among others, regular meetings, training sessions, workshops, or other events to establish a common understanding on the importance of high-quality data publication.

In France, various activities are carried out to assist data providers. Since 2021, Etalab - the French open data team - provides a tool called "publier.etalab.studio"<fnref n="258" /> to help portal users generate their data in a structured way. This tool helps to get better quality of the data published on the French open data portal. In addition, Etalab is making special efforts to better support data producers in their publication procedures through quality guides<fnref n="259" />. The guides cover legal, technical, or organisational themes and are conceived in an iterative and open manner. The guides insist on the publication of high-quality metadata<fnref n="260" />, and complements the portal's comprehensive documentation<fnref n="261" />.

In Ireland, the Irish Open Data Technical Framework was revised in 2021 and the new "Open Data Publication Guidelines"<fnref n="262" /> document was published. In the revised guidelines, the focus is on recommending best practices that will:

* Ensure the discoverability and accessibility of data,

* Empower people to understand and use data,

* Support increased public-service transparency,

* Drive evidence-based decision making and innovation, and

* Enable measurable impact.

Additionally, events are held to assist data providers in the publication of high-quality metadata. For example, in March 2021 a webinar for data providers was held focusing on "Preparing for the Open Data and Reuse of PSI Directive"<fnref n="263" /> and in December 2020 an Open Data Conference for publishers was held, focusing on data quality and impact.

## 4.3 DCAT-AP compliance

DCAT is a W3C standard designed to facilitate interoperability between data catalogues published on the web.<fnref n="264" /> DCAT-AP is an extension to DCAT – an “application profile” – that was developed by the European Commission specifically to improve interoperability and foster discoverability and re-use of open data across European catalogues.<fnref n="265" /> Compliance to DCAT-AP is increasingly recognised among the Member States. The DCAT-AP compliance indicator examines the extent to which metadata complies with the DCAT-AP standard for describing public sector datasets and what efforts are taken

<footnote n="258">²⁵⁸ https://publier.etalab.studio</footnote>

<footnote n="259">²⁵⁹ https://guides.etalab.gouv.fr/qualite/</footnote>

<footnote n="260">²⁶⁰ https://guides.etalab.gouv.fr/qualite/documenter-les-donnees/#description-du-mode-de-production-donnees</footnote>

<footnote n="261">²⁶¹ https://doc.data.gouv.fr/jeux-de-donnees/publier-un-jeu-de-donnees/</footnote>

<footnote n="262">²⁶² https://data.gov.ie/uploads/page_images/2021-05-11-144708.586537Open-Data-Publication-Guidelines-2021.pdf</footnote>

<footnote n="263">²⁶³ https://www.eventbrite.co.uk/e/its-time-to-open-preparing-for-new-open-data-and-reuse-of-psi-directive-tickets-143034131939</footnote>

<footnote n="264">²⁶⁴ https://www.w3.org/TR/vocab-dcat-2/</footnote>

<footnote n="265">²⁶⁵ For more information see https://joinup.ec.europa.eu/collection/semantic-interoperability-community-semantic/solution/dcat-application-profile-data-portals-europe and data.europa.eu's (formerly European Data Portal) Open Data Goldbook for Data Managers and Data Holders at https://data.europa.eu/en/training/data-providers-guide</footnote>
to assist data publishers in ensuring compliance with DCAT-AP. Also, it considers the availability of
recommended and optional classes.

4.3.1 Assisting data providers to be DCAT-AP compliant

85% of Member States provide their data suppliers with documentation on DCAT-AP. Documentation can consist of Member States' own developed documentation, factsheets provided by data.europa.eu, or materials published on websites hosted by the European Commission, such as the JoinUp Platform<fnref n="266" />.

In Sweden, a new website<fnref n="267" /> was launched last year to summarise the collection of available documentation. Specifically, it contains documentation such as “Harvesting specifications”<fnref n="268" />, “DCAT-AP-SE RDF examples”<fnref n="269" />, and “DCAT-AP recommendations per field”<fnref n="270" />.

In Spain, the metadata audits carried out for public bodies are based on the Metadata Quality Assessment (MQA) proposed by data.europa.eu²⁷¹. In the last year, several articles with relevant links to DCAT-AP have been published, such as “DCAT-AP 2.0.1: How has the European reference specification for the description of open data catalogues evolved?”<fnref n="272" />, “Why are data vocabularies important?”²⁷³ and “The importance of data cataloguing”<fnref n="274" /> in addition to the other documentation<fnref n="275" /> that assists data providers to be DCAT-AP compliant.

4.3.2 Investigating causes for a lack of DCAT-AP compliance

The importance of DCAT-AP for national data portals is also evident from the efforts taken to investigate the most common causes for lack of compliance. 78% of Member States investigate this and some examples of the main causes are included below.

Some countries, such as Croatia and Slovenia, indicate that more than 90% of metadata is compliant with DCAT-AP, so these countries do not see the urgency of having a detailed research into the lack of compliance.

In Germany, some of the causes mentioned are a general lack of knowledge about Linked-Open-Data, problems in using correct URLs, difficulties with mapping the right themes on the datasets, a lack of upgrading on newer versions of DCAT-AP and DCAT-AP.de as well as problems with limitations according to the software, for example CKAN.

In Spain, the main discrepancies in DCAT-AP compliance are due to the fact that the “Technical Interoperability Standard for the Reuse of Information Resources”<fnref n="276" /> is developed prior to the DCAT-AP specification. This standard does not derive from the use of metadata but from the controlled

<footnote n="266">266 https://joinup.ec.europa.eu/</footnote>

<footnote n="267">²⁶⁷ https://docs.dataportal.se/</footnote>

<footnote n="268">²⁶⁸ https://docs.dataportal.se/dcat/docs/harvesting/</footnote>

<footnote n="269">²⁶⁹ https://docs.dataportal.se/dcat/docs/examples/</footnote>

<footnote n="270">²⁷⁰ https://docs.dataportal.se/dcat/docs/recommendations/</footnote>

<footnote>https://data.europa.eu/mqa/?locale=en</footnote>

<footnote n="272">272 https://datos.gob.es/es/blog/dcat-ap-201-como-ha-evolucionado-la-especificacion-de-referencia-europea-para-la-descripción-de</footnote>

<footnote>https://datos.gob.es/es/blog/vocabularios-de-datos-por-que-son-importantes</footnote>

<footnote n="274">²⁷⁴ https://datos.gob.es/es/blog/importancia-de-la-catalogacion-de-datos</footnote>

<footnote n="275">²⁷⁵ https://datos.gob.es/es/documentacion/recursos-disponibles-para-conocer-mas-sobre-dcat-ap</footnote>

<footnote n="276">²⁷⁶ https://joinup.ec.europa.eu/collection/egovernment/document/es-technical-interoperability-standard-public-sector-information-reuse</footnote>
vocabularies used to identify data subjects, publishing entities, and geographical coverage. A level of detail is required at the national level that is not addressed in DCAT-AP.

In Sweden, the most common causes for a lack of DCAT-AP compliance are lack of technical skills and understanding to set up the RDF catalogue including the metadata harvesting. This is the prime reason why the Swedish team has updated the national DCAT-AP-SE and invested resources the last year to establish the technical framework and all the technical documentation, recommendations, and sandbox environment.

### 4.3.3 Compliance with DCAT-AP mandatory, recommended, and optional classes

In 70% of Member States, it is declared that more than 90% of the metadata is compliant to mandatory DCAT-AP classes (agent, catalogue, dataset, literal, resource). In 56% of Member States, more than 90% of the metadata is assumed to meet the standards of recommended classes (category, category scheme, distribution, license document), and in 41% of Member States, more than 90% of the metadata meets the standards of optional classes (catalogue record, checksum, document, frequency). Similar to last years, countries are focusing on compliance by providing metadata for the mandatory classes but invest less effort in recommended and optional classes. Figure 31 shows the percentage of metadata on national data portals in Europe declared to be DCAT-AP compliant as well as the recommended and optional classes.

<figure><img src="image_35.png" /><figcaption>Figure 31: Percentage of metadata compliant with DCAT-AP and using recommended or optional classes</figcaption></figure>
## 4.4 Deployment quality and linked data

This indicator examines the extent to which countries use a model, for example the “5-Star Open Data”<sup>277</sup> or the “FAIR Principles”<sup>278</sup>, to assess the quality of data deployment. This indicator assesses to what extent data is available under an open licence, in the form of structured data, machine-readable, using Uniform Resource Identifiers (URIs), and including links to other data sources.

### 4.4.1 Deployment quality models

78% of Member States use a model to assess the quality of data deployment. Most countries mention using the 5-Star Open Data model to the point of occasionally using it as a decision-making tool to determine which datasets are allowed to be published on their portal. Even more Member States (83%) also conducts activities to promote and familiarise data providers with ways to ensure higher quality data, such as promoting their chosen model.

Most countries, such as Austria, Cyprus, Italy, Malta, Romania, and Slovenia, use the 5-Star Open Data model.

In Lithuania, the 5-Star Open Data model is used as well. At the dataset level, the stars are assigned based on distribution format used. At individual data field level, however, stars from 0 to 3 are assigned manually, and 4 and 5 are detected automatically by checking if a data model has a reference to another data model and if an association with external vocabulary is provided. This way, first at dataset level, Lithuania has a very approximate rating, but on data fields level, there is a very precise rating.

In Sweden, the Swedish Research Council<sup>279</sup> coordinates Swedish efforts regarding open access to research data and publications and have established criteria for evaluating that data publication are according to the FAIR principles.<sup>280</sup> Good data management is a key component of open access to research data, and a cornerstone for FAIR. Using a Data Management Plan (DMP), researchers can describe how data are collected and/or created, how they will be handled during the course of the research, and how they will be taken care of afterwards. As from 2019, all those awarded grants by the Swedish Research Council need to produce such a plan. The national principles for data re-use from public sector bodies are developed in line with FAIR principles but are established on a more practical level.<sup>281</sup>

### 4.4.2 Deployment quality

Below, an overview is given on the extent to which data is available under an open licence, in the form of structured data, machine-readable, using URIs, and including links to other data sources.

