COMMISSION STAFF WORKING DOCUMENT IMPACT ASSESSMENT REPORT Accompanying the document Proposal for a REGULATION OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL on European data governance (Data Governance Act)
Date: 2020-11-25
Institutions: Directorate-General for Communications Networks, Content and Technology, European Commission
Subjects: access to information, administrative cooperation, data protection, data transmission, exchange of information, information storage and retrieval, personal data, public sector, right to reuse information, single market

EN 

  EN 

   EUROPEAN COMMISSION  Brussels, 25.11.2020  SWD(2020) 295 final  COMMISSION STAFF WORKING DOCUMENT  IMPACT ASSESSMENT REPORT  Accompanying the document Proposal for a REGULATION OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL on European data governance     (Data Governance Act) {COM(2020) 767 final} - {SEC(2020) 405 final} - {SWD(2020) 296 final}  
 
 
Table of contents 

1. 

2. 

INTRODUCTION: POLITICAL AND LEGAL CONTEXT ................................................................1 

PROBLEM DEFINITION .....................................................................................................................8 

2.1.  What is the problem? .........................................................................................8 
2.2.  What are the problem drivers? .........................................................................11 
2.3.  How will the problem evolve? .........................................................................16 

3.  WHY SHOULD THE EU ACT? ......................................................................................................... 17 

3.1.  Legal basis .......................................................................................................17 
3.2.  Subsidiarity: Necessity of EU action ...............................................................18 
3.3.  Subsidiarity: Added value of EU action ..........................................................18 

4.  OBJECTIVES: WHAT IS TO BE ACHIEVED? ................................................................................ 19 

4.1.  General objective .............................................................................................19 
4.2.  Specific objectives ...........................................................................................20 

5.  WHAT ARE THE AVAILABLE POLICY OPTIONS? ..................................................................... 21 

5.1.  What is the baseline from which options are assessed? ...................................22 
5.2.  Description of the policy options .....................................................................22 
5.3.  Options discarded at an early stage ..................................................................31 

6.  WHAT ARE THE IMPACTS OF THE POLICY OPTIONS? ............................................................ 31 

6.1.  Economic impact .............................................................................................31 
6.2.  Social and environmental impact .....................................................................43 
6.3. 
Impact on SMEs ...............................................................................................45 
6.4.  Member States’ and stakeholders’ views .........................................................46 

7.  HOW DO THE OPTIONS COMPARE? ............................................................................................. 48 

8. 

PREFERRED OPTION ....................................................................................................................... 51 

9.  HOW WILL ACTUAL IMPACTS BE MONITORED AND EVALUATED? .................................. 54 

9.1.  Monitoring of the specific objectives ..............................................................55 
9.2.  Monitoring of the preferred option ..................................................................55 

ANNEX 1: PROCEDURAL INFORMATION ............................................................................................. 58 

1. 

LEAD DG, DECIDE PLANNING/CWP REFERENCES ................................................................... 58 

2.  ORGANISATION AND TIMING ...................................................................................................... 58 

3. 

4. 

CONSULTATION OF THE RSB ....................................................................................................... 58 

EVIDENCE, SOURCES AND QUALITY ......................................................................................... 64 

ANNEX 2: STAKEHOLDER CONSULTATION ....................................................................................... 66 

ANNEX 3: WHO IS AFFECTED AND HOW? ........................................................................................... 74 

1. 

2. 

PRACTICAL IMPLICATIONS OF THE INITIATIVE ..................................................................... 74 

SUMMARY OF COSTS AND BENEFITS ........................................................................................ 77 

 
 
 
ANNEX 4: ANALYTICAL METHODS ...................................................................................................... 81 

ANNEX 5: SUBSIDIARITY GRID .............................................................................................................. 87 

ANNEX 6: GOVERNANCE FRAMEWORK IN THIRD COUNTRIES .................................................... 98 

 
 
1. 

INTRODUCTION: POLITICAL AND LEGAL CONTEXT     

This Impact Assessment accompanies the proposal for a Regulation of the European Parliament 
and of the Council1 on data governance. It is the first of a set of measures announced in the 2020 
European Strategy for Data2. The instrument aims to stimulate the availability of data for use and 
to strengthen data governance mechanisms in the EU. It would facilitate the following situations: 

 

the sharing of data among businesses, against remuneration or because of other benefits 
they derive from sharing; 

  making public sector data available for reuse, in situations where such data is subject to 

the rights of others3; 

  allowing the reuse of personal data with the help of a ‘personal data space’, designed to 
help  individuals  exercise  their  rights  under  the  General  Data  Protection  Regulation 
(GDPR); 

  making data reusable for altruistic purposes. 

1.1 Technological, economic and societal context 

An evolving technological landscape 

In  our  increasingly  connected  world,  more  and  more  data  is  being  generated,  originating  in 
factories or on farms, in cars or household appliances. The availability of such data is a critical 
enabler for data-driven innovation, including the development of more personalised and cheaper 
products, not least using artificial intelligence (AI) and related technologies.  

Europe  has  missed  the  first  wave  of  innovation  based  on  data,  mainly  data  collected  from 
individuals  over  the  Web  2.0.  But  a  second  wave  of  innovation  is  emerging  from  objects 
connected  to  the  Internet-of-Things  (IoT).  It  is  expected  that  the  volume  of  data  produced 
annually in the world will grow from the 33 zettabytes in 2018 to 175 zettabytes by 20254. The 
European  Strategy  for  Data  indicates  that  opportunities  arise  both  from  the  increasing  data 
volumes that are generated in fields in which the EU has a strong basis (such as manufacturing) 
and  the  changing  technological  landscape  for  data  use  will  offer  opportunities  for  European 
companies in the data economy.  

The importance of data for the economy 

In her 2020 State of the Union address, President von der Leyen stated that ‘A real data economy 
[…]  would  be  a  powerful  engine  for  innovation  and  new  jobs.’  According  to  a  study  by  the 
International  Data  Corporation  (IDC)  for  the  European  Commission,  the  data  economy  was 

1 The final form of the legal act will be determined by the content of the instrument. 
2 COM/2020/66 final. 
3 “Data the use of which is dependent on the rights of others” or “data subject to the rights of others” covers data that 
might be subject to data protection legislation, intellectual property, or contain trade secrets or other commercially 
sensitive information. 
4 Reinsel D., Gantz J., and Rydning J., (2018). The Digitization of the World. From Edge to Core, International Data 
Corporation White Paper No. US44413318. 

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estimated  to  be  worth  over  EUR  324.86  billion  at  the  end  of  20195,  representing  2.6%  of  the 
Gross  Domestic  Product  (GDP)  of  the  EU-27.  The  slow-down  caused  by  the  COVID  crisis  in 
2020 is expected to be followed by a rebound. 

Data is the basis for new digital products and services. It is essential for training AI systems. An 
example is the self-driving car: in addition to the data generated by the car itself, additional third-
party  data  are  required  for  this  type  of  system to  operate  securely,  irrespective  of  weather 
conditions, visibility or road-surface quality6. Moreover, the use of data drives productivity and 
resource  efficiency  gains  across  all  sectors  of  the  economy.  Research  by  the  Organization  for 
Economic  Cooperation  and  Development  (OECD)  suggests  that  companies  that  invest  in  data-
driven innovation and data analytics exhibit faster productivity growth than those that do not by 
approximately 5% to 10%7.  

