

8. 

Implement editorial tools, such as labels or tags, to increase the visibility of HVDs on the portal and 
encourage reuse by enabling users to filter specifically for these datasets. It would be beneficial to 
include a dedicated section of the portal that provides users with the latest updates and a clear 
overview of HVDs and their significance. 

9.  Regularly  update  the  portal  to  reflect  users’  needs.  Include  features  such  as  feedback  and 
interaction mechanisms at the dataset level, designated login areas for users, access via SPARQL 
queries and application programming interfaces in general. Consider integrating data visualisation 
and analytics tools to allow portal visitors to gain insights from data through interactive charts and 
other visualisation tools. Monitor access to and usage of the portal. Draw insights from this data 
and enhance awareness of it within your team. Become aware of the requirements of the Data 
Governance Act and the Data Act. 

10. Increase your understanding of the variety of data that your portal has (e.g. historical and current 
data) and work towards improving it. Identify data holders that do not publish their data or do not 
reach their full potential. Understand what friction they are experiencing and plan to address it. 
Enable publication of real-time data in your country. 

11. Provide training and online materials focusing on metadata and data quality. Promote the DCAT-
AP  standard  and  existing  guidelines  to  foster  compliance.  Create  an  understanding  of  the 
importance of publishing data in machine-readable, non-proprietary formats and of the licensing 
of  data.  Develop  knowledge  around  existing  open-source  tools  for  cleaning  up  data,  and 
specifically the use of validators for metadata compliance. 

Beginners 

Think big, act small 

Cluster characteristics 

The country is at an early stage of maturity in the four dimensions (or has yet to develop at the 
same pace as the countries in the higher-performing clusters). Fair progress towards an open data 
policy has been made, but this still needs to be supported by more robust implementing measures. 

The  open  data  portal  has  limited  features  or  a  limited  number  of  datasets.  No  or  very  limited 
activities are performed to monitor the reuse and impact of open data. 

More  action  is  needed  to  enable  high-quality  data  publication,  and  limited  efforts  are  directed 
towards ensuring the adoption of DCAT-AP standards. Clear limitations exist regarding open data 
publication, with only a few reuse examples. 

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1.  Develop a national strategy for open data and align it with broader strategies at the national level 
(e.g.  digital  strategies,  strategies  for  the  modernisation  of  the  public  sector).  Ensure  the 
development  of  legal  frameworks  and  ethical  guidelines  to  govern  the  use  of  open  data  and 
generally safeguard sensitive and personal information. 

2.  Rally  support  for  the  open  data  programme  and  political  leadership  from  the  top  level  of 
government. Showcase international research around the value of open data to emphasise the 
economic benefits of data exploitation. Use HVDs as a focal point. 

3.  Establish a team at the national level in charge of open data to ensure coordination of activities 
within the country and set up ‘roadshows’ to increase  understanding of the  team’s scope  and 
activities among primary public administrations. Include all levels of government in this process. 

4.  Organise  a  series  of  open  data  events  at  the  national  level  and  focus  on  engaging  both  data 
publishers and reusers in your country. Prioritise the promotion of reuse cases and best practices 
for data publication during such events. 

5.  Set up relevant communication channels and assign contact people for data publication within 
public  administrations  (e.g.  open  data  liaison  officers).  Maintain  an  active  dialogue  with  data 
officers  and  enable  regular  exchanges  of knowledge  among  them,  focusing on  efficient  online 
channels and face-to-face meetings. 

6. 

Identify  the  primary  data  holders  in  the  country  and  understand  their  main  concerns  and  the 
barriers to  data  publication  that  they  perceive.  Take  the  first  steps  towards overcoming these 
barriers and unlocking the publication of data. 

7.  Organise workshops and awareness-raising sessions with the primary data holders. Use materials 
already developed in other countries and at the European level for content and as a source of 
inspiration. 

8.  Begin exploring HVDs by reviewing the legislation that came into effect in June 2024. As a best 
practice, consider adding a dedicated section to the portal to provide users with updates and a 
general overview of what HVDs are. As a next step, consider labelling relevant datasets as high 
value on the portal to increase their visibility and encourage reuse. 

9.  Develop guidelines to enable the publication of data and its metadata, as well as the take-up of 
suitable licensing conditions. If standard licences are not appropriate, as a last resort, investigate 
the possibility of developing a custom national licence. Learn from European best practices and 
reach  out  to  colleagues  in  other  countries  when  setting  out  to  create  such  guidelines.  Raise 
awareness among the leading data publishers of the importance of metadata and promote the 
DCAT-AP standard and specifications and existing guidelines developed at the European level. 

10. Ensure that you run and maintain a modern portal that enables the publication and discoverability 
of  open  data.  Scout  for  European  best  practices  and  compare  solutions  to  choose  the  most 
appropriate ones to support the scope of your activities and your mission. Set up dedicated news 
and blog sections of the portal to promote relevant developments and showcase reuse. Ensure 
that  feedback  channels  are  seamlessly  integrated  into  the  national  portal.  Be  aware  of  users’ 
rights and privacy when performing web analytics, and choose your technology carefully. 

11. Ensure that the national open data strategy guarantees the scoping, management and funding of 
the portal. Use action plans setting out specific activities and responsible entities or people to 
ensure that the strategy can be carried out. Ensure that sufficient resources are allocated to open 
data awareness-raising activities with publishers and potential reusers. 

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Chapter 9: Conclusions 

Countries in Europe remain stable in terms of their open data maturity (ODM). This is despite an update 
to the ODM assessment methodology that set higher requirements for several questions. The intention 
of  the  update  was  to  systematically  stimulate  ODM  in  Europe  and  to  keep  pace  with  policy  and 
technological  developments  while  ensuring  consistency  and  comparability  with  previous  ODM 
assessments. 