<footnote n="277"><sup>277</sup> For more information: http://5stardata.info/en/ or https://joinup.ec.europa.eu/sites/default/files/inline-files/W3C04.pdf</footnote>

<footnote n="278"><sup>278</sup> https://www.go-fair.org/fair-principles/</footnote>

<footnote n="279"><sup>279</sup> The Swedish Research Council is Sweden's largest governmental research funding body, and supports research of the highest quality within all scientific fields, see https://www.vr.se/english.html</footnote>

<footnote n="280"><sup>280</sup> https://www.vr.se/english/mandates/open-science/open-access-to-research-data/faq-on-open-access-to-research-data.html</footnote>

<footnote n="281"><sup>281</sup> https://www.digg.se/utveckling-av-digital-forvaltning/oppna-och-delade-data/offentliga-aktorer/nationella-principer</footnote>
## Open licence

This indicator examines if data is accompanied by open licensing information. The majority of Member States (81%) have more than 90% of the published data made available under an open licence. In figure 32, the percentage of data available under an open licence is shown.

In some countries, the national portal does not only make open data available, but also documents the availability of more “closed” data - pursuing a more holistic approach to data sharing. The data may be available to citizens and organisations under more restrictive terms that need to be assessed on a case-by-case basis. Countries such as the Netherlands also document the existence of datasets that are completely confidential, to help re-users understand that the data does exist but simply cannot be made available, for any reason.

<figure><img src="image_36.png" /><figcaption>Figure 32: Percentage of datasets available with open licence</figcaption></figure>

## Structured format

56% of Member States offer more than 90% of the published data available in a structured format in addition to having an open licence. In figure 33, the distribution of the percentages of published data available in a structured format is shown.

<figure><img src="image_37.png" /><figcaption>Figure 33: Percentage of datasets available in a structured format</figcaption></figure>
## Machine-readable format

In figure 34, the distribution of the percentage of published data available in a machine-readable format is shown. 44% of Member States offer more than 90% of the published data available in a machine-readable format in addition to having a structured format and an open licence.

<figure><img src="image_38.png" /><figcaption>Figure 34: Percentage of datasets available in machine-readable format</figcaption></figure>

## Uniform Resource Identifiers (URIs)

In figure 35, the distribution of the percentage of published data available using Unique Resource Identifiers (URIs) is shown. 22% of Member States offer more than 90% of the published data available that consistently use URIs in addition to being in a machine-readable, structured format with an open licence.

<figure><img src="image_39.png" /><figcaption>Figure 35: Percentage of datasets available using URIs</figcaption></figure>

## Linked data

Finally, figure 36, shows the distribution of the percentage of published data that is also linked to other renowned sources. Only 2 (7%) Member States have more than 90% of the published data available that as linked data in addition to consistently using URIs, in a machine-readable, structured format, and with an open licence.
<figure><img src="image_40.png" /><figcaption>Figure 36: Percentage of datasets available as linked data</figcaption></figure>

## 4.5 Overall performance

Since a steep increase in last year's assessment, the average maturity score on the quality dimension has not increased significantly in 2021, see figure 37. With an average score of 77% the Member States show a continued desire to not just consider the quantity of open data that is made available, but also to focus on the quality of the data that is published, though there is still plenty of room for improvement.

<figure><img src="image_41.png" /><figcaption>Figure 37: Development in maturity of the quality dimension over the last years</figcaption></figure>

Figure 38 shows the score per indicator of the quality dimension compared to 2020. The first three indicators show an increase compared to last year. It is becoming more important to ensure timely and complete data and metadata. This is emphasised by the increasing focus on monitoring and measuring the quality of open data by the Member States' national open data team. They also provide guidance on licensing and assist data providers in the publication of high-quality metadata. Information on the importance of DCAT-AP compliance is provided to data publishers and several countries have developed their own national extensions of the DCAT-AP standard. Countries also often investigate
what the common causes are for lack of compliance and take action where necessary. The indicator deployment quality and linked data shows a decreased average score compared to last year.

<figure><img src="image_42.png" /><figcaption>Figure 38: Maturity score per quality indicator compared to last year</figcaption></figure>

The country ranking of the quality dimension can be observed in Figure 39. The figure shows that 17 Member States score above the EU27 average of 77% and 10 Member States scored below. The countries with the highest maturity levels on the portal dimension are France (94%), Ireland (92%), and Slovenia (92%).

<figure><img src="image_43.png" /><figcaption>Figure 39: Country ranking for the quality dimension</figcaption></figure>
# Chapter 5: Open Data Maturity in the EFTA and Other Countries

Similar to previous years, the open data landscaping exercise also assesses the open data maturity in European countries outside the EU27.

This chapter provides a brief overview on the open data maturity of two groups of countries outside the EU27. The first group focuses on the European Free Trade Association (EFTA) and the three countries that participated this year: Iceland, Norway, and Switzerland. The second group is made of two “Eastern Partnership” countries (EaP): Georgia and Ukraine, and additionally includes Montenegro and the United Kingdom (UK). This chapter follows the same structure of the four open data maturity dimensions: policy, impact, portal, and quality.

## 5.1 Open data policy

### 5.1.1 EFTA countries

#### Policy framework

In 2021, two of the participating EFTA countries have an open data policy in place: Iceland and Norway. Nevertheless, all EFTA countries implemented an open data strategy including an action plan. Additionally, all EFTA countries indicate that their open data policy or strategy outlines measures to support the re-use of open data by both the public and the private sector. Finally, in all EFTA countries have high-value domains or datasets been identified and prioritised for publication, where Norway and Switzerland have measures in place to involve relevant stakeholders in this prioritisation process.

In Iceland, the "Act on the reuse of public information"<fnref n="282" /> outlines the country's open data legislation. Also, open data is a fundamental topic in the "Digital Services Policy" which was published in May 2021²⁸³. Finally, the in 2020 published innovation strategy includes an action plan to increase the re-use of open data<fnref n="284" />.

As already explained in last year's assessments, the Norwegian open data policy is captured in the available guidelines for making public data available.<fnref n="285" /> Their national open data strategy is spread over several documents, among which the newly published "National Strategy for Artificial Intelligence"<fnref n="286" /> or "Data as a resource: Data-driven economy and innovation"<fnref n="287" />.

In Switzerland, the "Open Government Data Strategy" provides a detailed description of the plan for the years 2019-2023.<fnref n="288" /> The annex of the document includes an action plan with five defined objectives to reach their strategic goals, such as supporting and encouraging the re-use of open data and creating an overview of the open data inventories.

<footnote n="282">²⁸² https://www.althingi.is/lagas/nuna/2018045.html</footnote>

<footnote n="283">²⁸³ https://samradsgatt.island.is/oll-mal/$Cases/Details/?id=2968</footnote>

<footnote n="284">²⁸⁴ https://opinbernyskopun.island.is/wp-content/uploads/2020/03/A%C3%B0ger%C3%B0a%C3%A1%C3%A6tlun-um-opinbera-n%C3%BDsk%C3%B6pun.pdf</footnote>

<footnote n="285">²⁸⁵ https://www.regjeringen.no/no/dokumenter/retningslinjer-ved-tilgjengeliggjoring-av-offentlige-data/id2536870/</footnote>

<footnote n="286">²⁸⁶ https://www.regjeringen.no/en/dokumenter/nasjonal-strategi-for-kunstig-intelligens/id2685594/?ch=4#id0020</footnote>

<footnote n="287">²⁸⁷ https://www.regjeringen.no/no/dokumenter/meld.-st.-22-20202021/id2841118/</footnote>

<footnote n="288">²⁸⁸ https://www.fedlex.admin.ch/eli/fga/2019/125/de</footnote>
Governance of open data

In 2021, not only Switzerland, but also Norway indicates to have an open data governance structure in place to enable the inclusion of open data stakeholders. The governance structures apply a hybrid approach between bottom-up and top-down approaches. In both countries, the governance structure assists data providers in their publication process. Only in Switzerland official open data roles are appointed in the form of “data coordinators”.

In Norway, several governance structures co-exist for different data sharing areas. These governance structures, on its turn, are implemented by various stakeholders from both the public and private sector.

289

Although Iceland does not have a governance structure in place, their open data policy explains how to re-use open data according to the law. Also, “Digital Iceland” appoints civil servants to support with opening data via their national portal.<fnref n="290" />

Furthermore, in all EFTA countries a regular exchange of knowledge or experiences takes place both among public sector bodies, as well as between public sector bodies and open data re-users. In order to promote open data, multiple events are being organised in the countries by mixture of local, regional, national public and private sector bodies.

Open data implementation

All three EFTA countries have a document or tool at the national level to assist data providers in their publication process. In Iceland a best practice guide for API development has been created<fnref n="291" />, in Norway a guide for making open data available is offered<fnref n="292" />, and in Switzerland an open data handbook has been established<fnref n="293" />. Additionally, all countries have processes in place to monitor the implementation of the open data plans, such as monitoring and recurring gatherings. As a result, all countries consider the status of their open data implementation satisfactory.

All EFTA countries harvest local or regional data sources on their national open data portal. Where in Iceland a few existing local or regional sources are harvested, are the majority of local and regional datasets harvested in Norway and Switzerland.

Finally, Norway and Switzerland offer professional development or a training plan for civil servants working with open data. In Switzerland the trainings activities are integrated in some of the universities' curriculum and therefore receive a publicly recognised certificate after completion.