Data is a critical resource for startups and SMEs, in particular as a business can be set up with 
very  low  initial  capital.  Over  99%  of  data  supplier  companies  and  over  98.8%  of  data  user 
companies in the EU are SMEs8. Some 85% of new jobs created in the data economy over the 
last years have been created by SMEs9. 

Some  93%  of  the  EU  executives  surveyed  in  a  recent  study  by  McKinsey  believe  that  better 
access to data would be important to their organisation (with approximately 40% designating this 
as very important). More than 50% would be willing to  share their data  if they either  received 
access  to  similar data from  competitors in  return or were paid  for the data10.  It  is  important  to 
note that the term ‘data sharing’ does not imply that all data will be available for free for all, but 
may include situations of data exchanged against reward. 

Societal impact of data 

A  better  use  of  data  can  lead  to  improvements  in  health  and  well-being,  a  better  environment, 
strengthened climate action, more efficient public services and safer societies. As demonstrated 
during  the  COVID-19  crisis,  data  is  an  essential  asset  for  tackling  emergencies  such  as 
pandemics.  More  generally,  in  the  health  sector,  data  can  help  develop  better  and  more 
personalised  treatments.  McKinsey  estimates  that  data  and  digital  technologies  could  lead  to 
savings of approximately EUR 12011 billion a year in the EU health sector. 

In  the  mobility  sector,  as  well  as  saving  more  than  27  million  hours  of  public  transport  users’ 
time12, up to EUR 20 billion a year could be saved in labour costs of car drivers thanks, amongst 

5  European  Commission  (2020a).  Final  Study  Report  of  the  Updated  European  Data  Market  Study,  SMART 
2016/0063. 
6 OECD (2019). Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across 
Societies, OECD Publishing, Paris. 
7 OECD (2015). Data-driven innovation: big data for growth and well-being, OECD Publishing, Paris.   
8  European  Commission  (2020a).  Final  Study  Report  of  the  Updated  European  Data  Market  Study,  SMART 
2016/0063. 
9 European Commission, Entrepreneurship and Small and medium-sized enterprises (SMEs). 
10 European Commission (2020). Shaping the digital transformation in Europe, study prepared by McKinsey. 
11 McKinsey (2020). Shaping the digital transformation in Europe. 
12 Huyer E. (2020). The economic impact of open data: opportunities for value creation in Europe, European Data 
Portal Study.  

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others,  to  real-time  navigation  that  reduces  time  stuck  in  traffic13.  In  turn,  this  has  benefits  in 
terms of tackling climate change, due to reduced CO2 emissions and air pollution.  

Data  is  also  at  the  core  of  the  open  marketplaces  that  facilitate  the  collaborative  or  sharing 
economy. An example of such marketplaces is Dawex14, which acts as orchestrator between data 
holders and data users and facilitates the exchange of data between companies and organizations. 
It  is  estimated  that  this  saves  up  to  7%  of  household  budget  spending  and  reduces  waste  by 
20%15.  

1.2 Political context 

Already  in  March  2019,  the  European  Council  conclusions  stated  that  ‘the  EU  needs  to  go 
further  in  developing  a  competitive,  secure,  inclusive  and  ethical  digital  economy  with  world-
class connectivity. Special emphasis should be placed on access to, sharing of and use of data, 
on data security and on AI, in an environment of trust’16.  

The  European  Strategy  for  Data  of  19  February  2020  responded  to  such  political  calls  to 
strengthen  Europe’s  position  globally  by  making  better  use  of  data-driven  innovation.  In 
particular, it calls for the creation of common European data spaces.  

In  its  conclusions  of  2  October  202017,  the  European  Council  welcomed  the  data  strategy.  It 
stressed  the  need  to  make  high-quality  data  more  readily  available  and  to  promote  and  enable 
better sharing and pooling of data, as well as interoperability. It  also welcomed the creation of 
common European data spaces in strategic sectors. 

The role of common European data spaces  

The European Strategy for Data proposes to establish sector- or domain-specific data spaces, as 
the concrete arrangements  in  which data  sharing and/or data  pooling can happen beyond one 
single  Member  State.  A  common  European  data  space  will  be  composed  of  a  secure  IT 
environment  for  processing  of  data  by  an  open  number  of  organisations,  and  a  set  of  rules  of 
legislative,  administrative  and  contractual  nature  that  determine  the  rights  of  access  to  and 
processing  of  the  data.  Data  will  be  made  available  on  a  voluntary  basis  and  can  be  reused 
against remuneration or for free, depending on the data holder’s decision.  

The  present  instrument  proposes  an  overarching  framework  encompassing  horizontal 
measures relevant for all common European data spaces. The framework will leave room for 
sector-specific rules, governance mechanisms and standards where relevant. The objective of the 
initiative  is  not  to  create  the  common  European  data  spaces  by  law,  but  to  enhance  their 
development by strengthening trust in data sharing and in data intermediaries.  

13 Idem.  
14 See Dawex website for more info. 
15 Rademaekers K. et al. (2017). Environmental potential of the collaborative economy, European Commission.   
16 Council of the European Union Conclusions (22 March 2019).  
17 Council of the European Union Conclusions (2 October 2020). 

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The  European  Strategy  for  Data  was  welcomed  by  the  Member  States  in  the  Council 
Conclusions  of  9  June  2020.  They  called  on  the  European  Commission  ‘to  present  concrete 
proposals  on  data  governance  and  to  encourage  the  development  of  common  European  data 
spaces for strategic sectors of the industry and domains of public interest’18. 

In his opinion on the Data Strategy, the European Data Protection Supervisor (EDPS) underlined 
the political relevance of working towards common European data spaces: ‘one of the objectives 
of  the  Data  Strategy  should  be  to  prove  the  viability  and  sustainability  of  an  alternative  data 
economy  model  -  open,  fair  and  democratic.  Unlike  the  current  predominant  business  model, 
characterised by unprecedented concentration of data in a handful of powerful players, as well 
as  pervasive  tracking,  the  European  data  space  should  serve  as  an  example  of  transparency, 
effective accountability and proper balance between the interests of the individual data subjects 
and the shared interest of the society as a whole’19.  

As stated by President von der Leyen in her State of the Union speech, ‘Europe must now lead 
the way on digital – or it will have to follow the way of others, who are setting these standards 
for  us.’  The  EU  must  seize  the  opportunity  of  this  pivotal  moment  and  ensure  that  it  is  at  the 
forefront  of  the  second  wave  of  innovation  based  on  data.  This  urgency  is  confirmed  by  the 
COVID-19 crisis, which has demonstrated the importance of data for an effective response to a 
global  health  crisis.  Effective  responses  can  only  be  identified  if  as  much  evidence  (data)  is 
available as possible to test out as many hypotheses as possible.  

This  was the  essence for example of the Exscalate4COV initiative20:  In the initiative, an ad 
hoc  consortium  of  18  partner  organisations  tested  available  molecules  with  drug-like 
properties  in  order  to  identify  new  treatments  against  COVID-19.  They  have  been  able  to 
identify several molecules for treatment against the virus that are now being tested in clinical 
trials. This was only made possible because pharmaceutical companies ‘donated’ information 
on these molecules to European research centres. In the absence of established processes for 
the sharing of such data, it took 3 months to obtain it.  

It  is  also  essential  that  the  EU  acts  quickly  because  data  will  play  a  key  role  in  the  economic 
recovery, not least because of its importance for small and medium-sized enterprises (SMEs) and 
startups. The Communication ‘Europe’s moment: Repair and Prepare for the Next Generation’21 
gives  a  prominent  place  to  measures  that  accelerate  the  development  of  the  data  economy, 
including legislative action on data sharing and governance, which is the subject of this impact 
assessment. 