In the EU, the policy dimension remains the most advanced, with its average score showing year-on-
year improvement. This means that countries could provide the more detailed explanations requested 
in  the  revised  questionnaire  about  their  governance  structures.  The  underlying  ‘open  data 
implementation’  indicator  increased  its  score  the  most,  reflecting  the  fact  that  EU  Member  States 
continue  to  implement  their  open  data  policies  through  specific  measures  and  activities  and  have 
systems to assist data holders and address policy challenges. All Member States report that they are 
working towards applying the  implementing regulation on high-value  datasets (HVDs) (Commission 
Implementing  Regulation  (EU)  2023/138).  Some  data  categories,  such  as  statistical,  geospatial  and 
meteorological  data,  and  some  tasks,  such  as  identifying  HVDs and  addressing legal  barriers,  show 
more progress than others. Nonetheless, there have been significant advancements (progress of more 
than 10 percentage points per category and task) compared with 2023. 

The  portal  dimension  remains  the  second  most  mature.  However,  this  dimension  saw  the  largest 
average year-on year decrease in score  among the four dimensions year-on-year. In particular, the 
‘portal  features’  indicator  experienced  the  greatest  decrease.  As  part  of  the  update  to  the  ODM 
assessment methodology, questions about the presence of mature functionalities such as advanced 
search, filtering and download options were removed from the questionnaire. The absence of these 
points may have caused countries to score lower than in 2023 on this indicator. New requirements 
were also introduced regarding how portal managers use the data they collect from and about users 
to improve the portal. Overall, national portals probably remain similar to 2023, with the decrease in 
maturity scores related to the higher requirements set in this year’s questionnaire. The automated 
tests on portal performance introduced in this year’s assessment as a pilot indicator also highlighted 
various areas in which open data portals can invest efforts to improve their performance. 

Scores on the quality dimension also decreased on average compared with 2023, and it is narrowly 
the dimension on which countries scored the lowest. However, scores on the dimension are still higher 
than in 2022. Several countries recorded lower metadata quality scores on the same questions asked 
last  year.  Presumably,  this  reflects  more  accurate  reporting  than  in  the  previous  year,  perhaps 
indicating more accurate insights from their processes and monitoring tools. The computed metrics on 
metadata  quality  introduced  in  this  year’s  assessment  as  a  pilot  indicator  provide  an  automated 
evaluation of the metadata harvested by data.europa.eu. The goal of this pilot is to demonstrate the 
potential of using automatically measured metrics of metadata quality. The tool will need to undergo 
further scrutiny to enable more objective reporting in the future. DCAT-AP compliance, defined strictly 
using SHACL validation, is generally low. The pilot indicator highlights various areas in which metadata 
quality can still be improved. 

The  impact  dimension  again  experienced  the  greatest  year-on-year  improvement.  Building  on  the 
improvements from last year, Member States took further action to document the reuse of open data 
and collect and classify reuse cases. This translated into a greater awareness of available reuse cases, 
especially in the environmental and economic domains. However, examples of reuse cases  are still 
more readily available than systematically collected data on the impact created by open data. 

In the year ahead, Member States will continue to work to fully apply the implementing regulation on 
HVDs,  for  example  by  conducting  the  necessary  technical  upgrades  to  data  publication  processes 
(using application programming interfaces). In addition they will also ensure that they are no longer 
charging fees for the reuse of HVDs, that their metadata conforms to the DCAT-AP specification for 

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HVDs,  implementing  requirements  of  both  the  infrastructure  for  spatial  information  in  Europe 
directive (Directive 2007/2/EC) and the implementing regulation on HVDs for certain datasets, as well 
as fulfilling obligations on reporting to the Commission. 

In 2025, open data  teams must  continue  to navigate the evolving data-sharing landscape and help 
implement, or coordinate with their peer civil servants leading, new and complementary government 
initiatives on data sharing. For example, the Data Governance Act (Regulation (EU) 2022/868) and the 
Data Act (Regulation (EU) 2023/2854) introduce measures to increase data availability and overcome 
technical obstacles to the reuse of data. Specifically, under the Data Governance Act, Member States 
must  establish  national  single  information  points  (NSIPs)  to  assist  potential  reusers  in  finding 
information  on  what  protected  data  can  be  reused  under  specific  conditions.  Information  will  be 
collected from NSIPs and incorporated into the European Register for Protected Data held by the Public 
Sector,  which  will  require  their  metadata  to be  structured  and  provided  in  a  specific  way;  other 
technical  and  operational  requirements  for  NSIPs  will  also  need  to  be  met.  In  addition,  common 
European data spaces continue to be developed to increase the availability of data-sharing tools and 
services for the pooling, processing and sharing of industry data in accordance with European values 
and principles and with full respect for data providers’ rights and for confidentiality. 

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Appendix: Methodology 

This appendix describes the methodology of the 10th edition of the annual open data maturity (ODM) 
assessment conducted by data.europa.eu. 

Contents 

Appendix: Methodology ............................................................................................................ 150 

Objectives of the open data maturity assessment .......................................................................... 150 

History of the open data maturity assessment ............................................................................... 151 

Work approach ................................................................................................................................ 152 

Indicators and metrics ..................................................................................................................... 152 

Scoring  ............................................................................................................................................. 157 

Pilot indicator: automated metrics of metadata quality ................................................................. 158 

Pilot indicator: automated metrics of portal performance............................................................. 160 

Objectives of the open data maturity assessment 

Since its launch in 2015, data.europa.eu (1) has been the main point of access at the EU level to public 
sector information published across Europe. The portal aims to improve access to open data, as well 
as to foster both high-quality open data publication and the reuse of open data to create impact. 