The Norwegian Directorate for ICT and Joint Services in Higher Education & Research<fnref n="294" /> has together with Digital Norway<fnref n="295" /> launched a digital learning platform, which also covers data and related topics.<fnref n="296" />

<footnote n="289">289 See https://www.digdir.no/digitalisering-og-samordning/sentralt-styringsdokument-prosjekt-deling-av-data/2598 and https://www.digdir.no/digitalisering-og-samordning/mandat-skate/1261</footnote>

<footnote n="290">290 More information can be found at https://joinup.ec.europa.eu/sites/default/files/inline-files/Digital PUBLIC Administration Factsheets Iceland vFINAL.pdf</footnote>

<footnote n="291">291 https://docs.devland.is/technical-overview/api-design-guide</footnote>

<footnote n="292">292 https://data.norge.no/guide/veileder-apne-data/</footnote>

<footnote n="293">293 https://handbook.opendata.swiss</footnote>

<footnote n="294">294 Directorate for ICT and Joint Services in Higher Education & Research: https://www.unit.no/en/about-unit-0</footnote>

<footnote n="295">295 Digital Norway: https://digitalnorway.com/</footnote>

<footnote n="296">296 https://digitalnorway.com/kurs/</footnote>
5.1.2 EaP countries, Montenegro, and the United Kingdom

Policy framework

Of the remaining participating countries, Montenegro, Ukraine, and the UK have an open data policy in place including an action plan with measures to be implemented in the field of open data. Ukraine and the UK also implemented an open data strategy. Montenegro, Ukraine, and the UK indicate that their open data policy or strategy outlines measures to support the re-use of open data by both the public and the private sector.

In Montenegro, the “Law on Free Access to Information from 2017” prescribes the obligation of public authorities to publish data in an open format on the open data.<fnref n="297" /> Furthermore, a new strategy for public administration reform 2022-2026 is being developed as the previous strategy expired. One of the strategic goals is a transparent and inclusive public administration that explicitly includes open data.

In Ukraine, a new “Open Data Strategy 2021-2025” is being developed and is expected to be adopted late 2021.<fnref n="298" /> The strategy will include definitions of fundamental terms (such as public information, information provider, open data impact, etc.), aims and goals to be reached, instruments of the open data policy, and a description of the current situation including opportunities and challenges in the field of open data.

In the UK, since the introduction of open data in the 2012 White Paper, ‘Unleashing the Potential<fnref n="299" />’, the government has adopted the policy of ‘Open by Default’ for public sector data across all departments. In December 2020, the UK adopted the “National Data Strategy”<fnref n="300" /> with the aim to improve data use in government. In the field of open data, the strategy aims to review the open data publication and decision-making processes to ensure their consistency and to continue the implementation of the “Energy Data Taskforce”<fnref n="301" />.

Furthermore, in Georgia, Montenegro, and Ukraine high value domains or datasets have been identified and prioritised for publication and measures are in place to assist other stakeholders’ involvement in this prioritisation process.

Governance of open data

All countries have a governance structure in place that enables the participation and inclusion of various open data stakeholders. Except from Georgia, all countries published the governance structure online. In Montenegro a top-down approach is used to govern open data, while in the other countries a hybrid model between a top-down and bottom-up approach is used. In all countries, assistance is being provided to support data providers with their data publication process. In Montenegro, Ukraine, and the UK the governance structure appoints official roles in civil service dedicated to open data.

In Georgia, the “Digital Governance Agency”<fnref n="302" /> is responsible to define the unified standard for data publishing and to ensure the availability of open data through the national open data portal.

<footnote n="297">297 https://www.ombudsman.co.me/spi/1613568996_zakon-o-slobodnom-pristupu-informacijama-1.pdf</footnote>

<footnote n="298">²⁹⁸ The draft is published for discussion:
https://docs.google.com/document/d/1r8KK3_GqEbfYklPrBiQGmEuJ8CaMqQnvfgEXlvAXK0I/edit?usp=sharing</footnote>

<footnote n="299">299 https://www.gov.uk/government/publications/open-data-white-paper-unleashing-the-potential</footnote>

<footnote n="300">³⁰⁰ See section 6.1.3, available at https://www.gov.uk/government/publications/uk-national-data-strategy/national-data-strategy</footnote>

<footnote n="301">301 https://innovateuk.blog.gov.uk/2020/05/29/modernising-energy-data-access-and-the-winners-are/</footnote>

<footnote n="302">³⁰² https://www.facebook.com/dga.gov.ge/</footnote>
In Ukraine, the Ministry of Digital Transformation 303 is the body responsible for the developments in the field of open data. Since the creation of the Ministry in 2019, the position of the "Chief Digital Transformation Officer" was introduced, who is responsible for the coordination of the open data sphere. Furthermore, each public body must appoint the person responsible for providing support in the open data publication process.

In all countries the exchange of knowledge and experiences takes place between different public sector bodies. In Montenegro and Ukraine this exchange takes also place between public sector bodies and open data re-users. In all countries open data is being promoted at events, which are organised by a mixture of local, regional, national public and private sector bodies.

## Open data implementation

In Montenegro, Ukraine, and the UK a document, such as a guidebook, is in place at the national level to assist data providers in their publication process, including publication plans at local, regional, or national level. In Ukraine and the UK processes are run to ensure that the open data plans are implemented, such as quarterly or monthly reporting. As a result, in Ukraine the implementation of the publication plans can be described as satisfactory, and in the UK as neutral.

The national open data portals of Ukraine and the UK harvest all datasets from local and regional data sources. In Montenegro data providers can manually post data on the portal, but the harvesting has not started yet.

Furthermore, in Montenegro, Ukraine, and the UK a professional development or training plan is offered to civil servants working with data. After completing these plans or training activities, certification is offered which is recognised within public bodies.

In Ukraine, a certified advanced training programme was launched, the "Open Data for Civil Servants: A Practical Course." The programme aims to increase the competency of officials from public authorities and local governments who are responsible for the disclosure of public information in the form of open data and covers 18 different topics.304 As a measure to develop professional skills of civil servants working with data is the online course "Open Data for Civil Servants" created.305 The course was launched in September 2020 and, at the moment of filling in the questionnaire, 16 thousand government officials completed the course.

## 5.2 Open data impact

### 5.2.1 EFTA countries

#### Strategic awareness

All participating EFTA countries observe a focus on understanding the level of re-use of their country's open data at the national level. Although this focus is limited in Iceland and Switzerland, in Norway there is a strong focus on understanding the level of open data re-use. Both Norway and Switzerland run processes at the national level to estimate the level of re-use in the form of, among others, the

<footnote n="303">303 Ministry of Digital Transformation: https://www.kmu.gov.ua/en/yevropejska-integraciya/coordination/cifrova-transformaciya</footnote>

<footnote n="304">304 https://pdp.nacs.gov.ua/courses/vidkryti-dani-dlia-derzhsluzhbovtsiv-praktychnyi-kurs</footnote>

<footnote n="305">305 https://osvita.diia.gov.ua/courses/open-data</footnote>
use of web analytics on their national portal. None of the EFTA countries have incentives in place for public bodies or civil servants to estimate the level of re-use of their own open data.

Norway and Switzerland have defined within their country what 'impact of open data' means. Norway is the only country to have a methodology in place to estimate the open data impact, and to have conducted studies in the past year to estimate the level of open data impact.

The Norwegian Institute of Transport Economics (TØI) <fnref n="306" /> has been responsible for a research on the impact of open science in the European "BE OPEN" project<fnref n="307" />. The report includes open data impact on social, environmental, and economic areas.<fnref n="308" /> In Norway, they are investigating whether this method can be the starting point for a national framework.

Furthermore, all EFTA countries indicate to have civil society initiatives in place that are open data driven and aim to create impact, such as hackathons. Also, in all EFTA countries there is collaboration between government and civil society or academia to create open data impact.

## Political impact

In 2021, Norway was the only EFTA country who performed activities to assess the political impact of open data. They launched 'data as a resource', which aims to develop a common methodology for measuring and demonstrating the benefits and effects of public data, based on the work done in the EU and the OECD in this area.<fnref n="309" />

The table below represents the components that influenced the level of political impact of open data in the EFTA countries.

<table><thead><tr><th colspan="4">Level of Political Impact</th></tr><tr><th></th><th>Iceland</th><th>Norway</th><th>Switzerland</th></tr></thead><tbody><tr><td>Increasing government effectiveness</td><td>Medium</td><td>High</td><td>--</td></tr><tr><td>Increasing government efficiency</td><td>--</td><td>High</td><td>Medium</td></tr><tr><td>Increasing transparency and accountability</td><td>High</td><td>High</td><td>Medium</td></tr></tbody></table>

In Norway, the open data impact on increasing government effectiveness improved from medium to high in 2021. This is related to all invoicing having better quality due to the availability of a company register information about private organisations and public bodies. <fnref n="310" />

## Social impact

Norway is the only participating EFTA country to perform activities in 2021 to monitor the social impact of open data. Remarkable is the effort that all the EFTA countries put in creating value from open data in the fight against the current COVID-19 pandemic. The table below represents the components that influenced the level of social impact of open data in the EFTA countries. As can be seen, all countries indicate that open data has a high impact on raising awareness on health and well-being related issues.

<footnote n="306">³⁰⁶ Institute of Transport Economics (TØI): https://www.toi.no/about-toi/category26.html</footnote>

<footnote n="307">³⁰⁷ https://beopen-project.eu/</footnote>

<footnote n="308">³⁰⁸ https://beopen-project.eu/storage/files/beopen-d53-impact-assessment-of-open-science-in-transport.pdf</footnote>

<footnote n="309">³⁰⁹ https://www.regjeringen.no/no/dokumenter/meld.-st.-22-20202021/id2841118/?ch=5#kap5-7</footnote>

<footnote n="310">³¹⁰ See for example https://data.norge.no/datasets/5a5374c3-c6a7-49f8-b9cc-0a9e48c1acd7 or https://data.norge.no/datasets/68d08f28-a16d-4fab-a953-ed4ab08ce2e2</footnote>
Level of Social Impact

<table><thead><tr><th></th><th>Iceland</th><th>Norway</th><th>Switzerland</th></tr></thead><tbody><tr><td>Inclusion of marginalised groups</td><td>--</td><td>High</td><td>--</td></tr><tr><td>Raising awareness concerning housing in the city</td><td>High</td><td>High</td><td>--</td></tr><tr><td>Raising awareness on health and well-being</td><td>High</td><td>High</td><td>High</td></tr></tbody></table>

All EFTA countries created a COVID-19 dashboard to visualise the latest numbers on the spread of the virus.<sup>311,312,313</sup> In Norway, open data has been used throughout the pandemic, both by central government and by local authorities. An example is the municipalities' dashboard for infection tracking. The municipalities also have more advanced dashboards for internal use, such as planning, quarantines etc.