18 Council of the European Union Conclusions (9 June 2020). 
19 European Data Protection Supervisor (2020). Opinion 03/2020 on the European strategy for data.  
20 Exscalate4COV webpage. 
21 COM(2020) 456 final. 

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1.3 Legal context  

1.3.1 Horizontal legislation  

The  current  initiative  covers  different  types  of  data  intermediaries,  handling  both  personal  and 
non-personal  data.  Therefore,  the  interplay  with  the  legislation  on  personal  data  is  particularly 
important. With the General Data Protection Regulation22 and ePrivacy Directive23, the EU has 
put in place a solid and trusted legal framework for the protection of personal data and a standard 
for  the  world.  The  legislative  framework  for  the  common  data  spaces  would  work  within  the 
rules of the existing legislation on the protection of personal data. In particular, it would remain 
the responsibility of each party to identify the suitable legal basis for the processing of personal 
data within a common European data space.  

The proposal will build on the mechanisms present  in  the  existing legislation, in  particular the 
portability right under Article 20 GDPR, that give individuals more control over how their data is 
used. Article 20 of the GDPR gives data subjects  the right  to  move their data (e.g. their social 
media  data,  mobility  or  health  data)  to  another  service,  or  to  allow  a  third  party  to  access  that 
data. This right has a strong potential for reuse of personal data, as identified, amongst others, in 
the  report  on  competition  policy  and  the  digital  era  prepared  for  Commissioner  Vestager  in 
201924. Additionally, this right would give individuals the possibility to make some of their data, 
such as their mobility or health data, available for the common good, if they wish to do so.  

Similarly,  the  initiative  would  not  amend  existing  competition  law  provisions,  and  would  be 
designed in  full compliance with  Articles 101 and 102 of the Treaty on the Functioning of the 
European Union (TFEU), which prohibit anti-competitive agreements and the abuse of dominant 
market power, respectively. 

The initiative would also be in full compliance with the EU’s international obligations, notably in 
the multilateral agreements in the World Trade Organisation and in its regional trade agreements. 

The  current  proposal  would  complement  the  Directive  on  open  data  and  the  reuse  of  public 
sector information (Open Data Directive)25. The Open Data Directive deals with data for which 
public sector bodies have all the relevant  rights.  It  does not,  however, cover public sector data 
subject to the rights of others (e.g. personal data, data protected by intellectual property rights or 
trade secrets). Due to these third party rights, such data cannot be made available as open data, 
i.e. with as little usage restrictions as possible. By facilitating the secure access to such datasets, 
this  proposal  encourages  the  exploitation  of  data  whose  reuse  is  not  regulated  by  the  existing 
Directive.  As  a  consequence,  the  Implementing  Act  on  High-Value  Datasets  under  the  Open 
Data Directive, which is expected to be adopted in 202126, will also be fully complementary with 
this initiative.  

22 OJ L 119, 4.5.2016, p. 1-88.  
23 OJ L 201, 31.7.2002, p. 37-47.  
24 Crémer J., de Montjoye Y.-A. and Schweitzer H. (2019). Competition policy for the digital era, Report prepared 
for Commissioner Vestager.  
25 OJ L 172, 26.6.2019, p. 56–83. 
26 See COM/2020/66 final. 

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1.3.2 Sectoral legislation  

Sector-specific legislation on data access is in place to address identified market failures in fields 
such  as  automotive27,  payment  service  providers28,  smart  metering  information29,  electricity 
network data30, intelligent transport systems31 and electronic freight transport information32. The 
legal  instrument  for  the  common  European  data  spaces  would  support  the  use  of  data  made 
available under such rules without altering them or creating new sectoral obligations. 

1.3.3 Relationship with other planned initiatives 

The  current  legislative  initiative  has  logical  and  coherent  links  with  the  other  initiatives 
announced in the European Strategy for Data. It aims at improving voluntary data sharing within 
and across common European data spaces. This would be achieved by supporting the emergence 
of data intermediaries that could organise data spaces as trusted third parties and provide relevant 
technologies.  In  addition,  it  would  support  the  development  of  technical  and  legal  standards 
relating to the means of the data exchange which, in turn, will enhance trust in data sharing.  

The current initiative is a first step in the two-step approach announced in the European Strategy 
for Data. The initiative will address the urgent need to facilitate data sharing through an enabling 
governance framework. In a second step, the Commission will address issues about who controls 
or  ‘owns’  the  data,  i.e.  the  material  rights  on  who  can  access  and  use  what  data  under  which 
circumstances. The introduction of such rights will be examined in the context of the Data Act 
(2021)33.  Diverging  interests  of  the  stakeholders  and  different  views  on  what  is  fair  in  this 
respect make these issues subject to intense debate, which warrants taking more time. 

While offering an alternative model to the data handling practices of the Big Tech platforms, the 
current legislative initiative is also clearly distinct from the Digital Market Act (DMA) and the 
Digital  Services  Act  (DSA).  The  DMA,  foreseen  for  Q4  2020,  will  combine  two  elements  to 
ensure the proper functioning of the internal market by promoting effective competition in digital 
markets: (i) a set of clear-cut prohibitions and obligations to address known unfair practices of 
online  platforms  with  a  gatekeeping  role,  resulting  from,  among  other  factors,  their  control  of 
large  amounts  of  data;  and  (ii)  a  market  investigation  regime  which  would  allow  tackling 
existing and emerging market failures in digital markets, including in relation to data access and 
use. The DSA, also foreseen for Q4 2020, intends to clarify the responsibilities and obligations 
of  digital  services,  and  in  particular  online  platforms,  based  on,  amongst  other  elements,  an 
evaluation of the e-Commerce Directive. 

The interplay with the other initiatives announced in the Data Strategy is illustrated in the image 
below: 

27 OJ L 188 18.7.2009, p. 1 as amended by OJ L 151, 14.6.2018, p. 1. 
28 OJ L 337, 23.12.2015, p. 35-127. 
29 OJ L 158, 14.6.2019, p. 125-199; OJ L 211, 14.8.2009, p. 94-136. 
30 OJ L 220, 25.8.2017, p. 1-120; OJ L 113, 1.5.2015, p. 13-26. 
31 OJ L 207, 6.8.2010, p. 1-13. 
32 OJ L 249, 31.7.2020, p. 33–48 
33 See COM/2020/66 final. 

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Overview of envisaged data actions. Source: European Commission 

The European Strategy for Data also proposes the creation of sectoral data spaces in areas such 
as mobility and health, and announces sector-specific initiatives, including legislative action for 
the  specific  sectors.  The  Commission  is,  for  example,  working  on  a  review  of  the  current  EU 
type approval legislation for motor vehicles. The initiative aims at ensuring fair and safe access 
to  vehicle  data  and  ultimately  to  offer  better  access  to  more  services  based  on  car  data.  This 
initiative is envisaged for 2021. 

The image below shows the interplay of the horizontal framework with the sectoral initiatives. 

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Source: European Commission 

The  development  of  common  European  data  spaces  will  be  supported  financially  under  the 
Digital Europe programme and the Connecting Europe Facility2. The current legislative initiative 
and the financing from these programmes will mutually reinforce each other. 