Within this remit, data.europa.eu conducts an annual landscaping exercise of European countries on 
their ODM. Participation is voluntary, and the scope of the assessment includes the EU Member States, 
European Free Trade Association (EFTA) countries and candidate countries for EU membership. 

The purpose of the ODM assessment is to evaluate  the development of countries in making public 
sector information available and stimulating its reuse. The landscaping exercise offers a benchmarking 
and  learning  tool  for  use  at  both  the  national  and  European  levels.  The  results  of  the  assessment 
support  countries  in  better  understanding  their  relative  level  of  maturity  compared  with  other 
countries.  The  results  also  capture  year-on-year  developments  in  countries’  ODM  and  help  in 
identifying  areas  for  improvement.  Furthermore,  the  exercise  also  results  in  evidence-based 
recommendations on the activities that European countries could adopt to increase their ODM. 

The ODM assessment is informed by the EU’s open data policies, primarily the  open data directive 
(Directive  (EU)  2019/1024)  and  the  implementing  regulation  on  high-value  datasets  (Commission 
Implementing Regulation (EU) 2023/138). The ODM assessment also includes questions about data 
that  cannot  be  made  open,  such  as  data  covered  by  the  Data  Governance  Act  (Regulation  (EU) 
2022/868), since having an overview of such data is helpful when making publication plans, and open 
data portals can be used to assist potential reusers in finding information on what protected data can 
be reused under specific conditions. 

(1)  data.europa.eu is the official portal for European open data. The portal was launched in 2021, formed 
from the merger of the European Data Portal and the European Union Open Data Portal into a single 
coherent core component of the public sector data infrastructure that has been set up by the EU, its 
institutions and the Member States. 

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History of the open data maturity assessment 

The first three editions of the ODM assessment (2015–2017) used two dimensions to assess ODM: (1) 
open data readiness and (2) portal maturity, which evaluated policy developments at the national level 
and the degree of sophistication of national open data portals, respectively. In 2018, a major update 
to  the  landscaping  methodology  was  carried  out  to  better  reflect  open  data  developments  across 
Europe. This revision of the methodology made the assessment more comprehensive and placed a 
stronger emphasis on the quality of metadata and the reuse of and impact derived from open data. 
The scope of the evaluation was broadened to cover four dimensions: (1) policy, (2) portal, (3) quality 
and (4) impact. 

In  2019,  additional  layers  of  granularity  were  added  to  the  four  dimensions.  The  updates  to  the 
assessment aimed to provide further stimulus for national open data teams to redirect their focus onto 
new  strategic  areas –  such  as  greater  prioritisation  of  high-quality  open  data  publication,  active 
fostering  of  mechanisms  to  monitor  open  data  reuse,  and  the  development  of  advanced  portal 
features such as multifaceted search and user feedback functionalities – and to raise awareness of the 
need for more inclusive and participative governance structures. 

In 2022, the methodology underwent another structured revision. To this end, all four dimensions and 
related questions were reviewed. Across the four dimensions, questions were streamlined to better 
include initiatives at the regional and local levels and specific types of open data, such as real-time data 
and  high-value  datasets.  In  addition,  the  revision  introduced  a  focus  on  countries’  level  of 
preparedness  for  the  European  Commission’s  upcoming  implementing  regulation  on  high-value 
datasets.  A  major  change  in  the  2022  methodological  update  was  the  restructuring  of  the  impact 
dimension. This was done to better acknowledge the challenge that countries face in assessing the 
impact  of  open  data  and  to  better  distinguish  between  measuring  the  reuse  of  open  data  and 
measuring the impact created through that reuse. This involved adding a new indicator, on measuring 
impact, to the impact dimension. 

In 2024, the method underwent another planned revision. The dimensions and indicators remained 
unchanged  from  the  previous  version  of  the  methodology.  In  the  policy  dimension,  more  detailed 
explanations were requested regarding the national governance structure, and a question was added 
about the processes in place to update policies/strategies. In the portal dimension, some mature portal 
functionalities, such as search and download, were removed from the questionnaire. More detailed 
explanations were requested regarding how data about portal usage and user feedback are used to 
improve the portal. In the quality dimension, more detailed explanations were requested regarding 
the workflows and activities of the portal team to ensure that several aspects of high-quality metadata 
are achieved. Some questions about the type of support offered to data providers were merged due 
to  overlapping  responses  from  survey  respondents.  No  major  changes  were  made  to  the  impact 
dimension, except that survey respondents needed to provide only one example of a reuse case for 
each category (instead of a maximum of three) and explain that case in more detail. Questions about 
high-value datasets were added across all dimensions, since the related implementing regulation was 
applicable  from  June  2024.  EFTA  and  candidate  countries  could  choose  ‘not  applicable’  when 
answering questions regarding specific EU legislative provisions and still be awarded full points under 
the scoring system. 

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Work approach 

The data for the ODM assessment is collected through a voluntary self-assessment questionnaire sent 
to national open data representatives. This is done in collaboration with the European Commission 
and the Expert Group on Public Sector Information. Most questions have a predefined list of response 
options  (e.g.  ‘Yes’  or  ‘No’)  from which  the  respondents  select.  In  addition, most  questions  request 
additional supporting information, such as a URL linking to relevant material or a description of related 
activities.  Questions  for  which  data  from  2023  was  available  were  prefilled  in  the  questionnaire, 
enabling survey respondents to confirm if last year’s response was still valid or provide a new response. 
This feature was newly introduced to support year-on-year consistency in responses. 