Environmental impact

Norway was the only participating EFTA country who performed activities in the past year to monitor the level of environmental impact of open data. The Norwegian Environment Agency<sup>314</sup> is systematically monitoring the environmental impact by publishing and producing studies.<sup>315</sup> The table below represents the components that influenced the level of environmental impact of open data in the EFTA countries.

Level of Environmental Impact

<table><thead><tr><th></th><th>Iceland</th><th>Norway</th><th>Switzerland</th></tr></thead><tbody><tr><td>Raising awareness on water and/or air quality</td><td>High</td><td>High</td><td>Medium</td></tr><tr><td>Raising awareness on noise levels in cities</td><td>Medium</td><td>Medium</td><td>--</td></tr><tr><td>Waste management</td><td>High</td><td>High</td><td>Medium</td></tr><tr><td>Environmental-friendly transport systems in cities</td><td>Medium</td><td>High</td><td>Medium</td></tr></tbody></table>

In Norway, different initiatives have been set up to raise awareness on noise levels in cities. The Norwegian Environment Agency has developed a map that allows the public to investigate the noise level in the cities.<sup>316</sup> Also, the municipality of Stavanger has published open datasets that allows the public to check out different noise levels.<sup>317</sup>

Economic impact

Norway is the only participating performed activities to monitor the economic impact of open data. Menon Economic conducted a study, on behalf of the Confederation of Norwegian Enterprise (NHO)<sup>318</sup>,

<footnote n="311"><sup>311</sup> COVID-19 dashboard Switzerland: https://www.covid19.admin.ch/de/overview.</footnote>

<footnote n="312"><sup>312</sup> COVID-19 dashboard Iceland: https://www.covid.is.</footnote>

<footnote n="313"><sup>313</sup> COVID-19 dashboard Norway: https://experience.arcgis.com/experience/742a281a0fa74ab79147a76e6b52833b</footnote>

<footnote n="314"><sup>314</sup> Environment Agency: https://www/environmentagency.no/</footnote>

<footnote n="315"><sup>315</sup> https://cmsapi-data.miljodirektoratet.no/var-datapolitikk/</footnote>

<footnote n="316"><sup>316</sup> https://miljostatus.miljodirektoratet.no/tema/forurensning/stoy/</footnote>

<footnote n="317"><sup>317</sup> https://open.stavanger.kommune.no/dataset/stoy-jernbane</footnote>

<footnote n="318"><sup>318</sup> Confederation of Norwegian Enterprise (NHO): https://www.nho.no/en/</footnote>
to monitor the economic impact of open data.<fnref n="319" /> The table below represents the components that influenced the level of economic impact of open data in the EFTA countries.

<table><thead><tr><th colspan="4">Level of Economic Impact</th></tr><tr><th></th><th>Iceland</th><th>Norway</th><th>Switzerland</th></tr></thead><tbody><tr><th>Macro-economic impact of open data</th><td>High</td><td>High</td><td>--</td></tr><tr><th>Micro-economic impact of open data</th><td>Medium</td><td>High</td><td>--</td></tr><tr><th>Economic benefits for public administrations</th><td>High</td><td>High</td><td>--</td></tr></tbody></table>

In Iceland, the majority of government economic research is on the macroeconomic level and relies on open data. These studies form the basis for macroeconomic policy making and facilitates a healthy public debate on the government's economic policy. Examples of the usage of open data in economic research and analysis can be seen in working papers and regular publications by the Central Bank of Iceland and the government's fiscal plans and budgets.<fnref n="320" />

### 5.2.2 EaP countries, Montenegro and the United Kingdom

#### Strategic awareness

Montenegro, Ukraine and the UK indicate that they observe a strong focus on understanding the level of re-use of their country's open data. Only Georgia did not observe this focus and is also the only country to not have processes running to estimate the level of re-use in their country. Ukraine and the UK have incentives or obligations in place for public bodies or civil servants to estimate the level of re-use in their own open data.

For example, in Ukraine, a yearly survey for users is conducted by the Ministry of digital Transformation<fnref n="321" />. The analysis of the most recently conducted survey was published in May 2021.<fnref n="322" /> The results of the survey, in which more than 500 respondents took part, showed that the Ukrainian data portal, data.gov.ua, is a useful entry point into the world of open data for representatives of various spheres of employment, from business representatives to civil servants and academia.

Only in the UK has the government defined what 'impact of open data' means in their national data strategy.<fnref n="323" /> Ukraine is the only country where a methodology is developed to estimate the impact of open data. In Ukraine and Montenegro are studies conducted in the past year to assess the impact of open data.

<footnote n="319">³¹⁹ https://www.nho.no/publikasjoner/veikart/er-verdiskaping-med-data-noe-norge-kan-leve-av/2019-88-Verdiskaping-med-data.pdf</footnote>

<footnote n="320">³²⁰ For example, https://www.cb.is/publications/publications/publications-all-archive/?all=1 or https://www.cb.is/publications/publications/publications-all-archive/?all=1&newscat=0b5b3895-35dc-11e5-93ff-005056bc2afe</footnote>

<footnote n="321">³²¹ Ministry of digital Transformation: https://thedigital.gov.ua/</footnote>

<footnote n="322">³²² The survey: https://diia.data.gov.ua/news/do-uvahy-korystuvachiv-datagovua, and the report: https://diia.data.gov.ua/news/provedeno-opituvannya-koristuvaciv-jedinogo-derzavnogo-veb-portalu-vidkritix-danix</footnote>

<footnote n="323">³²³ https://www.gov.uk/government/publications/uk-national-data-strategy/national-data-strategy</footnote>
The Ministry of Digital Transformation<fnref n="324" /> and Transparency and Accountability in Public Administration and Services (TAPAS)<fnref n="325" /> developed a qualitative approach by utilising international best practices. They launched a series of research on anti-corruption and social impact of open data in different sectors of Ukraine.<fnref n="326" />

Finally, in all countries is there a collaboration between government and civil society or academia to create open data impact. Montenegro is the only country to not have civil society initiatives to create open data impact that are open data driven.

## Political impact

Ukraine is the only country where public bodies launched activities in the past year to assess the political impact of open data, such as the aforementioned research. Ukraine and the UK are the only countries where open data is used in policy-making processes and in decision-making processes. The table below represents the components that influenced the level of political impact of open data in the EaP countries, Montenegro, and the UK.

<table><thead><tr><th colspan="5">Level of Political Impact</th></tr><tr><th></th><th>Georgia</th><th>Montenegro</th><th>Ukraine</th><th>The UK</th></tr></thead><tbody><tr><td>Increasing government effectiveness</td><td>--</td><td>Low</td><td>High</td><td>Medium</td></tr><tr><td>Increasing government efficiency</td><td>--</td><td>--</td><td>High</td><td>Medium</td></tr><tr><td>Increasing transparency and accountability</td><td>--</td><td>--</td><td>High</td><td>Medium</td></tr></tbody></table>

For example, in the UK a project to catalogue, standardise and make available data pertaining to local services for sufferers of loneliness was funded and delivered in 2021. The aim of the project is to connect citizens in need of specific services to the respective providers, and to better understand how to reach those in need.<fnref n="327" />

## Social impact

In Montenegro, Ukraine and the UK have public sector stakeholders active in the open data field performed activities to monitor the social impact of open data, either in the form of conducting research or by incorporating the social impact of open data into their data strategy document. The table below represents the components that influenced the level of social impact of open data in the EaP countries, Montenegro, and the UK.

<table><thead><tr><th colspan="5">Level of Social Impact</th></tr><tr><th></th><th>Georgia</th><th>Montenegro</th><th>Ukraine</th><th>The UK</th></tr></thead><tbody><tr><td>Inclusion of marginalised groups</td><td>--</td><td>--</td><td>High</td><td>Medium</td></tr><tr><td>Raising awareness concerning housing in the city</td><td>--</td><td>--</td><td>High</td><td>Medium</td></tr><tr><td>Raising awareness on health and well-being</td><td>--</td><td>Medium</td><td>High</td><td>High</td></tr></tbody></table>

Similar to other participating countries in the 2021 landscaping exercises do the EaP countries, Montenegro and the UK observe a high social impact of open data on raising awareness on health and

<footnote n="324">³²⁴ Ministry of digital Transformation: https://thedigital.gov.ua/</footnote>

<footnote n="325">³²⁵ Transparency and Accountability in Public Administration and Services (TAPAS): https://www.eurasia.org/Programs/ukraine_TAPAS</footnote>

<footnote n="326">³²⁶ https://tapas.org.ua/wp-content/uploads/2021/01/OD-Research-DABI_ed.pdf</footnote>

<footnote n="327">³²⁷ https://about.esd.org.uk/news/lga-place-based-directory-services-loneliness-pilots</footnote>
well-being. This is shown by, for example, the publication of COVID-19 data in Montenegro<fnref n="328" />, a vaccination map launched in Ukraine<fnref n="329" />, or the COVID-19 dashboard published in the UK<fnref n="330" />.

## Environmental impact

In Montenegro, Ukraine and the UK have public sector stakeholders active in the open data field performed activities to monitor the environmental impact of open data, for example, by conducting research or having their national environment agency publish and monitor the re-use of their data. The table below represents the components that influenced the level of environmental impact of open data in the EaP countries, Montenegro, and the UK.

<table><thead><tr><th colspan="5">Level of Environmental Impact</th></tr><tr><th></th><th>Georgia</th><th>Montenegro</th><th>Ukraine</th><th>The UK</th></tr></thead><tbody><tr><td>Raising awareness on water and/or air quality</td><td>--</td><td>Medium</td><td>High</td><td>High</td></tr><tr><td>Raising awareness on noise levels in cities</td><td>--</td><td>--</td><td>Low</td><td>--</td></tr><tr><td>Waste management</td><td>--</td><td>Medium</td><td>High</td><td>--</td></tr><tr><td>Environmental-friendly transport systems in cities</td><td>--</td><td>Medium</td><td>High</td><td>High</td></tr></tbody></table>

Ecoinfo is a Ukrainian initiative that offers an interactive map for citizens to avoid being outdoors during hazardous air pollution or to choose housing in an area with less polluted air.<fnref n="331" /> The map integrates open data of the Ministry of Environmental Protection and Natural Resources<fnref n="332" /> with data from public monitoring networks on air pollution.