2.  PROBLEM DEFINITION 

2.1.  What is the problem? 

Source: European Commission 

As described in Chapter 1, the economic and societal potential of data use is enormous, in terms 
of new products and services based on novel technologies, more efficient production, and tools 
for combatting societal challenges. The problem that this initiative addresses is that this potential 
is  not  realised  due  to  limited  data  sharing  in  the  EU.  A  number  of  obstacles  (low  trust  in  data 
sharing, issues related to the reuse of public sector data and data collection for the common good, 
technical  obstacles) stand in  the way of data sharing becoming more prevalent. These problem 
drivers are described in section 2.2. 

The importance of data sharing 

In order to leverage the value of data in the economy and society, more economic operators and 
organisations promoting societal interests need to be able to use data. This will include data held 
by  others,  as  it  is  not  cost-efficient  if  every  company  or  organisation  collects  similar  or  even 
identical data in parallel to others. Digital data can be copied at virtually no cost, and can be used 
simultaneously  by  different  actors  for  an  unlimited  numbers  of  times.  These  characteristics 
distinguish  data  from  traditional  economic  resources.  In  order  to  harness  such  potential,  more 
data needs to be shared among operators and organisations, including against monetary and other 
rewards,  to  have  a  sufficient  amount  of  data  available  for  innovation  in  the  market.  Given  the 

8 

 
 
fact that the availability of resources feeding data-driven innovation benefits the entirety of the 
data-driven economy in the EU, the socioeconomic benefits will positively impact all the vertical 
sectors directly or indirectly linked to the ever-growing EU data economy.  

According  to  the  OECD,  data  access  and  reuse  could  generate  social  and  economic  benefits 
worth up to 1.5% of GDP in the case of publicly held data, and between 1% and 2.5% of GDP 
when also including privately held data34. Data access and sharing can increase the value of data 
to  holders  (direct  impact),  but  it  can  also  help  create  10  to  20  times  more  value  for  data  users 
(indirect  impact),  and  20  to  50  times  more  value  for  the  wider  economy  and  society  (induced 
impact)35.  

An unfulfilled potential 

Difficulties in accessing and using data held by others have been reported repeatedly. According 
to the OECD, ‘individuals, businesses, and governments often face barriers to data access, which 
may be compounded by reluctance to share’36. 

In the recent public online consultation on the Data Strategy, almost 80% of companies reported 
problems  in  data  access.  When  asked  about  the  nature  of  such  difficulties,  72.1%  of  these 
companies  reported  ‘technical  aspects  relating  to  both  data  interoperability  and  transfer 
mechanisms’ and 43.5% the ‘impossibility to find data of the relevant quality’ (multiple choices 
possible). Other issues relate to outright denial of data access (65%) or prohibitive prices or other 
conditions  (41.7%).  This  suggests  that  technical  difficulties  are  an  important  barrier  to  data 
sharing.  

A 2018 report by Deloitte37 highlights the considerable potential for increasing the level of data 
sharing, in  particular of  machine-generated non-personal  data, in  Europe over the next  decade. 
The  report  suggests  that  only  between  43%  and  58%  of  the  potential  of  data  sharing  along  a 
value chain is realised and only 20% and 40% of the potential of sharing between sectors38. The 
report estimates that leveraging this potential would create, in monetary terms, EUR 35 billion of 
value in agriculture by raising yields; reduce costs from road vehicle damage, maintenance and 
repairs by EUR 40 billion; and generate efficiencies in resource management and prevent drug 
counterfeiting in the healthcare sector, saving EUR 14 billion. It could  create as much as EUR 
1.3 trillion of value in manufacturing by improving productivity by 2027. The untapped potential 
of data sharing is confirmed by a recent study on ecosystems  (focusing on health, construction 
and automotive and mobility) carried out by McKinsey39.  

34 OECD (2019). Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across 
Societies, OECD Publishing, Paris. 
35 Idem.  
36 Idem. 
37 Deloitte (2018). Realising the economic potential of machine-generated, non-personal data in the EU, Report for 
Vodafone Group. 
38  Horizontal  data  sharing  is  defined  as  sharing  between  organisations  involved  in  the  same  commercial  or  non-
commercial point of the value chain, e.g. businesses selling the same product in the same market place. Vertical data 
sharing  is  defined  as  sharing  between  organisations  who  have  a  customer  or  supplier  relationship,  directly  or 
indirectly. 
39 McKinsey (2020). Shaping the digital transformation in Europe. 

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Why would companies and individuals share their data? 

What  are the incentives for companies to  share their data? Direct  monetisation is  currently not 
the  main  reason  for  data  sharing.  Respondents  to  a  survey  conducted  by  the  MIT  Technology 
Review  indicate  that  data  sharing  helps  to  obtain  greater  speed  and  visibility  across  supply 
chains,  and  to  support  faster  and  more  innovative  product  development40.  Incentives  for 
companies  to  share  data  include  increased  access  to  data  of  other  contributors  in  exchange  for 
giving access to their own data, analytical results derived from the shared data, the availability of 
services  such  as  predictive  maintenance  services  or  licence  fees,  as  well  as  reduced  time  and 
costs of product marketing. 

The incentive for individuals to share data can vary. It can come from the wish to contribute to 
research on rare diseases or to make local transport more efficient (in the case of data altruism). 
It can also be driven by possibilities to obtain better advice on their personal situation or more 
personalised or cheaper services in exchange for the use of the data. 

The role of platforms in the data economy  

The  consumer-oriented  data  economy  has  given  rise  to  the  development  of  intermediaries  that 
cover the  entire value chain,  from  data  collection (collection through websites, smartphones or 
connected  objects  such  as  thermostats)  to  storage  and  processing  (cloud  infrastructures)  and 
services. This has led to economies of scope and scale in terms of data (i.e. the capacity to not 
only have large volumes of data at their disposal but also data on a variety of human activities), 
resulting in huge advantages in rolling out additional data-driven services, including in the field 
of AI.  

As European industry begins to interconnect factories, suppliers and other business partners and 
clients,  to  deliver  better,  more  personalised  products  in  a  more  efficient  (and  thus  cheaper) 
manner,  questions  related  to  the  organisation  of  such  data  flows  arise.  According  to  many 
bilateral interactions with stakeholders, there is a high level of distrust in integrated tech service 
providers as platforms for industrial data exchange. Large players like Airbus, Siemens, GE or 
MAN therefore sometimes opt for creating their own platforms. However, these can be exposed 
to similar criticism from their business partners (notably SMEs, but also suppliers), who may be 
in a weaker bargaining position to determine data use by such platforms.  

40 McCauley D. (2020). The global AI agenda, MIT Technology Review Insights. 

10 

 
 
                                                           
The current initiative thus represents an important first step in creating a new model for the data 
economy. This has the potential to meet new market demands and allow the EU to become more 
competitive in the data-driven world economy, while maintaining its data sovereignty and its full 
compliance with its international obligations in trade agreements. Such a model is necessary as 
an alternative to the current business model dominated by Big Tech platforms. It would be built 
on  a  division  of  functions  and  the  development  of  common  European  data  spaces  as 
collaborative  ecosystems  in  which  data  would  be  usable  by  a  broader  range  of  organisations 
(public  and  private)  based  on  a  collective  governance  of  data  sharing.  These  data  spaces  will 
constitute the core tissue of an interconnected and competitive data economy in the EU. 

2.2.  What are the problem drivers? 

2.2.1. Low trust in data sharing  

Based  on  the  views  expressed  in  the  series  of  stakeholder  consultations  organised  by  the 
European  Commission  on  data  sharing,  companies  do  not  necessarily  trust  that,  if  they  share 
data, the reuser will use it in line with the contractual agreement. For example they fear that their 
data could be made available to third parties.  