Once the completed questionnaires are submitted, the research team validates the responses. First, 
the team performs a high-level check of each questionnaire for completeness. Following this, countries 
are given the opportunity to provide input on any missing answers. Then, an in-depth review of the 
completed questionnaires is conducted. The reviewers assess whether the explanations accompanying 
the answers are complete, relate to the question and sufficiently justify the response selected. The 
reviewers mark questions that are insufficiently answered and therefore require further input from 
the countries. Since the questionnaires were prefilled, allowing the survey respondents to confirm or 
change their responses, only answers that survey respondents changed from the previous year and 
answers for new questions were reviewed in detail. 

Finally,  a  consultation  round  was  held  in  which  the  survey  respondents  were  invited  to  provide 
additional inputs and revise their responses to and supporting explanations for flagged questions. A 
preliminary scoresheet was shared with the survey respondents to validate the results. The research 
team finalised the scores based on the responses to the flagged questions. 

Indicators and metrics 

The indicators within each dimension are assessed through several questions that pertain to specific 
concepts. The tables below summarise the key concepts assessed for each indicator. 

Dimension 1: Open data policy 

1.1.  Policy framework 

1.1.1. 

▪  Open data policies and strategies are in place at the national, regional and/or local 

levels. 

▪  The open data policies/strategies include action plans with concrete measures. 

1.1.2. 

▪  The  (national) open data strategy incentivises the  public and private sectors to 

reuse open data. 

▪  The  (national)  open  data  policies/strategies  incentivise  access  to  real-time  and 

dynamic data, citizen-generated data and geospatial data. 

▪  The (national) open data policies/strategies incentivise the development of data 

inventories in national, regional and local public bodies. 

1.1.3. 

▪  Measures are in place to implement the regulation on high-value datasets. 

▪  Progress has been made in ensuring that public bodies holding high-value datasets 

are prepared to denote those datasets as such in their metadata. 

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Dimension 1: Open data policy 

2. 1.2. Governance of open data 

1.2.1. 

▪  An open data governance structure that ensures open data publication at all 

government levels is in place. 

▪  The governance structure enables the development of open data initiatives at 

the local and regional levels. 

1.2.2. 

▪  Details of the person or team responsible for open data activities in the country 

are publicly available. 

▪  A document describing the responsibilities and working approach of the national 
open data team (and possibly those of regional and/or local teams) is publicly 
available. 

▪  Regular exchanges between the national open data team and the team 

maintaining the national and/or local portal(s) are ensured. 

1.2.3. 

▪  Open data officers have been appointed at each public body level. 

▪  Regular exchanges between the national open data team and open data officers 

are ensured. 

▪  Regular exchanges between open data officers, data providers and data reusers 

are ensured. 

1.3. Open data implementation 

1.3.1. 

▪  Data publication plans exist at the public body level, and progress against these 

plans is monitored at the national level. 

▪  The number of public bodies still charging above the marginal costs for datasets 

is monitored. 

1.3.2. 

▪  Measures are in place to address the challenges faced in implementing the 

aforementioned open data policies/strategies. 

▪  There are activities to assist data holders in making their data publicly available. 

▪  There are processes in place to update the policies/strategies. 

1.3.3. 

▪  Training activities for civil servants working with (open) data are in place. 

▪  Training activities result in certification and/or are formally recognised as 

professional development for civil servants. 

▪  Society-wide open data literacy initiatives are in place. 

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Dimension 2: Open data portal 

2.1. Portal features 

2.1.1. 

▪  Portal features ensure the discoverability of and access to datasets (including 

through APIs) and relevant content. 

▪  Portal users can find documentation about using APIs and other tools that 
enable working with metadata, such as through search functionalities. 

2.1.2. 

▪  Advanced features enable users to provide content for the portal, give feedback 

on existing content and rate featured datasets. 

2.1.3. 

▪  The portal enables users to find information and news on relevant open data 

topics in the country. 

2.1.4. 

▪  The portal enables interaction and exchange between reusers and publishers. 

2.1.5. 

▪  Use cases are promoted through a designated section on the portal and mapped 

to the open data on which they are based. 

▪  Reusers can submit use cases to the portal. 

2.1.6 

2.1.7. 

▪  Preview functions for both tabular and geospatial data are available. 

▪  The portal has features to promote the visibility and reuse of high-value datasets. 

2. 2.2. Portal usage 

2.2.1. 

▪  Traffic to the portal (e.g. number of unique visitors, visitor profiles, percentage of 

outgoing portal traffic generated through APIs, number of downloads) is 
monitored by the portal team. 

2.2.2. 

▪  Analytics tools are used to derive insights into users’ behaviour and needs. 

▪  These insights are embedded in the portal update cycles. 

2.2.3. 

▪  The most and least consulted categories and datasets are known. 

▪  The most used search keywords are known, and updates are performed to 

ensure greater discoverability of available content. 

2.2.4. 

▪  API  usage  is  monitored  and the results are used to gain insights  into  user 

profiles. 

3. 2.3. Data provision 

2.3.1. 

▪  Most data providers can submit data to the national portal. 

▪  Data providers that do not contribute to the national portal have been 

identified, and actions have been taken to enable data publication from these 
sources. 

2.3.2. 

▪  Local or regional data sources are discoverable through the national portal. 

▪  Metadata from local or regional data sources is harvested automatically. 

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Dimension 2: Open data portal 

2.3.3. 

▪  Access to real-time data is provided through the national portal. 

▪  The percentage of real-time data in all data featured on the portal is known. 

2.3.4. 

▪  A separate section exists on the portal where community-sourced/citizen-

generated data can be uploaded. 

4. 2.4. Portal sustainability 

2.4.1. 

▪  Measures are in place to ensure that the portal reaches its target audience. 