## Economic impact

In Montenegro, Ukraine and the UK have public sector stakeholders active in the open data field performed activities to monitor the economic impact of open data, either in the form of conducting research or by incorporating the social impact of open data into their data strategy document. The table below represents the components that influenced the level of social impact of open data in the EaP countries, Montenegro, and the UK.

<table><thead><tr><th colspan="5">Level of Economic Impact</th></tr><tr><th></th><th>Georgia</th><th>Montenegro</th><th>Ukraine</th><th>The UK</th></tr></thead><tbody><tr><td>Macro-economic impact of open data</td><td>--</td><td>--</td><td>High</td><td>Medium</td></tr><tr><td>Micro-economic impact of open data</td><td>--</td><td>Low</td><td>High</td><td>Medium</td></tr><tr><td>Economic benefits for public administrations</td><td>--</td><td>--</td><td>High</td><td>Medium</td></tr></tbody></table>

In the UK, a positive micro-economic effect comes from the publication of open data on flooding. This data has helped to influence the decision-making of planners and builders when seeking plots for new housing, business, etc.<fnref n="333" />

<footnote n="328">³²⁸ https://www.ijzcg.me/me/covid19-kumulativne-stope-po-opstinama</footnote>

<footnote n="329">³²⁹ https://vac.shtab.net/</footnote>

<footnote n="330">³³⁰ https://coronavirus.data.gov.uk/</footnote>

<footnote n="331">³³¹ https://ecoinfo.pro/site/any_points</footnote>

<footnote n="332">³³² Ministry of Environmental Protection and Natural Resources: http://eng.menr.gov.ua/</footnote>

<footnote n="333">³³³ https://flood-warning-information.service.gov.uk/long-term-flood-risk</footnote>
## 5.3 Open data portal

### 5.3.1 EFTA countries

All participating EFTA countries, Iceland, Norway and Switzerland have a national open data portal in place. Iceland launched a new open data portal in April 2021, for which they are in the process of merging the old data portal and a portal for geographical information into one.

#### Portal features

In 2021, all participating EFTA countries offer on their national data portal an advanced data search function, the possibility to download datasets, and the possibility to search by file format or data domain. Additionally, all EFTA countries offer a way to programmatically query the metadata. Norway and Switzerland offer a preview function for geospatial data, and Switzerland also offers a preview function for tabular data.

Iceland and Norway offer both a general feedback mechanism as well as a feedback mechanism at dataset level. All EFTA countries offer the possibility for users to request datasets, but Norway is the only country that presents the requests in a transparent manner on the national portal. Norway recently launched a new website for the open data community to submit data requests and share feedback.334 This new website makes Norway the only EFTA country to include a discussion form for users.

Norway and Switzerland have a dedicated section on their portal to showcase use cases, but only the Swiss portal reference the dataset that the use case is based on. Both countries offer the possibility for users to submit their own use case.

#### Portal usage

All participating EFTA countries perform activities to gain insight into the national portal's usage, and Iceland and Norway use these insights to improve the portal. In Iceland and Norway Google Analytics are used and in Switzerland Matomo is used. The Icelandic national portal has, on average, 500 unique visitors per month, the Norwegian portal has more than 4000 unique visitors per month, and the Swiss portal hosts approximately 15 000 unique visitors per month.

The national portal teams of Norway and Switzerland monitor what keywords are used to search for data and content and what the most and least consulted pages are. The Icelandic national portal recently launched their open data portal; therefore, the monitoring mechanisms will provide more insights in next year's assessment.

On the open data portals of all EFTA countries, the metadata is available in clear plain language as well as to enable both humans and machines to read and understand it. Also, all countries run analytics on API usage if applicable. Of the Icelandic portal traffic, 100% is generated by API usage only. For the Swiss data portal, the traffic generated by API usage is less than 1%.

#### Data provision

In Norway and Switzerland, approximately half of the public sector data providers contribute to the national data portal, but they identify the data providers that are not yet publishing their data on the portal. In Iceland only a few public sector data providers contribute. The new Icelandic open data portal is only recently launched, so the number of publishing public sector data providers is expected to steadily increase over time. All EFTA countries assist data providers with their publication process.

<footnote n="334">334 http://datalandsbyen.norge.no/</footnote>
All EFTA countries' open data portals include datasets that are real-time or dynamic. In Iceland and Norway, more than 30% of the metadata links to such data. In Switzerland this number lies between 1%-10%.

### Portal sustainability

All participating EFTA countries have a strategy in place to ensure the national portals' sustainability. The Icelandic and Norwegian strategy documents include a description of the portals' target audience group and how to reach this audience. All EFTA countries take actions to promote the national data portals' activities and the available open data, for example, by being active on social media. All countries also made their portal's source code and relevant documentation available to the public.

All EFTA countries have a process in place to review and improve their national open data portals on a regular basis. In Norway, for example, a user satisfaction survey was conducted in the past year. In Norway and Switzerland, the review activities take place on a quarterly basis, in Iceland this is performed twice a year.

### 5.3.2 EaP countries, Montenegro and the United Kingdom

All countries discussed in this paragraph, Georgia, Montenegro, Ukraine and the UK, have a national open data portal in place.

### Portal features

All countries offer on their national data portal an advanced data search function, the possibility to download datasets, and the possibility to search by file format. Only Montenegro does not allow to search by data domain. Additionally, Montenegro, Ukraine and the UK offer a way to programmatically query the metadata, for example via an API or SPARQL access point.

All countries offer a feedback mechanism at the dataset level on their national open data portals. Georgia and Ukraine incorporated a mechanism on their national portals that allows user to rate datasets. Georgia, Ukraine, and the UK also offer a general feedback mechanism. In all countries it is possible to request a dataset, where only Ukraine presents the requests and its status in a transparent manner on the portal.335 Ukraine also allows users to see what data exists but cannot be made available as open data.

Montenegro and Ukraine have a designated area on their national portal to showcase use cases, also allowing users to submit their own use cases. Additionally, Ukraine offers a discussion forum where data providers and data re-users can interact with one another.336

### Portal usage

All countries perform activities to gain insight into the portal's usage in the form of web analytics. Georgia, Ukraine and the UK use these insights to improve their portal. The Montenegrin data portal have, on average 100 unique visitors per month, the Ukrainian portal has between 110 000 - 115 000 unique monthly visitors, and the UK approximately 350 000.

Montenegro, Ukraine and the UK monitor what keywords are used to search for data on the portal as well as the most and least consulted pages. In all countries is the metadata on the national portals available in plain language as well to enable both humans and machines to read and understand it.

<footnote n="335">335 https://diia.data.gov.ua/join/datasets</footnote>

<footnote n="336">336 https://forum.data.gov.ua</footnote>
Montenegro, Ukraine and the UK run analytics on API usage. Around 50% of the Montenegrin portal traffic is generated by API usage, and approximately 77% of the Ukrainian portal traffic.

### Data provision

In Montenegro and Ukraine do all public sector data providers contribute to the portal, in the UK the majority of public sector data providers contribute. In Georgia only a few public sector data provers contribute but they identified the parties that not yet contribute to the portal. All countries perform activities to support data providers with publication process. Only the Ukrainian data portal includes datasets that are real-time or dynamic, which concerns between 21-30% of the metadata on the portal.

### Portal sustainability

In Ukraine and the UK, a strategy is in place to ensure the open data portal's sustainability. Montenegro and Ukraine perform activities to promote the available data on their portal. Only the Ukrainian data portal is active on social media.

Only in Ukraine a user satisfaction survey has been conducted in the past year. Nevertheless, Montenegro, Ukraine, and the UK indicate to have a process in place in which the portal is reviewed regularly. For the UK, the revision of the portal happens quarterly, while for Montenegro and Ukraine this is annually.

## 5.4 Open data quality

### 5.4.1 EFTA countries

#### Currency and completeness

All participating EFTA countries indicate to have a pre-defined approach in place to ensure that the metadata is kept up to date. In Iceland and Norway 100% of the metadata is obtained from the source automatically, rather than edited manually. In Switzerland, this percentage falls between 90-99%, showing an improvement compared to last year for both Norway and Switzerland. In all countries is the metadata on the national portals updated within one day in case the metadata at the source changes. In Norway all metadata is automatically harvested at least daily. Most catalogues are harvested every 1-6 hours. Finally, in Iceland all datasets cover the full period from when it was first published until today, in Norway this concerns the majority of datasets, and in Switzerland this only holds for a few datasets.

#### Monitoring and measures

Where last year only Switzerland monitored the quality of the metadata on their portal, this year also Norway started to monitor the metadata quality. The Norwegian data portal team also publishes an assessment of the metadata on their portal.<fnref n="337" />

All EFTA countries have guidelines in place to assist publishers in choosing an appropriate license for their data. In Norway and Switzerland an own licence has been developed to foster the publication of open data. All countries' guidelines provide recommendation for the use of either Creative Commons (CC) licences or their own licence. In 2021, all EFTA countries experienced an increase in the share of datasets that is accompanied by licencing information compared to last year, with the current share being more than 90% of the datasets.

<footnote n="337">³³⁷ https://data.norge.no/guidance/metadata</footnote>
All EFTA countries conduct regular activities to incentivise or assist data providers in the publication of both machine-readable formats as well as high-quality metadata.

In Switzerland, a national programme to implement the "once only" principle has been launched.338
With the primary goal of enabling interoperability, the programme encourages and supports the
production of high-quality metadata of their data providers.

DCAT-AP compliance

Norway and Switzerland offer documentation on DCAT-AP to their data providers on their national portal. In Iceland, DCAT-AP compliance is not yet a priority, but they are considering it for the future.