As shown in a 2017 Commission consultation, 20% of companies do not engage in data sharing 
because  of  this  fear41.  Some  companies  fear  that  they  might  lose  their  competitive  advantage 
within  their  market  or  in  prospective  markets  if  they  engage  in  data  sharing.  The  OECD  also 
reports that this is one of the major concerns for both organisations and individuals with regard 
to  data-sharing  constellations42.  Furthermore,  in  the  2020  consultation,  several  companies 
highlighted the difficulty they face when trying to access datasets of other companies, which may 
be reluctant to share data due to this fear43. For example, one insurance company explained that: 
‘Companies  are  reluctant  to  share  data  since  it  is  the  fundamental  basis  of  their  competitive 
advantage.  Therefore,  it  is  critical  to  introduce  appropriate  safeguards  to  develop  a  trusted 
environment.’ Some emerging technologies can track and trace data use within a data ecosystem. 
This  can  improve  trust,  but  the  use  of  these  technologies  in  more  open  ecosystems  is  not  yet 
widespread44. 

The lack of trust leads to high transaction costs, related to finding a suitable data-sharing partner; 
negotiating, drafting and monitoring the contract, and; developing interoperability solutions for 
transferring,  transforming  and  cleaning  the  data45.  This  has  been  highlighted  by  stakeholders 
(especially  SMEs)  since  201746.  The  OECD  confirms  that  these  high  transaction  costs  might 
heavily affect those in a weaker position, notably individuals (consumers) and SMEs47. 

41 European Commission (2017). Synopsis report consultation on the ‘building a European data economy’ initiative.   
42 Idem.  
43 European Commission (2020b). Outcome of the online consultation on the European strategy for data. 
44 E.g. the Connector Architecture of the International Data Spaces Association, part of the Gaia-X initiative.  
45 Deloitte (2018). Realising the economic potential of machine-generated, non-personal data in the EU, Report for 
Vodafone Group. 
46 European Commission (2017). Synopsis report consultation on the ‘building a European data economy’ initiative.   
47 OECD (2019). Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across 
Societies, OECD Publishing, Paris. 

11 

 
                                                           
Bringing  the  offer  and  demand  for  data  together  in  new  market  places  is  a  pre-requisite  to 
solving the problem. These new market places are, however, at risk of not being able to scale up 
sufficiently due to the lack of sufficient trust in them. It is clear that this can happen only upon 
the condition of a sufficient level of trust in intermediaries for market actors to buy-in48. Without 
this, it is unlikely that they will be able to scale up.  

Both  existing  companies  and  start-ups  propose  data  marketplaces,  platforms  or  trusts  and 
personal data intermediaries as a means to improve findability of relevant data, lower the costs of 
transacting in data and propose exploitation of shared resources49. These data intermediaries can 
reduce  transaction  costs,  for  example  by  proposing  standardised  clauses  in  data-sharing 
contracts, providing a platform for data sharing, offering solutions for data interoperability, and 
helping  data  holders  who  may  not  have  the  necessary  skills  to  ensure  compliance  with  data 
protection law50. These facilitators generally aim to remain neutral in the data exchange that they 
accommodate, meaning that they do not accumulate data or monetise on the data exchanged51. 

Personal  data  intermediaries  are  a  specific  category  of  data  intermediaries.  They  seek  to 
empower  individuals  to  exercise  their  rights  under  data  protection  law  and  manage  their  own 
personal  data52.  Already  in  2016,  the  EDPS  highlighted  the  potential  of  these  solutions53.  The 
2020 online consultation showed that close to 80% of the 201 citizens responding consider that 
‘it should be made easier for individuals to give access to existing data held about them, in line 
with  the  GDPR’.  In  the  same  group  of  citizens,  43%  considered  that  this  could  be  achieved 
through practical solutions that allow individuals to exercise control, such as mobile and online 
dashboards or apps54.  

2.2.2. Issues related to the reuse of public sector data and collecting data for the common good 

Data  sharing  is  hampered  by  an  absence  of  appropriate  structures  and  processes,  notably  to 
facilitate data altruism and the reuse of publicly held data that is subject to the rights of others. 

a)

  Limited data-handling capacity and reuse culture in the public sector 

48 Idem; Joint Research Centre, Business-to-business data sharing: An economic and legal analysis, 2020.  
49 COM/2017/09 final; SWD/2017/02 final; the importance of data sharing platforms or institutions is discussed in 
the  French,  UK  and  German  data  or  AI  strategies:  Villani,  Donner  un  sens  à  l’intelligence  artificielle,  2018, 
Hall/Pensenti, Growing the artificial intelligence strategy in the UK, 2017, Report German Datenethikkommission, 
2019; and in the following reports: OECD (2019). Enhancing Access to and Sharing of Data: Reconciling Risks and 
Benefits for Data Re-use across Societies; Open Data Institute, Designing trustworthy data institutions, 2020. 
50 Joint Research Centre, Business-to-business data sharing: An economic and legal analysis, 2020.  
51 This will avoid the problem of platformisation that profits from network effects and economies of scope. There is 
a risk that these neutral entrants may realise that it could be necessary to leave their neutral position and monetise on 
the  data  exchanged  through  their  service  by  offering  added  value  services  in  other  markets.  This  would  lead  to 
problems  of  data  aggregation  analysed  in  consumer  platforms  discussions.  See  also  JRC  (2020);  COM/2020/66 
final. 
52 European Commission (2016). An emerging offer of "personal information management services" - Current state 
of service offers and challenges; Ctrl+Shift (2014). Personal Information Management Services: An analysis of an 
emerging market; 
53  European  Data  Protection  Supervisor  (2016).  EDPS  Opinion  on  Personal  Information  Management  Systems, 
Opinion 9/2016. 
54 European Commission (2020b). Outcome of the online consultation on the European strategy for data. 

12 

 
                                                           
The GDPR has increased awareness on personal data protection in companies, data subjects, the 
public  sector  and  academia  alike55.  While  this  is  a  very  positive  development,  the  increased 
awareness is not always matched by a high level of expertise in the public sector on the rules and 
exceptions.  The  consultation  supporting  the  review  of  the  Public  Sector  Information  Directive 
showed that public sector bodies had difficulties in  managing  risks related to  the reuse of data 
subject to the rights of others, especially personal data56. In addition, public sector bodies have 
signalled57  that  dealing  with  requests  to  reuse  this  specific  category  of  data  represents  a  major 
issue for them, as they lack the technical and legal capacity to process these requests. 

The potential value of this type of data held by the public sector (such as health data or micro-
statistics) is often high for machine learning and research. The challenge is to find ways to make 
it possible to extract knowledge from the data, while fully preserving privacy or other rights that 
may be attached to the data. Technical mechanisms exist that allow controlled processing of data 
that  is  subject  to  the  rights  of  others  (‘safe  reading  rooms’).  Some  Member  States  (notably 
France, Finland and Germany) have established specific bodies underpinned by legislation that 
offer such technical mechanisms, creating secure and privacy-enhancing conditions for the reuse 
of such data.  