▪  The national portal has accounts and an active presence on social media 

platforms. 

▪  The portal team helps to enhance the visibility of the portal and the featured 

datasets by organising/attending information sessions and/or events to promote 
the national portal. 

Dimension 3: Open data quality 

3.1. Metadata currency and completeness 

3.1.1. 

3.1.2. 

3.1.3. 

3.1.4. 

▪  A predefined approach is in place to ensure that metadata is up to date. 

▪  Mechanisms are in place to ensure that changes at the source are reflected with 

minimal delay on the national portal. 

▪  The portal provides access to a vast range of historical and current data. 

▪  Mechanisms are in place to ensure the interoperability of high-value datasets 

with those of other countries. 

2. 3.2. Monitoring and measures 

3.2.1. 

▪  Mechanisms are in place to monitor the quality of metadata. 

▪  Information on metadata quality is available to the broader public. 

3.2.2. 

▪  Guidelines and/or tools are available to assist data providers in choosing the 

correct licence for their data. 

▪  The compliance level in terms of correct licensing information is monitored. 

3.2.3. 

▪  Support (e.g. documentation, tools, a helpline) is in place to assist data providers 

in improving data quality. 

3. 3.3. DCAT-AP compliance 

3.3.1. 

▪  The national portal follows the DCAT-AP framework or is interoperable with it. 

3.3.2. 

▪  Compliance with the DCAT-AP standard regarding mandatory, recommended and 

optional classes is monitored.  

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Dimension 3: Open data quality 

3.3.3. 

▪  Monitoring activities on the percentage of accessible distributions (i.e. the 
availability of ‘accessURL’ and ‘downloadURL’ properties) are in place.  

4. 3.4. Deployment quality and linked data 

3.4.1. 

▪  A model (e.g. the 5-star open data model or similar) is used to assess the quality 

of data deployment. 

▪  Activities are in place to familiarise data providers with ways to ensure the 

provision of high-quality data. 

3.4.2. 

▪  The percentage of published open data that complies with the chosen quality 

model is known. 

Dimension 4: Open data impact 

4.1. Strategic awareness 

4.1.1. 

▪  Reuse of open data is monitored at the national, regional or local level, for 
example through the national portal. This includes monitoring the reuse of 
high-value datasets. 

4.1.2. 

▪  Activities are in place at the public body level to boost and monitor the reuse of 

bodies’ own published data. 

4.1.3. 

▪  A definition of reuse is in place. 

▪  A methodology to measure the impact of open data is in place. 

4.2. Measuring reuse 

4.2.1. 

▪  Activities  are  in  place  to  understand  which  datasets  are  reused  and  how,  for 

example: 
o  automated  feedback  mechanisms  are  in  place  to  track  users’  access  to 

datasets; 

o  interviews/workshops are conducted with reusers to gather feedback; 
o  surveys /  other  extensive  research  tools  are  used  to  measure  the  reuse  of 

open data. 

4.2.2. 

▪  Activities are in place to better understand reusers’ needs, for example: 
o  feedback sessions with portal users are conducted regularly; 
o  social media sentiment analysis is used. 

4.2.3. 

▪  A process is in place to systematically gather reuse cases. 

▪  Reuse cases are classified according to categories (e.g. environmental, social, 

economic) 

3. 4.3. Created impact 

4.3.1. 

▪  Data on the impact created by open data on governmental challenges is 

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Dimension 4: Open data impact 

available in the country. 

▪  Various reuse examples exist that showcase the impact of open data on: 

o  increasing  government  efficiency  and  effectiveness  in  delivering  public 

services; 

o  increasing the transparency and accountability of public administrations; 
o  enabling better policy- and decision-making. 

4.3.2. 

▪  Data on the impact created by open data on societal challenges is available in 

the country. 

▪  Various reuse examples exist that showcase the impact of open data on: 

o  better including marginalised groups and reducing inequality; 
o  raising awareness of urban housing issues; 
o  raising awareness of health- and well-being-related issues; 
o  raising awareness of educational issues. 

4.3.3. 

▪  Data on the impact created by open data on environmental challenges is 

available in the country. 

▪  Various reuse examples exist that showcase the impact of open data on: 

o  raising awareness of biodiversity-related topics (e.g. air and water quality); 
o  enabling more environmentally friendly cities; 
o  raising awareness of climate change and related disasters; 
o  encouraging lower energy consumption by reducing fuel use and switching to 

renewables. 

4.3.4. 

▪  Data on the impact created by open data on the economy is available in the 

country. 

▪  Various reuse examples exist that showcase the impact of open data on the 

following indicators of economic growth: 

o  employment, 
o  technology and innovation, 
o  entrepreneurship and business creation, 
o  productivity. 

Scoring 

Countries  are  scored  on  a  list  of  questions  relating  to  each  indicator.  Each  question-and-answer 
selection is worth a different number of points. Where relevant, choosing ‘not applicable’ as an answer 
is worth full points, for example when EU legislation does not apply to a country. The scores for the 
individual questions sum together to provide a total score for the indicator. In turn, the indicator scores 
are  added  together  to  give  scores  for  the  dimensions.  The  maximum  scores  for  the  indicators and 
dimensions are shown in the  table  below. The  overall maturity score is calculated as the weighted 
percentage of all the dimensions, meaning that each dimension contributes 25 % towards the overall 
maturity score. 