In Norway, the guide for describing a dataset is published by the Norwegian Digitalisation Agency.339 Currently more than 90% of the metadata is DCAT-AP compliant, more than 90% of the metadata uses recommended classes, and between 31%-50% uses optional classes. The high level of DCAT-AP compliance is attributed to the fact that the Norwegian data portal does not allow registrations if mandatory classes are missing. For optional classes, metadata quality is measured, which is displayed for each individual dataset.

In Switzerland, all documentation related to DCAT-AP are summarised on a recently published dedicated page from the Swiss eGovernment initiative.340 In Switzerland, less than 10% of the portal's metadata is DCAT-AP compliant (contrary to the 71-90% of last year), more than 90% of the metadata uses recommended classes, and between 51%-70% uses optional classes. The lack of DCAT-AP compliance can be explained by the current version of DCAT-AP-CH, the swiss extension, which presents different incompatibilities to DCAT-AP. They are currently working on fixing this matter by updating the swiss specification.

Both countries developed a national extension of the DCAT-AP standard to better fit their national context. Norway extended the DCAT-AP standard to support the portal's scope that goes beyond open data. As mentioned, the Swiss DCAT-AP extension is currently being updated.

Deployment quality and linked data

In Norway and Switzerland, a model is implemented to assess the quality of deployment of data in their country, Norway uses the FAIR-principles<fnref n="341" />, and Switzerland uses the 5-star model. This is different from last year, when only Switzerland had such a model in place. Both countries conduct activities to promote and familiarise data providers with ways to ensure higher quality data.

In Iceland, more than 90% of datasets is made available under an open licence. Out of this group, more than 90% of datasets is available in a structured data format. Norway shows similar results to last year, between 71%-90% of their datasets is available under an open licence, including text documents, which is a decrease compared to last year. More than 90% of Norwegian open datasets are also made available in a structured format. In Switzerland, more than 90% of datasets is available under an open licence. Out of this group, more than 90% also made available in a structured format, which is an improvement compared to last year.

<footnote n="338">³³⁸ https://www.bfs.admin.ch/bfs/en/home/nadb/nadb.html</footnote>

<footnote n="339">³³⁹ https://data.norge.no/specification/dcat-ap-no/</footnote>

<footnote n="340">³⁴⁰ https://dcat-ap.ch/</footnote>

<footnote n="341">³⁴¹ For more information see: https://data.norge.no/guidance/metadata</footnote>
### 5.4.2 EaP countries, Montenegro and the United Kingdom

**Currency and completeness**

Georgia, Ukraine and the UK indicate to have a pre-defined approach in place to ensure the metadata on their national open data portal is being kept up to date. In Georgia and Montenegro less than 30% of the portal's metadata is obtained from the source automatically, in Ukraine this number is between 50%-69%, and in the UK between 30%-49%. In Ukraine, metadata on the portal is updated within a day in case the metadata at the source changes, in Montenegro within a week, and in Georgia and the UK this can either take longer than one month, or they do not know the exact time it takes to update the metadata.

Finally, in Ukraine all published datasets covers the full period from when it was first published until today, in Montenegro this holds for approximately half of the datasets, in the UK for a few datasets, and in Georgia for none of the portal's datasets.

**Monitoring and measures**

Ukraine and the UK monitor the quality of their portal's metadata and share this information with the public. In Ukraine a Business Intelligence (BI) tool is available to monitor metadata.<fnref n="342" /> The UK offers a broken links report to show its portal's quality.<fnref n="343" />

In Ukraine and the UK guidelines are offered to assist publishers in choosing an appropriate open data licence. Additionally, the UK developed their own licence to foster data publication.<fnref n="344" /> Both Ukraine and the UK included recommendations on which licences to use in the available guidelines. As a result, in both countries more than 90% of the open data on their national portal is accompanied by licensing information.

In Montenegro, Ukraine, and the UK regular activities are being conducted to incentivise data providers in the publication of data in machine-readable formats. Additionally, in Ukraine activities are conducted to support the publication of high-quality metadata.

**DCAT-AP compliance**

In Georgia, Montenegro, and the UK, DCAT-AP compliancy is not a priority at the moment. Ukraine is the only country where data providers are supplied with documentation on DCAT-AP. As a result, more than 90% of the metadata on the Ukrainian data portal is DCAT-AP compliant. More than 90% of its metadata uses DCAT-AP recommended classes, and between 71%-90% uses DCAT-AP optional classes. In case metadata lacks DCAT-AP compliancy this is often caused by the absence of support of DCAT in the software used by the open data providers. Additionally, more than 90% of the Ukrainian datasets provides a reference to where the data can be downloaded and a webpage from where it can be accessed.

**Deployment quality and linked data**

Montenegro and Ukraine use a 5-star model to assess the quality of deployment of data in their country. They both conduct activities to familiarise data providers with ways to ensure higher quality data. In Montenegro and Ukraine, more than 90% of the datasets is available under an open licence, including text documents. Out of this group, between 31%-50% of the Montenegrin open datasets and 51%-70% of the Ukrainian open datasets is also made available in a structured format. Finally, in

<footnote n="342">³⁴² https://data.gov.ua/pages/analityka</footnote>

<footnote n="343">³⁴³ https://data.gov.uk/data/report/broken-links</footnote>

<footnote n="344">³⁴⁴ http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/</footnote>
the UK, between 71%-90% of the datasets is available under an open licence, including text documents, of which between 51%-70% also in a structured format.

## 5.5 Overall performance

### 5.5.1 EFTA countries

In figure 40 the scores of the EFTA countries are shown per dimension. Norway shows a major improvement in score in 2021, outperforming the other EFTA countries on all dimensions. Similar to last year, the most mature dimension of Switzerland is quality, while within impact they are falling behind compared to the others. Iceland did not participate in last year's assessment, but comparing their score to 2019, a massive step forward can be observed on all four dimensions.

<figure><img src="image_44.png" /><figcaption>Figure 40: The EFTA countries' scores on the four open data maturity dimensions</figcaption></figure>

To understand the remarkable improvements by the EFTA countries, the overall maturity scores of the last three years are shown in figure 41. Compared to 2019, Iceland's score increased from 8% to 61%. Iceland introduced new policy and strategy documentation over the last two years, structuring their open data practices and defining a path for the upcoming years. Also, recently new open data portal was launched improving Iceland's score on both portal and quality, therefore directly affecting the impact that is being created. Norway also shows major improvements in their open data maturity, with jumping from 51% in 2020 to 91% in 2021, they show the highest increase in score of this year's assessment. Finally, Switzerland's score steadily increases over the years, illustrating their continuous effort to improve.
<figure><img src="image_45.png" /><figcaption>Figure 41: Open data maturity score of the EFTA countries between 2019-2021</figcaption></figure>

### 5.5.2 EaP countries, Montenegro and the United Kingdom

Last year was the first year the Eastern Partnership countries participated in the landscaping exercise. Montenegro joined for the first time this year. The UK has been participating since the first edition but left the EU by 2020. In figure 42 the scores of the EaP countries, Montenegro, and the UK are shown per dimension. Ukraine, as being one of the top performing countries of the assessment outperforms the other countries on all dimensions. For all countries holds that, similar to last year, the policy dimension is the most mature dimension. The UK shows great improvement within the impact dimension, jumping from 48% in 2020 to 69% in 2021.

<figure><img src="image_46.png" /><figcaption>Figure 42: The EaP countries, Montenegro, and the UK's scores on the four open data maturity dimensions</figcaption></figure>

Comparing this year's overall open data maturity score to last year (see figure 43), most countries increased in score and Georgia's score remained unchanged. Especially Ukraine shows great improvement in score, promoting to the trend-setter cluster as explained in the next chapter. As this
is only the first year that Montenegro participates in the assessment, it is difficult to provide a
perspective on their results. Nevertheless, 53% is a promising score for Montenegro to enter the
assessment with.

<figure><img src="image_47.png" /><figcaption>Figure 43: Open data maturity score of the EaP countries, Montenegro, and the UK between 2020-2021</figcaption></figure>
# Chapter 6: Clustering the Countries

As part of the landscaping exercise all participating countries are grouped into four clusters based on the 2021 open data maturity assessment. Clustering the countries based on their level of maturity helps to identify affinities between their progress and challenges. Countries in the same cluster can share and discuss strategies on how to overcome challenges they are facing and learn from the countries in more mature clusters. Clustering also enables us to provide more focused advice for each of the clusters.

From the lowest to the highest performing, these clusters are named: beginners, followers, fast-trackers, and trend-setters. Similar to last year, the country scores are concentrated around the highest performing clusters.

## 6.1 Clustering profiles

The indicative profiles that exemplify the level of maturity one may expect from the countries according to the cluster they belong to are specified below. The clustering profiles have not changed in recent years.

Note that the names of the clusters are an exemplification and do not intend to generalise nor to represent literally the achievements and history of open data developments in the respective countries, for example, you may find countries in the beginners cluster that have been investing in open data for years, though with less significant results emerging from the survey than others.