In 2018, the Centre d’accès sécurisé aux données58 (Centre for secure access to data) was 
established  by  the  French  government  and  the  National  School  for  Statistics  and  other 
partners to allow the secure processing of statistical micro-data. Finnish legislation recently 
established  the  data  permit  authority  Findata59  with  the  aim  of  providing  researchers 
with a one-stop-shop service for receiving a permit to process data from a range of public 
registers for health and social protection. Similarly, the German  government  has adopted 
legislation  that  will  enable  research  on  the  basis  of  medical  reimbursement  data.  In 
Germany 38 Forschungsdatenzentren (secure data research infrastructures) have been set 
up  in  order  to  facilitate  access  to  sensitive  data  for  researchers  and  more  are  being 
established. 

In spite of these initiatives, the overall capacity of the public sector across the EU to handle these 
types of requests remains low, since public sector bodies are often not equipped to make the data 
available for use in a way that is compliant with data protection rules. At the same time, offers to 
public sector bodies (cities, hospitals) from large companies to collaborate on projects involving 
data can lead to situations in which the company gets de facto an exclusive access to the data60. 

55 COM/2020/264 final. 
56 European Commission (2018a). Synopsis report of the public consultation on the revision of the Directive on the 
reuse of public sector information. 
57 Idem.  
58 Centre d’accès sécurisé aux données website.  
59 FINDATA website. 
60  European  Commission  (2018d).  Study  to  support  the  review  of  Directive  2003/98/EC  on  the  re-use  of  public 
sector information, study prepared by Deloitte. 

13 

 
                                                           
b)

  Lack of means to manage consent-based sharing of personal data at scale 

Individuals  are  increasingly  willing  to  share  their  personal  data  for  the  common  good  and 
research61. This is confirmed by a 2017 public consultation that gathered more than 1 400 replies, 
in which 81% of respondents believed that ‘sharing of health data could be beneficial to improve 
treatment,  diagnosis  and  prevention  of  diseases  across  the  EU’62.  In  addition,  in  the  2019 
Eurobarometer63,  six  in  ten  respondents  indicated  that  they  would  be  willing  to  securely  share 
some of their personal information to improve public services.  

Pilot initiatives for individuals to give access to  64 their data for altruistic reasons do exist. They 
remain,  however,  limited  in  scale.  One  example  is  a  citizen-driven  model  of  collaborative 
governance  and  management  of  health  data  called  Salus  Coop65.  Other  examples  are  the  pilot 
projects  in  La  Rochelle,  Nantes  and  Lyon.  Nantes  has  used  data  made  available  by  citizens  to 
develop  an  energy  transition  scheme  for  the  city.  La  Rochelle  intends  to  improve  mobility 
services and public transport through insights gained from such data. Lyon aims to help socially 
excluded  families  and  to  simplify  the  life  of  citizens  who  do  not  speak  French66.   During  the 
COVID-19  crisis,  the  German  Robert  Koch  Institut  developed  the  Corona  Datenspende-App, 
allowing  individuals  to  provide  their  fitness  tracker  and  smart  watch  data  to  help  determine 
patterns  of  the  spread  of  the  virus67.  Such  opportunities  were  already  identified  in  the  Villani 
Report68,  which  recognised  the  potential  of  ‘civic  data  sharing’,  i.e.  data  contributed  by 
individuals for the benefit of public services or research. 

Despite these efforts,  researchers, innovators  and public sector organisations lack the means to 
collect personal data at scale, based on the consent of the data subject or following the exercise 
of  their  right  to  data  portability  provided  by  the  GDPR.  This  is  confirmed  by  the  2020  public 
consultation,  which  showed  that  almost  70%  of  participating  citizens  considered  there  are  not 
enough mechanisms  to  give their consent  to  the  processing of their data  or they simply do not 
know  about  them  (18.4%).  Therefore,  personal  data  sharing  for  the  common  good  remains 
underdeveloped and it is difficult to establish sufficiently large data pools69.  

There are currently no clear rules and processes in place in a large majority of the Member States 
that address the issue of data altruism. For health data, only Denmark has already put in place a 

61 Recital 33 of the GDPR; Halvorson G. C., Permanente K. and Novelli W. D. (2014).  Data altruism: honouring 
patients’ expectations for continuous learning, Institute of Medicine Commentary, Washington, DC. 
62 European Commission (2018b). Synopsis report of the public consultation on Digital transformation of health and 
care in the context of the Digital Single Market.  
63  European  Commission  (2019c).  Special  Eurobarometer  503:  Attitudes  towards  the  impact  of  digitalisation  on 
daily lives.  
64 The notion of ‘donation’ should be used with care as it may suggest that consent for the processing of data can no 
longer be withdrawn, which would be counter to Article 7(3) GDPR. 
65 SalusCoop website.  
66 CNIL (2017) La plateforme d’une ville, CAHIERS IP N.5.  
67 Corona-Datenspende website.  
68  Villani,  C.,  (2018).  For  a  meaningful  artificial  intelligence:  towards  a  French  and  European  strategy,  Report 
from a parliamentary mission from 8 September 2017 to 8 March 2018.  
69 BBVA (2019).The case for a regulation on data sharing by users to increase European competitiveness, Policy 
Paper sent to DG CNECT.  

14 

 
                                                           
data altruism mechanism and Germany plans to roll it out in 2023, while 15 EU Member States 
are viewing the idea favourably70.  

A  key  barrier  is  that  there  are  currently  no  mechanisms  to  examine  and  attest  whether  the 
organisations behind such schemes are trustworthy and actually use the data for the proclaimed 
altruistic purposes71.  

2.2.3 Technical obstacles to data reuse  

a)

  Interoperability problems for data use across sectors 

The 2019 workshops on common European data spaces72 highlighted a series of issues regarding 
standardisation within the different  sectors. For instance, in  industrial and agricultural  settings, 
data and service providers have selected architectures, ways to describe the data and data formats 
for their platforms, which make it difficult to exchange data. 

This problem is even stronger at the cross-sectoral level. The value of data is often derived from 
combining datasets from diverse sources, possibly coming from different sectors. A 2018 study 
by Deloitte estimated that, depending on the sector, between 24% and 36% of the benefits of data 
sharing will come from sharing between the sectors73. Standards are an important tool for this to 
happen, both from a technical and legal point of view. However, commonly accepted standards 
are failing to emerge in domains where stakeholders have conflicting interests. 

The OECD states that ‘one of the most frequently cited barriers to data sharing and reuse is the 
lack of common standards, or the proliferation of incompatible standards’74. This is confirmed by 
the  2020  public  consultation,  where  91.5%  of  the  respondents  agreed  that  standardisation  is 
necessary  to  improve  interoperability  and  ultimately  data  reuse  across  sectors.  Some  91.1%  of 
respondents  agreed  that  future  standardisation  activities  need  to  better  address  the  use  of  data 
across sectors of the economy or domains of society75. 

b)

  Limited  findability  of  data  that  is  fit  for  a  given  purpose  and  the  related 

uncertainty about data quality 

Companies  often  struggle  to  find  or  obtain  the  data  that  they  need.  In  the  public  online 
consultation  on the Data Strategy, almost  80% of companies reported problems in  data access. 
When  asked  about  the  nature  of  such  difficulties,  43.5%  of  those  companies  signalled  the 
‘impossibility to find data of the relevant quality’ (multiple choices possible).76 In the course of 

70  EU  Health  Consortium  (2020).  Assessment  of  the  EU  Member  States’  rules  on  health  data  in  the  light  of  the 
GDPR.   
71  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte.  
72 European Commission (2019b). Reports of the workshops on common European data spaces. 
73 Deloitte (2018). Realising the economic potential of machine-generated, non-personal data in the EU, Report for 
Vodafone Group. 
74 OECD (2019). Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across 
Societies. 
75 European Commission (2020b). Outcome of the online consultation on the European strategy for data. 
76 European Commission (2020b). Outcome of the online consultation on the European strategy for data.  