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Dimension 

Indicator 

Number of scored 
questions 

Policy framework 

Policy 

Governance of open data 

Open data 
implementation 

Portal features 

Portal usage 

Data provision 

Portal sustainability 

Metadata currency and 
completeness 

Monitoring and measures 

DCAT-AP compliance 

Deployment quality and 
linked data 

Portal 

Quality 

Impact 

Strategic awareness 
Measuring reuse 
Created impact 

13 

8 

7 

21 

9 

8 

5 

6 

8 

7 

7 

7 
4 
20 

Maximum 
score per 
indicator 
320 

Maximum 
score per 
dimension 

180 

140 

230 

180 

150 

110 

140 

160 

165 

165 

140 
120 
320 

640 

670 

630 

580 

Pilot indicator: automated metrics of metadata quality 

Metrics  were  extracted  from  the  metadata  quality  assessment  (MQA)  to  quantitatively  evaluate 
metadata  quality.  The  MQA  evaluates  the  quality  of  metadata  of  each  catalogue  harvested  by 
data.europa.eu. 

Five metrics were reported in the MQA as a pilot indicator of ODM quality. The level of compliance 
with  these  five  metrics  was  taken  for  one  catalogue  per  participating  country.  These  metrics  are 
evaluated largely based on the use of specific data catalogue vocabulary application profile (DCAT-AP) 
properties and the content of these properties in relation to specific controlled vocabularies across 
distributions in the catalogue. A summary of the metrics and their definitions is provided in Table 63.

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Table 63: Selected metrics from the metadata quality assessment 

Metric 

What is being measured? 

How is it measured? 

DCAT-AP 
compliance 

compliance 

is 
DCAT-AP 
calculated across all sources and 
datasets 
a 
available 
catalogue.  This  check  is  only 
performed  if  the  metadata  is 
originally  harvested  as  a DCAT-
AP or as a valid derivate. 

in 

DCAT-AP  is  a  specification  for 
describing  linked  public  data  in 
Europe. 

Machine-
readable 

Checks  if  the  format  of  the 
distribution 
machine-
is 
readable. 

The metadata is validated against a set 
of  SHACL  shapes.  The  metadata  is  not 
compliant 
the  SHACL  validation 
if 
reports at least one issue. 

The  MQA  uses  data.europa.eu’s  DCAT-
AP SHACL validation service. 

if  the  specified  format 

The distribution is considered machine-
readable 
is 
corresponding 
contained 
in 
data.europa.eu 
repository 
vocabulary. 

the 
GitLab 

Distribution: dct:format 

DownloadURL  The downloadURL is a direct link 

to the referenced data. 

It is checked whether the property is set 
or not. 

Distribution: dcat:downloadURL 

Licence 
information 

A licence is valuable information 
for the reuse of data. 

Whether  the  property  is  set  or  not  is 
checked. 

Licence 
vocabulary 

limit  the 
like  to 
We  would 
provision  of  incorrect  licence 
information.  For  example,  we 
Creative 
encounter  many 
lack 
Commons 
versioning. 

licences  that 

Distribution: dct:license 
This metric describes all dimensions that 
the  MQA  examines  to  determine  the 
quality.  The  dimensions  are  derived 
based  on  the  principles  of  findability, 
and 
accessibility, 
reusability. 

interoperability 

The  MQA  recommends  and  credits  the 
use  of  controlled  vocabularies.  The 
data.europa.eu  portal  publishes 
its 
controlled  vocabularies  in  GitLab.  The 
vocabularies  are  derived  from  the  EU 
vocabularies. 

Distribution: dct:license 

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Pilot indicator: automated metrics of portal performance 

In addition to gathering qualitative information on portals, there are technical/quantitative ways to 
evaluate portals. These tests extend the scope of ODM through standardised tools. Automated tools 
are online tests through which website URLs are entered and assessed on several criteria. As a pilot, 
four indicators (mobile friendliness, page speed, security and web accessibility) were measured using 
standardised online tests. The home page of the main open data portal reported in the ODM survey 
for each participating country was evaluated. 

Mobile-friendliness 

The mobile-friendliness indicator assesses how well a website is adapted for access on mobile 
devices, ensuring a seamless user experience for visitors on smartphones and tablets. This indicator 
is measured through the Bing Mobile Friendliness Test Tool, which runs checks on the following key 
factors. 

•  Viewport and zoom control configuration. The viewport meta tag needs to be set correctly 
in order for mobile-friendly pages to work well on devices of different sizes and orientations. 
In general, this means that the viewport is set with the content width equal to the device 
width. While it is possible for pages with an alternate viewport configuration to be mobile 
friendly on certain devices, they may not work equally well on all devices. The zoom control 
check verifies if the configuration of the viewport hampers the user’s ability to pinch and 
zoom the page. In general, not using the scale-related viewport settings should result in your 
page being zoomable on most mobile browsers. However, the improper use of these settings 
(user scalable, maximum scale, minimum scale) could result in hampering access to some 
content on the page. Some mobile-friendly pages prevent user zoom by design, and the Bing 
test takes that into account before flagging an error. 

•  Width of page content. In general, the content width should not exceed the screen width. 

The Bing test has some tolerance built in, but any page that requires excessive horizontal 
panning will be flagged for the error ‘Page content does not fit device width’. 

•  Readability of text on the page. It is important to understand that readability is a function 
not just of font size, but also of viewport scaling. It is useful to think of readability as the 
average area occupied by text when the page is fully zoomed out to fit the device’s width. 

•  Spacing of links and other elements on the page. This indicator is related to touch 

friendliness. The Bing test looks at all input elements and hyperlinks on the page to see if 
they occupy an area considered ‘tap-friendly’ at maximum zoom-out. If that is not the case, 
the page will be flagged with ‘Links and tap targets are too small’. 