<table><thead><tr><th></th><th></th></tr></thead><tbody><tr><td>Trend-setter</td><td>The country has an advanced open data policy in place with a strong coordination of open data activities throughout at all levels of government. The national portal provides a wide range of features and caters for the needs of advanced users and publishers. The level of quality of open data in the country is very good, with various initiatives in place to ensure the publication of high-quality data and compliance with DCAT-AP. There are different open data ecosystems developed around data domains, with a high level of interaction and reuse within these domains. Activities to measure re-use are conducted, with methodologies in place to assess the impact in different domains. Little to no limitations to publication or re-use are observable.</td></tr><tr><td>Fast-tracker</td><td>The country shows a good level of maturity against all dimensions. Overall, the country showcases activities to boost data publication, with a strategic approach to increase the quality of published data and a high level of compliance with standards is achieved. The national portal provides a good level of functionalities to cover the needs of advanced and basic users. Limited efforts are made to monitor the impact of open data. However, a stronger focus is given to tracking and boosting re-use. Some issues can still be observed, but measures are in place to tackle them.</td></tr><tr><td>Follower</td><td>The country already has an open data policy in place and is conducting activities to ensure a fair level of coordination of open data activities. The portal showcases standard features, but also a limited number of features that cater for the needs of more advanced users. There are a few activities conducted to boost the publication of high-quality data from different providers, however, there is no systematic</td></tr></tbody></table>
<table><tr><td></td><td>approach to ensure a higher quality of publication across the board. Only very limited activities to monitor re-use and measure the impact of open data are performed. A fair number of limitations in terms of data publication and re-use still exist.</td></tr><tr><td>Beginner</td><td>The country shows an early stage of maturity on the four dimensions or – alternatively – was not able to develop at the same pace as the counties in other, better performing clusters. Progress is more prominent in the open data policy dimension. There is no open data portal or, if existent, the portal showcases limited features or a limited number of datasets, compared to the country's potential. None or very limited activities are performed to monitor the reuse of open data in the country and no monitoring is done to assess impact. In terms of data quality, the country is taking little action to enable the publication of data in higher quality, and little effort is spent to ensure the adoption of DCAT-AP. Visible limitations in terms of open data publication exist, with limited reuse examples.</td></tr></table>

## 6.2 The 2021 clustering

In order to cluster the countries, the scores are plotted on from low to high and groups are defined where a significant gap in the overall scores is found. Interestingly, all cluster intervals shifted upwards on the scale, meaning that a higher score is needed to belong to certain cluster. The intervals of the fast-trackers and followers clusters outperformed last year's intervals as they do not overlap, showing the significant improvements made by the concerned countries. The results of the clustering can be found in figure 44.

<figure><img src="image_48.png" /><figcaption>Figure 44: Clustering of the 2021 maturity score of the participating European countries</figcaption></figure>

The results, including the cut-off points of the clusters, are listed below. Countries marked with an asterisk (*) are not part of the EU27.

* **Trend-setters (94%-98%):** France, Ireland, Spain, Poland, Estonia, and Ukraine*

* **Fast-trackers (89%-92%):** Austria, Italy, Slovenia, Netherlands, Cyprus, Denmark, Norway*, Lithuania, and Germany

* **Followers (74%-86%):** Finland, Sweden, Croatia, Greece, Bulgaria, Latvia, Romania, Czech Republic

* **Beginners (17%-66%):** Luxembourg, Portugal, Switzerland*, the UK*, Iceland*, Hungary, Belgium, Montenegro*, Malta, Slovakia, and Georgia*
## Open Data Trend-setters

The trend-setters cluster consists of 6 countries who have an overall maturity score of 94% or higher. The interval of the trend-setter cluster shifted 4 percentage points upwards in 2021, as the scores range between 94%-98%, while in 2020 the scores ranged between 90%-96%.

In 2021, France recorded the highest score of 98% and took the lead in the assessment for the first time, with a relatively large gap towards the other trend-setters. The remaining 5 trend-setters' scores are extremely close and fall within a range of 1%. Ireland, Spain, Poland, all with a score of 95%, and Estonia with a score of 94% retained their trend-setter position. Finally, Ukraine entered the trend-setter cluster for the first time with a score of 94%. Each of these countries improved their score from last year. Ukraine showed the most significant improvement with an increase in score of 10 percentage points, jumping from fast-tracker to trend-setter.

## Open Data Fast-trackers

In 2021, the fast-trackers cluster consists of 9 countries who have an overall maturity score between 89%-92%. The countries in the fast-tracker cluster showed remarkable improvements in this year's assessment, as the lower limit of the interval increased by 11 percentage points. Also, the scores as of the fast-trackers are much more concentrated on a smaller range compared to last year. The scores of the fast-trackers ranged between 78%-88% in 2020. This trend is also represented by the decline in countries included in the fast-tracker cluster from 13 countries in 2020 to 9 countries in 2021.

The fast-tracker countries' maturity scores are extremely close to each other. In 2021, 7 out of the 9 fast-trackers' scores fall within a range of 1,2%. The fast-trackers cluster consists of Austria, Italy, Slovenia, and the Netherlands with a score of 92%, Cyprus, Denmark, and Norway, with a score of 91%, and Lithuania and Germany with an identical score of 89%. Austria and Denmark moved from trend-setter to fast-tracker, as their score did not improve enough to match the higher trend-setters' maturity scores. Norway showed the highest improvement in score of the 2021 assessment, with an increase of 40 percentage points compared to last year, jumping from beginner to fast-tracker.

## Open Data Followers

The followers cluster consists of 8 countries, with overall maturity scores ranging between 74%-86%. Similar to the fast-trackers, show countries included in this cluster significant improvements compared to last year. The lower limit of the interval increased by 17 percentage points, not even overlapping last year's interval of 57%-72%.

Most countries within this cluster, 5 out of 7, moved down from the fast-trackers cluster as their improvements did not follow the high growth rate of this cluster. Finland (86%), Sweden (84%), Croatia (84%), Greece (82%), Bulgaria (78%), and Latvia (77%) moved from the fast-tracker to the followers cluster. Romania (76%) and Czech Republic (74%) retained their position in this cluster by showing an increase in score of 7% and 2% respectively.

## Open Data Beginners

The beginners cluster is the most numerous cluster of the 2021 assessment, consisting of 11 countries with an overall maturity score below 66%. This threshold is 13% higher than for last year's beginner's cluster.

Ranked from the highest to lowest scores, the beginners are: Luxembourg (66%), Portugal (66%), Switzerland (65%), the UK (60%), Iceland (61%), Hungary (58%), Belgium (55%), Montenegro (54%), Malta (51%), Slovakia (50%), and Georgia (17%). Luxembourg, Switzerland, the UK, and Belgium moved from the followers to the beginners cluster. Due to the speed of open data transformation in other countries and the corresponding increases in the overall open data maturity scores, most countries
remain in the beginners cluster even when they have showed improvement, because they are not progressing as fast as others. For example, Hungary improved from 34% to 58% and Portugal improved from 48% to 66%. Montenegro and Iceland did not participate in last year's assessment and entered this year in the beginners cluster.

## 6.3 Development of the clusters 2015-2021

The development of the share of countries included per clusters can be seen in figure 45. The figure shows that the trend-setter cluster did not change significantly in growth. The fast-tracker cluster is the most volatile cluster in terms of group size. Where last year the group increase drastically, this year a decline is visible. The opposite trend holds for the followers cluster, where last year a steep decline was observed and this year a slight increase. Finally, the beginners cluster shows and increasing trend since 2018. Mainly due to the inclusion of countries outside the EU27 and the peak performances in maturity scores of recent years.

<figure><img src="image_49.png" /><figcaption>Figure 45: EU27 average open data maturity per dimension for the period 2015-2021</figcaption></figure>

The significant progress from 2019 onwards, also suggests the need for a re-calibration of the methodology. That would incentivise the countries to perform even better, highlight and reward appropriately their achievements, and enable better observing and learning from the choices that make them different.
# Chapter 7: Recommendations for the Countries

The researchers' recommendations for the countries, by cluster, are collected in this section. These have not changed substantially from the previous year, as the clusters' profile have not changed, and the trends observed last year were confirmed.

## 7.1 Trend-setters

*Maintain the ecosystem, experiment, and share the knowledge*

1. Enhance and consolidate the open data ecosystems you support by developing thematic communities of providers and re-users. Continue to prioritise the categories specified for the high-value datasets in the Open Data Directive. Particularly in this time of pandemic, invest into online channels and tools that enable continuing the exchange of knowledge and experience, such as periodic videoconference meetings, wikis on topics of interest etc.

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 the agencies and local authorities, that will gain prominence over time.

3. Define and/or develop a strategy to ensure the sustainability of the national and local open data portal infrastructure. Experiment with alternative funding models beyond state funding, e.g. pay for value-added services on the portal. Share the outcome of your experimentation with the other countries.

4. Collaborate with other national open data teams, universities, and research institutions, and data.europa.eu to develop an experimental impact assessment framework. Also, start developing country-specific metrics to measure impact. Operationalise monitoring the metrics and assessing 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, etc.) to ensure a variety of insights. Improve the method iteratively over time.

5. Continue to conduct research to assess the economic impact of open data, at both micro and macro levels.<fnref n="345" /> Iterate annually or biannually to observe change and refine activities and goals. Leverage the momentum created by showcasing the results and rally stronger political support.

6. Harness the wisdom of the crowd by enabling the broader open data community to contribute more to the national open data programmes. Enable re-users to upload their own data and showcase their ideas and creations on the national portal. Enable users to comment on and rate datasets and embed their feedback and ratings in the search algorithms. Enable publishers to improve their data publication, based on re-users' feedback and ratings.

7. Continue the work on improving the quality of both metadata and data by boosting the use of tools on your portal (e.g. for the validation of metadata). Enable automated notifications to

<footnote n="345">³⁴⁵ For example, by following the methodology of data.europa.eu's report "Economic Impact of Open Data: Opportunities for value creation in Europe" (2020). Available at https://data.europa.eu/sites/default/files/the-economic-impact-of-open-data.pdf</footnote>
publishers to notify them of issues. Provide tools to enable data conversion into alternative formats, possibly replacing non-machine-readable, proprietary formats. Invest into the portal to use new workflows and tools that enable the best understanding of your re-users' profiles and needs, while preserving their privacy.

8. As the Open Data Directive is implemented in your country, adapt the national portal to give clear visibility of the datasets. Particularly with regards to real-time data, link to a variety of sources and evaluate means of incentivising custodians of real-time data to publish beyond the minimum legislative requirements.

9. Work with training institutions on providing advanced open data courses and training and tailor training curriculum to involve more advanced topics. Make such courses formally recognised and provide certification upon successful completion.

10. Share your knowledge and results of your experimentation with other countries and enable them to learn from your best practices and contribute to your research, e.g. in areas of focus you share, or where you experience similar barriers. Reach out and cooperate with other countries on developing solutions to common challenges, including basic, re-usable elements such as open source software that your platforms share (e.g. portal extensions).

## 7.2 Fast-trackers

*Graduate from traction to impact*

1. Assist the development of open data initiatives at local and regional level and coordinate more with the local and regional open data teams.