15 

 
                                                           
targeted  consultation  activities  undertaken  in  201977,  stakeholders  confirmed  that  findability  of 
data is one of the main barriers to trading data. For example, stakeholders in the environmental 
field  stated  that,  while  there  is  no  shortage  of  environmental  data,  these  data  are  not  easily 
findable, comparable and accessible, that there is a need for harmonised standards and work on 
data  quality,  and  that  these  issues  could  be  addressed  through  the  common  data  spaces78.  The 
measurable  cost  of  not  having  research  data  compliant  with  standards  developed  by  the  FAIR 
initiative  (aiming  to  make  research  data  findable,  accessible,  interoperable  and  reusable)79  is 
estimated at EUR 10.2 billion per year in Europe80. 

Next to findability or discovery of existing data, information about the quality of data is key. It 
allows  the  reuser  to  assess  whether  certain  data  is  fit  for  the  given  purpose.  This  is  especially 
important for big data analytics and AI, including machine learning, to avoid bias in the results. 
A  low  level  of  data  quality  can  have  particularly  severe  consequences  in  certain  sensitive 
domains,  such  as  health  or  critical  infrastructures81.  A  2018  study  on  data  sharing  between 
companies  in  Europe  on  behalf  of  the  Commission  confirmed  the  importance  of  data  quality: 
73% of the 129 companies surveyed indicated that poor or insufficient data quality hampers data 
sharing82.  In  the  2020  online  consultation,  stakeholders  also  signalled  this  problem83.  As  an 
example,  the  Netherlands  Vehicle  Authority  (RDW)  commented  that:  ‘The  main  condition  to 
ensure  the  reuse  of  a  dataset  is  availability  in  general,  quality  of  data,  quality  of  meta-data, 
findability, actuality and accuracy.’  

2.3.  How will the problem evolve? 

According  to  the  OECD,  with  the  increasing  use  of  AI  and  the  Internet  of  Things  (IoT)  the 
supply of, and demand for, data will increase even in traditionally less data-intensive fields, and 
this  to  a  level  that  very  few  organisations  will  be  able  to  meet  alone84.  Therefore,  even  in  the 
absence of EU action, the use of data and data sharing are expected to grow, but would encounter 
the following limitations:  

1.  Consolidation  of  market  actors’  power:  without  measures  to  overcome  the  generalised  low 
trust and uncertainty related to data sharing, the high transaction costs (see 2.2.1) are unlikely to 
change.  Big  Tech  platforms  already  enjoy  a  high  degree  of  market  power  in  several  digital 
markets.  In the absence of measures, including this initiative, they could enter the data-sharing 
market and offer services as data intermediaries85 without substantial competition - an evolution 

77 European Commission (2019b). Reports of the workshops on common European data spaces.  
78 Idem. 
79 FORCE11 (2020). The FAIR data principles.  
80 PwC (2018), Cost of not having FAIR research data, Study prepared for DG RTD. 
81 That applies also for public procurement, which ensures the functioning of many critical public services such as 
health, education, construction, mobility, security, defence, emergency response, etc. 
82 Everis (2018). Study on data sharing between companies in Europe, Study prepared for DG CNECT.  
83 European Commission (2020b). Outcome of the online consultation on the European strategy for data.  
84 OECD (2019). Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across 
Societies. 
85  Tombal  T.  (2020).  Economic  Dependence  and  Data  Access,  International  Review  of  Intellectual  Property  and 
Competition Law, Vol. 51. 

16 

 
                                                           
that some industrial players, for example in the banking sector86, fear. Smaller companies would 
then be confronted with a business dilemma of not being able to offer new data-based services or 
products, or of sharing data through such Big Tech platforms even if this means losing some of 
the value of the data to the platforms. Some stakeholders consider the significant amounts of data 
held by Big Tech platforms to be the single biggest barrier to entry in the digital economy87.  

2. Full economic and societal value derived from data remains untapped: limited data availability 
would lead to  less  innovation in  the EU and  a slower development  of AI, as  underlined in  the 
Villani Report88. It is likely that the public sector in some Member States would facilitate the use 
of  data  that  cannot  be  made  available  as  open  data,  while  others  would  not,  thus  creating  a 
growing gap between the Member States. Data altruism would take off through more standalone 
initiatives,  but  this  would  not  lead  to  data  pools  of  the  necessary  scale  and  cross-border 
dimension. 

innovation,  products  and  services:  cross-sector 
3.  Lack  of  cross-border  data-driven 
standardisation  efforts  would  be  slow  or  could  be  dominated  by  large  players  who  are  already 
working  across  the  different  sectors,  as  indicated  in  the  support  study  for  this  Impact 
Assessment89. Without a harmonised set of rules, Member States would continue to legislate in 
highly  diverging  ways,  which  would  lead  to  an  even  more  fragmented  landscape.  This  would 
make  it  difficult  for  companies  to  develop  pan-European  products  and  services,  and  research 
results would not be representative for the whole of the EU.  

4. Dependency on third countries: data research and the development of AI systems would move 
abroad90, where rules are less stringent. The EU could experience a brain drain of professionals, 
researchers  and  companies91  moving  their  operations  to  third  countries.  The  ambition  to  foster 
data  infrastructures  that  would  make  Europe  more  autonomous,  as  announced  in  the  Data 
Strategy, is also relevant for limiting the dependency on third countries.  

3.  WHY SHOULD THE EU ACT? 

3.1.  Legal basis 

This  initiative is  part of  the 2020 European Strategy  for Data that aims to reinforce the Single 
Market  for  Data.  With  a  growing  digitalisation  of  the  economy  and  society,  there  is  a  risk  of 
Member States increasingly legislating data-related issues in an uncoordinated way, which would 
intensify  fragmentation  in  the  internal  market.  Setting  up  the  governance  structures  and 
mechanisms  that  will  create  a  coordinated  approach  to  using  data  across  sectors  and  Member 
States  would  help  stakeholders  in  the  data  economy  to  capitalise  on  the  scale  of  the  internal 

86 Padilla J. (2020). Big Tech “banks”, financial stability and regulation, Financial Stability Review, Issue 38. 
87 Furman (2019). Unlocking digital competition - Report of the Digital Competition Expert Panel. 
88  Villani,  C.,  (2018).  For  a  meaningful  artificial  intelligence:  towards  a  French  and  European  strategy,  Report 
from a parliamentary mission from 8 September 2017 to 8 March 2018. 
89 European Commission (2020). Support Study to this Impact Assessment, SMART 2019/0024, prepared by Deloitte. 
90 Bughin J., Seong J. et al. (2019). Tackling Europe’s gap in digital and AI, McKinsey Global Institute, Discussion 
Paper. 
91 Delcker J. (2018). Merkel warns of AI brain drain to foreign tech companies, Politico. 

17 

 
                                                           
market. This would be in full respect of the provisions on anti-competitive practices and the ban 
on the abuse of dominant market power, as laid out in Articles 101 and 102 of the Treaty on the 
Functioning of the European Union (TFEU). Thus, Article 114 TFEU is identified as the relevant 
legal basis for this initiative. 

3.2. 

Subsidiarity: Necessity of EU action  

In the EU, the key sectors of the economy span across borders, with the suppliers, producers and 
clients established in different Member States. Data flows form an intrinsic part of digital activity 
and  mirror  these  EU-wide  supply  chains  and  collaborations.  Any  initiative  aiming  to  organize 
such data flows must address the EU single market in its entirety.   