•  Use of incompatible plug-ins. Another warning that Bing detects is when the page is 

incompatible with plug-ins (e.g. Flash) or the page is otherwise not intended for use on 
mobile devices. The Bing tool detects any error messages that are produced by the page on a 
typical mobile device and currently captures those as warnings in the mobile friendliness 
test. 

Additionally, the tool checks for and reports on resources that are needed to analyse the page fully but 
that the Bing tool was not able to assess due to robots.txt constraints. This way, rendering issues can 
be fixed by webmasters by updating robots.txt in such a way that Bing can accurately determine the 
mobile friendliness of the sites. To analyse a website, the Bing mobile crawler fetches and renders the 
page, extracting important features that are used by the tool to determine how the page performs 

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against each of the above factors. The outcomes are then aggregated to provide a consolidated mobile 
friendliness verdict for the page. 

The scoring is as follows: 

• 
• 

if a website passes all the tests, a score of 100 % is attributed; 
if a website fails any of the tests, a score of 0 % is attributed. 

Speed and performance 

The speed and performance of a website are important parts of its usability. This indicator measures 
a selection of speed and performance standards from Google’s page speed insights. 

The following indicators are included: 

•  Time to interactive is the amount of time it takes for the page to become fully interactive. This 
is an important user-centric metric because it measures how quickly visitors are able to fully 
interact with the page. It measures a page’s load responsiveness and helps identify situations 
in which a page looks interactive but, in fact, it is not. 

•  First contentful paint measures the time from the start of loading to when elements of the 
content  of  the  page  appear  on  the  user’s  screen  (including  images,  text,  scalable  vector 
graphics and non-white elements). It measures the time from when the page is completely 
blank until the first element appears on the screen 
Largest contentful paint measures the time a website takes to show the user the largest piece 
of content on the screen, complete and ready for interaction. 

• 

•  Cumulative layout shift measures the largest burst of layout shift scores for every unexpected 
layout shift that occurs during the entire lifespan of a page. A layout shift occurs whenever a 
visible element changes its position from one rendered frame to the next. 

Each website either passes or fails based on the thresholds set by the tool (Table 64). 

Table 64: Google page speed insights thresholds 

Test 

Time to interactive 

First contentful paint 
Largest contentful paint 

Pass threshold 
Less than 3.8 seconds 

Less than 1.8 seconds 
Less than 2.5 seconds 

Cumulative layout shift 

Less than 0.1 milliseconds 

Security 

All URLs were run through the publicly available security testing tool internet.nl, which was developed 
by the Dutch national government. This tool tests several complementary items, which are considered 
to contribute to basic cybersecurity hygiene. Each test results in either a pass or fail based on whether 
or not the URL meets the requirements set. 

• 

IPv6: reachable through a modern internet address? Overall, this test checks if the website is 
reachable  for  visitors  using  a  modern  address  (IPv6),  making  it  fully  part  of  the  modern 
internet. The test includes the following subtests. 
—  IPv6 addresses for name servers. This test checks if your domain name has at least two 

name servers with an IPv6 address. 

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—  IPv6 reachability of name servers. This test checks if all name servers that have an AAAA 

record with an IPv6 address are reachable through IPv6. 

—  IPv6 addresses for web servers. This test checks if there is at least one AAAA record with 

an IPv6 address for a web server. 

—  IPv6 reachability of web servers. This test checks if it is possible to connect to a web 
server through IPv6 on any available ports (80 and/or 443). Additionally, all IPv6 
addresses that are received from the name servers are tested. A partial score is given if 
not all IPv6 addresses are reachable. If an IPv6 address is (syntactically) invalid, it is 
considered unreachable. 

—  Same website on IPv6 and IPv4. This test compares the response and content received 

from a web server over IPv6 with that received over IPv4. 

•  Domain name system security extensions (DNSSEC): domain name signed? This test checks 
if the domain is signed with a valid signature (DNSSEC). If so, visitors with domain signature 
validation enabled are protected against manipulated translation from the domain into rogue 
internet addresses. 
—  DNSSEC existence checks if the domain, more specifically its start of authority record, is 
DNSSEC signed. If a domain redirects to another domain through a canonical name 
(CNAME), then it also checks if the CNAME domain is signed (which is conformant with 
the DNSSEC standard). If the CNAME domain is not signed, the result of this subtest will 
be negative. 

—  DNSSEC validity checks if the domain, more specifically its start of authority record, is 

signed with a valid signature, making it ‘secure’. 

•  Hypertext transfer protocol secure (HTTPS): secure connection?  Overall, this test checks  if 
information in transit between the website and its visitors is protected against eavesdropping 
and tampering. This includes the following subtests. 
—  HTTPS available checks if the website is reachable on HTTPS. If so, it also checks in the 
below subtests whether HTTPS is configured sufficiently securely in conformance with 
the IT Security Guidelines for Transport Layer Security (TLS) from National Cyber Security 
Centre in the Netherlands. HTTPS guarantees the confidentiality and integrity of the 
information exchanged. Because how (privacy) sensitive and valuable information is 
depends on the situation, a secure HTTPS configuration is important for every website. 
Note that, for performance reasons, the tests in the HTTPS test section are only run for 
the first available IPv6 and IPv4 addresses. 

—  HTTPS redirect checks if a web server automatically redirects visitors from HTTP to HTTPS 
on the same domain (through a 3xx redirect status code like 301 or 302) or if it offers 
support for only HTTPS and not HTTP. If the server does redirect visitors, a domain should 
first upgrade itself by redirecting to its HTTPS version before it redirects to another 
domain. This also ensures that the HTTP strict transport security (HSTS) policy will be 
accepted by the web browser. Note that this subtest is only conducted if the given 
domain correctly redirects from HTTP to HTTPS. An eventual further redirect to a 
different domain (including a subdomain of the tested domain) is not tested. 