2. Activate the network of open data officers and enable them to set up monitoring activities within their organisation (e.g., develop plans for data publication and monitor charging practice). Track progress against these plans and assist open data officers to alleviate 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 financial resources to be 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 formats (e.g. hackathons) to formats that privilege enabling business opportunities for medium- to long-term engagement (e.g. data challenges). Ensure funding and political sponsorship (e.g. an organisation as 'patron') for winning ideas.

5. Promote and follow-up on the performance of products and services built on open data. Develop strategic awareness of re-use and impact. Focus resources on a relevant field or sector, to start demonstrating impact, and use the high-value datasets 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 between providers and re-users. Increase your knowledge on the publication and re-use of data in that domain and start thinking of a definition of impact in that field that can be operationalised into metrics.
6. As the Open Data Directive is implemented in your country, adapt the national portal to give clear visibility of the datasets. Update the portal to better engage your audience. Include features that enable online interaction between data publishers and re-users. Showcase re-use examples prominently on the national portal and promote the datasets used to develop those use cases. Consider the opportunity to promote the developers as well.

7. Monitor access and usage of the portal and enhance knowledge in your team around the profiles of your portal's typical users. Ensure the re-users' privacy in doing web analytics and be explicit with them about how that insight will be used. Enable such insights to flow into improving the portals features, the access to data and improve the variety of data published in your country.

8. Address the requirements of the implementation of the Open Data Directive in your country by revising and enhancing the portal's support for real-time data sources. Identify the main real-time data holders and promote the publication of their data beyond the minimum requirements specified by law. Understand the concerns and costs of publication and work together with publishers to enable the data publication process.

9. Think of ways to ensure the portal's sustainability by enabling more contributions from the open data community (e.g. submitted datasets, developed use cases, news and blog items written by the community), by providing value-added features, and by exploring additional funding options.

10. Enforce minimum standards to the quality of metadata and data by using analytics tools to monitor data publication – at both metadata (compliance with the DCAT-AP schema) and data (formats of publication) level. Develop validation schemas 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, both in terms of metadata and data.

## 7.3 Followers

*Strengthen governance, boost engagement*

1. Update the national strategy for open data to reflect technical and policy developments at EU level. In particular, address the requirements of the latest Open Data Directive by identifying high-priority domains and high-value datasets for publication, through APIs and free whenever possible. Support publication through legislation where suitable.

2. Set up a governance structure that accounts for the characteristics of your country. Engage potential re-use groups (e.g. data companies, research institutions, NGO's) into the open data governance in your country. This will enable a co-ownership around a common vision and buy-in on the actions for each sector.

3. Develop a yearly plan for online activities (e.g. events, conferences...) to promote open data. Focus on formats that promote publication as well as re-use by both public and private sector. Experiment with formats that both leverage creativity (e.g. hackathons) and enable the development of business opportunities on medium- to long-term engagements (e.g. data challenges). Ensure funding and political sponsorship for the winning ideas. Promote and follow up on the performance of developed products and/or services.

4. Analyse user behaviour on the data portals responsibly, ensuring their privacy and being explicit about how that insight will be used. Identify communities of re-users and conduct awareness-
raising activities around open data within these groups (e.g. universities, data start-ups and data companies, research institutes, NGOs, 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 monitor charging practices within their organisation and exchange within the network on practices to alleviate such barriers. Deepen the understanding within the network of open data officers of the benefits of open data re-use by the public sector.

6. Ensure that pre-existing open data courses and training materials are used and cooperate with public administrations and training organisations to develop open data training curricula for national, regional and local administrations. Enable such courses to be formally recognised and provide certification upon completion. Ensure financial resources are allocated at all administrative levels to training activities for civil servants working with data.

7. Enable meet-ups and engagement between re-users and publishers. Develop a deeper understanding of open data demand side and work together with data publishers to prioritise data publication in line with this demand. Focus on fostering open data reuse by both public and private sector and encourage the 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 homepage.

8. As the Open Data Directive is implemented in your country, adapt the national portal to give clear visibility of the datasets. Conduct regular updates to the portal to reflect the users' needs. Include features such as feedback and interaction mechanisms at dataset level, designated login areas for users, access via SPARQL query or/and API in general. Consider integrating data visualisation and analytics tools to allow portal visitors to gain insights from data via interactive charts and other visualisation tools. Monitor access and usage of the portal. Draw insights from this data and enhance awareness around it within your team.

9. Increase understanding of the variety of data that your portal features (historical vs. current data) and work towards improving it. Identify data holders that do not publish their data or do not reach to their full potential, understand what friction they are experiencing and plan to address it. Think of the future and on enabling publication of real-time data in your country.

10. Provide trainings and online materials that focus on metadata and data quality. Promote the DCAT-AP standard and existing guidelines to foster compliance. Create understanding around the importance of publishing data in machine-readable, non-proprietary formats as well as regarding the licensing of data. Develop knowledge around existing open source tools to clean up data and validators for metadata compliance.

## 7.4 Beginners

Think big, act small

1. Develop a national strategy for open data and align it with broader strategies at national level (e.g. digital strategies, strategies for the modernisation of public sector etc.)
2. Rally support to the open data programme and political leadership from top level of government. Showcase international research around the value of open data, to emphasise economic benefits of data exploitation.<fnref n="346" />

3. Set up a team at national level in charge of open data to ensure coordination of activities within the country and set up 'road-shows' to promote the team's scope and activities with the main public administrations. Include all levels of government in this process.

4. Organise a series of open data events at national level and focus on engaging both data publishers and re-users in your country. Prioritise the promotion of data publication best practices and re-use cases during such events.

5. Set up relevant communication channels and contact persons for data publication within public administrations (e.g. open data liaison officers). Maintain an active dialogue with the officers and enable regular exchange of knowledge amongst them, focusing on efficient online channels, in this time of pandemic (meetings, online forums etc.).

6. Identify the main data holders in the country and understand the main concerns and barriers to data publication. Take the first steps to overrun these barriers and unlock the publication of data.

7. Organise workshops and awareness-raising sessions with the main data holders. Use materials already developed in other countries and at European level for content and as source of inspiration.

8. Develop guidelines to enable publication of data, of its metadata and the take-up of suitable licensing conditions. If standard licences are not suitable, as a last resort evaluate developing a custom national licence. Learn from European best practices and reach out to colleagues in other countries when setting out to develop such guidelines. Raise awareness amongst main data publishers around the importance of metadata and promote the DCAT-AP standard, specifications, and existing guidelines developed at European level.

9. Make sure you run and maintain a modern portal that enables publication and discoverability of open data. Scout for European best practices and compare solutions to choose the most adequate to support your scope and mission. Set up dedicated news and blog sections to promote relevant developments and to showcase re-use. Ensure feedback channels are seamlessly integrated into the national portal. Be aware of users' rights and privacy as you perform web analytics, and choose your technology carefully, particularly following the invalidation of the EU-U.S. Privacy Shield.

10. Ensure that the national open data strategy guarantees scoping, management, and funding of the portal. Use action plans with actions and responsible entities or persons to ensure the strategy to be carried out. Ensure that sufficient resources are allocated to open data awareness-raising activities with both publishers and potential re-users.

<footnote n="346">³⁴⁶ For example, by following the methodology of data.europa.eu's report "Economic Impact of Open Data: Opportunities for value creation in Europe" (2020). Available at https://data.europa.eu/sites/default/files/the-economic-impact-of-open-data.pdf</footnote>
Conclusions

This report offered an extensive view into the 2021 edition of data.europa.eu's (formerly conducted by the European Data Portal) annual open data maturity benchmarking exercise. It provides insight into the developments in the open data field in European countries, including the 27 EU Member States, participating EFTA countries Iceland, Norway, and Switzerland, participating Eastern Partnership countries Georgia and Ukraine, as well as Montenegro and the United Kingdom.

The assessment measured open data maturity against four dimensions: policy, impact, portal, and quality. Maturity was scored against these dimensions, forming an overall open data maturity score for each country. The countries were clustered into four groups, from the most mature to the least: trend-setters, fast-trackers, followers, and beginners. For each, recommendations tailored to the level of maturity and characteristics of the clusters have been provided. By doing so, the report provides policymakers and national open data teams with actionable guidance to continue their development in the field of open data, in turn, enabling the creation of meaningful and sustainable benefits for the citizens of their countries.

The Member States are in the process of transposing the Open Data Directive into their open data policies, which aims, among other things, to reap the full potential of open data re-use. The Open Data Directive requires the adoption by the European Commission, via a future implementing regulation, of a list of high-value datasets. Although the adoption is still ongoing, this landscaping exercise got a first glimpse of the approach Member States will use to implement the upcoming regulation.

The open data impact dimension experienced the largest increase compared to the other dimensions underlining the increased importance of understanding, monitoring, and measuring open data value creation and impact. This is in line with one of the objectives of the Open Data Directive to reap the full potential of open data re-use. In recent years, impact was often measured by monitoring user analytics of national open data portals or by keeping a list of use cases. This year a clear trend has shown towards conducting in-depth research, such as desk research or surveys. This will, in the long-term, result in a structured approach on measuring open data impact and more accurate estimations of the impact on the society and economy as a whole.

Finally, the COVID-19 pandemic continues to strengthen the value and high social impact of open data in 2021. Last year's assessment showed the emphasis on the importance of systematically collecting and making data available to the public as a response to the pandemic. This year, the initiatives and dashboards are in most cases complemented with recent statistics about national vaccination rates, vaccination productions capacities, protective equipment availabilities, intensive care capacities, etc., showing the continuation of the value creation.

Looking ahead, the scores of the countries are consistently high and are gradually approaching the 100%. This proves the value of a revision of the methodology which is scheduled for 2022. The new methodology will aim to stimulate the Member States to continue to improve and grow beyond the current assessment, while ensuring consistency and comparability of the results.

This report and the numerous best practices from the countries aims to inspire the national open data teams but, also, anybody fostering open data availability and re-use. Cross-border collaboration will be stimulated ever further throughout 2022, enabling the open data community to learn from each other, and to spark new initiatives. This is of pivotal importance to reach the full potential of open data in Europe.