—  HTTP compression makes a secure connection with a web server vulnerable to a browser 
Reconnaissance and exfiltration via adaptive compression of hypertext attack. However, 
HTTP compression is commonly used to make more efficient use of the available 
bandwidth. This subtest checks if a web server supports HTTP compression at the root 

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directory level. However, it does not check additional website sources like images and 
scripts. 

—  HSTS checks if your web server supports HSTS. Browsers remember HSTS per 

(sub)domain. Not adding a HSTS header to every (sub)domain (in a redirect chain) may 
leave users vulnerable to man-in-the-middle attacks. Therefore, this subtest checks for 
HSTS on first contact (i.e. before any redirection). 

—  Transport layer security (TLS) version checks if a web server supports only secure TLS 

versions. A web server may support more than one TLS version. 

—  Cyphers (algorithm selections) checks if a web server only supports secure (i.e. ‘good’ 

and/or ‘sufficient’ cyphers (also known as algorithm selections)). An algorithm selection 
consists of cyphers for four cryptographic functions: (a) key exchange, (b) certificate 
verification, (c) bulk encryption and (d) hashing. A web server may support more than 
one algorithm selection. 

—  Cypher order checks if a web server enforces its own cypher preference (‘I’) and offers 

cyphers in accordance with the prescribed ordering (‘II’). 

—  Key exchange parameters checks if the public parameters used in Diffie–Hellman key 

exchange by a web server are secure. 

—  Hash function for key exchange checks if a web server supports secure hash functions to 

create the digital signature during key exchange. 

—  TLS compression checks if a web server supports TLS compression. The use of 

compression can give an attacker information about the secret parts of encrypted 
communication. An attacker that can determine or control parts of the data sent can 
reconstruct the original data by performing a large number of requests. TLS compression 
is used so rarely that disabling it is generally not a problem. 

—  Secure renegotiation checks if a web server supports secure renegotiation. 
—  Client-initiated renegotiation checks if a client (usually a web browser) can initiate a 

renegotiation with a web server. Allowing clients to initiate renegotiation is generally not 
necessary and leaves a web server open to denial-of-service attacks inside a TLS 
connection. An attacker can perform similar denial-of-service attacks without client-
initiated renegotiation by opening many parallel TLS connections, but these are easier to 
detect and defend against using standard mitigation procedures. 

—  Zero round trip time resumption checks if a web server supports zero round trip time 

resumption. 

—  Online Certificate Status Protocol stapling checks if a web server supports the TLS 

certificate status extension, also known as Online Certificate Status Protocol stapling. 
—  Trust chain of certificate checks if it is possible to build a valid chain of trust for a website 
certificate. To have a valid chain of trust, the certificate must be published by a publicly 
trusted certificate authority, and the web server must present all necessary intermediate 
certificates. 

—  Public key of certificate checks if an elliptic curve digital signature algorithm or a Rivest–

Shamir–Adleman algorithm digital signature of a website certificate uses secure 
parameters. 

—  Signature of certificate checks if the signed fingerprint of a website certificate was 

created with a secure hashing algorithm. 

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—  Domain name on certificate checks if the domain name of a website matches the 

domain name on the certificate. 

—  Domain-name-system-based authentication of named entities (DANE) existence checks 
if the name servers of a website domain contain a correctly signed TLS authentication 
record for DANE. As DNSSEC are a precondition for DANE, this test will fail if DNSSEC are 
missing on the website domain or if there are DANE-related DNSSEC issues (e.g. no proof 
of ‘denial of existence’). 

—  DANE validity checks if the DANE fingerprint presented by a domain is valid for the web 

certificate. 

Accessibility foundations 

This indicator evaluates the accessibility status of websites, assessing how usable websites are for a 
large variety of users (regardless of, for instance, their visual abilities). The open-source Axe-core tool 
(browser extension) is used to measure this indicator. This indicator can also be defined as the extent 
to  which  websites  comply  with  the  foundational  parts  of  the  EN 301 549  standard  (web  content 
accessibility guidelines (WCAGs) level AA). 

The tool takes into account the most recent WCAGs and covers 20 of the 50 success criteria, with tests 
across all of the four main principles (perceivability, operability, understandability and robustness). For 
this pilot indictor, the following seven success criteria were measured. 

•  Alternative text (WCAG 1.1.1) evaluates whether a website offers text alternatives for non-
text content, enabling it to be transformed into formats like large print, braille, speech, 
symbols or simplified language to meet diverse user needs. 

•  Colour contrast (WCAG 1.4.3) evaluates if the visual presentation of text and images of text 
on a website has a contrast ratio of at least 4.5:1.Exceptions include cases of large text, text 
or images part of an inactive user interface component and text that is part of a logo or 
brand name. 

•  Page/document title (WCAG 2.4.2) evaluates if a website has titles that describe the topic or 

• 
• 

purpose. 
Link name (WCAG 2.4.4) evaluates the clarity and accessibility of links on a website. 
Language attribute (WCAG 3.1.1) evaluates if the primary language of each web page is 
specified in a way that can be identified by software, such as screen readers and search 
engines. 

•  Valid language code (WCAG 3.1.2) evaluates if the language of each passage or phrase in a 
website’s content can be identified and defined by software, allowing assistive technologies 
(e.g. screen readers) to accurately convey content in the appropriate language. 

•  Name, role and value (WCAG: 4.1.2) evaluates the accessibility and compatibility of user 

interface components of a website with assistive technologies. 

If no violations are found, the  website  is at least  potentially accessible. If violations are found, the 
website is at least not fully accessible. The tool reports on the number and types of violations found. 

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ISBN: 978-92-78-44708-3 

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