Companies  active  in  the  data  economy  should  be  able  to  benefit  from  the  size  of  the  internal 
market by rolling out  EU-wide products and services. Datasets available in individual Member 
States often do not have the richness and diversity to allow big data pattern detection or machine 
learning. In addition, data-based products and services developed in one Member State may need 
to  be  customised  to  the  preferences  of  customers  in  another,  and  this  requires  local  data.  Data 
needs to be able to flow easily through EU-wide and cross-sector value chains, making it easier 
to launch a cross-border service or to replicate an existing data-based service from one Member 
State to another.  

As they become increasingly aware of the importance of data sharing, including the reuse of data 
held by public sector bodies, Member States have started to legislate on different aspects of the 
data  economy92.  This  creates  a  risk  of  legislative  and  administrative  fragmentation.  France, 
Germany  and  Finland,  for  example,  are  setting  up  administrative  structures  and  processes  to 
allow the reuse of publicly held data, the use of which is subject to the respect of rights of others. 
In Denmark, the Statistical Office has the role of granting permits for research to be carried out 
using  several  data  sources,  including  smart  metering  information93.  Other  Member  States  have 
not  taken  any  legislative  action  in  this  field.  EU  action  would  offer  a  common  vision  to  these 
national  endeavours and ensure that the barriers  and bottlenecks which are common across the 
entire EU economy can be tackled in a coherent manner across the internal market. 

EU-level  intervention  is  ultimately  best  suited  to  increase  the  levels  of  data  reuse  across  the 
economy, as it can lay down the elements that ensure comparable access and use conditions in all 
data spaces. It is unlikely that national intervention would be equally efficient. 

3.3. 

Subsidiarity: Added value of EU action 

Considering the importance of economies of scale for the development of data technologies and 
services,  coordinated  action  at  EU  level  can  bring  greater  value  to  the  European  economy  and 
society  than  action  by  individual  Member  States.  A  Single  Market  for  Data  would  ensure  that 
data  from  the  public  sector,  businesses  and  citizens  can  be  accessed  and  used  in  the  most 

92 See on this and the European Commission (2020). Support Study to this Impact Assessment, SMART 2019/0024, 
prepared by Deloitte. 
93 Statistics Denmark, Data for research.  

18 

 
                                                           
effective and responsible manner possible, while businesses and citizens keep control of the data 
they generate and investments made into their collection are respected. Companies would be able 
to  market  their  products  and  services  in  all  Member  States.  Companies  and  research 
organisations would advance representative scientific developments and market innovation in the 
EU  as  a  whole,  which  is  particularly  important  in  situations  where  EU  coordinated  action  is 
necessary, like the COVID-19 crisis.  

Furthermore, only concerted action by the Member States can ensure that a European model of 
data sharing, with trusted data intermediaries for B2B data sharing and for personal data spaces, 
can take off. Mutual recognition of certification/labelling mechanisms and of a trust scheme for 
data  altruism  will  make  it  possible  to  collect  and  use  the  data  at  the  necessary  scale.  A  ‘light 
touch’  enabling  legislation,  as  proposed  in  this  initiative,  will  ensure  that  the  Member  States 
move in the same direction and at the same speed. 

In the 2020 consultation, 86.4% of the respondents agreed that data governance mechanisms are 
needed  to  capture  the  potential  of  data,  in  particular  for  cross-sector  data  use94.  This  shows  a 
clear added value and relevance of EU intervention to establish a coordinated approach to data 
sharing. 

4.  OBJECTIVES: WHAT IS TO BE ACHIEVED? 

4.1.  General objective 

The general objective of this intervention is to leverage the potential of data for the economy 
and society. This would be brought about by facilitating a higher level of data sharing across the 
entire EU Digital Single Market. 

The  economy  would  be  boosted  by  increased  innovation  and  competitiveness.  Such  benefits 
would, for example, materialise in terms of better and personalised products for customers and of 
important  efficiency  gains  in  industry.  Society  as  a  whole  would  benefit  from  evidence-based 
policies  and  from  the  availability  of  more  data  that  would  help  to  address  societal  challenges 
(e.g.  combating  climate  change,  improving  healthcare  systems,  addressing  the  challenges  of 
ageing societies across the EU).  

This  initiative  would lay  the  foundations  to  tackle  the  problem  drivers  identified  in  Chapter  2, 
and  ensure  that  the  Member  States’  actions  on  data  are  aligned.  It  would  benefit  the  different 
common European dataspaces, by: 

increasing trust in data sharing; 
strengthening mechanisms that increase data availability; 

- 
- 
-  overcoming technical obstacles to the use of data. 

The  initiative  would  underpin  a  new,  ‘European’  approach  for  data  that  would  work  as  an 
alternative to an integrated platform model, dominated by Big Tech but potentially also by any 
other player with a high degree of market power. The policy interest behind the advancement of 

94 European Commission (2020b). Outcome of the online consultation on the European strategy for data.  

19 

 
                                                           
such a model is to truly empower individuals to exercise their rights under the GDPR and to give 
companies more control over the data that they generate and over its value.  

Overview: Intervention logic. Source: European Commission 

4.2. 

Specific objectives 

4.2.1 Reinforcing trust in data sharing 

Trust is a key prerequisite for data sharing. Therefore, the first specific objective of the initiative 
is  to  create  trust  in  data  sharing  as  such.  Common  European  dataspaces  should  become 
environments in which businesses and individuals can trust that the data they exchange or pool is 
secure  and  processed  in  compliance  with  applicable  legislation  as  well  as  with  the  conditions 
they set on the use of such data. Where such a data space is organised by a specific intermediary, 
businesses  and  individuals  should  be  able  to  trust  those.  When  businesses  prefer  not  to  make 
recourse  to  an  intermediary,  they  would  benefit  from  a  framework  composed  of  technical 
standards and their related governance (‘data-sharing schema’) as an alternative means to create 
trust.  

Increased  trust  in  data  sharing  and  the  citizens’  and  companies’  assurance  that  their  ‘sensitive 
data’  (personal  data,  commercially  sensitive  information)  is  processed  in  line  with  relevant 
legislation and the limitations they set in contractual obligations, would serve as an incentive to 
share the data with selected partners. Such assurances should also apply with respect to demands 
to  access  data  by  governmental  authorities,  including  from  third  countries  that  do  not  comply 
with due process requirements. The considerations that are at the heart of the CJEU judgment in 

20 

 
 
case C-311/1895 (Schrems II), examining the impact of broad investigative powers of intelligence 
authorities and invalidating the Privacy Shield are very relevant in this context. 

4.2.2 Making more public sector data available for reuse and facilitating the collection of 

data to be used for the common good 

The  second  specific  objective  is  to  make  more  data  available  for  reuse  for  businesses,  in 
particular  SMEs  and  start-ups,  public  administrations  and  researchers,  by  addressing  the 
problems caused by mainly the lack of institutional capacities and expertise in the public sector, 
as well as by the lack of mechanisms for collecting data for the common good.  

Actions should focus on data that could be made available for reuse by others on the basis of the 
existing legislative framework and where data holders could agree to this. This concerns i) data 
held by public sector bodies that cannot be made accessible as ‘open data’96 but could be used 
under legal and technical restrictions/processed in trusted and secure environments, and ii) data 
that individuals would agree to make available for reuse97 for research, official statistics or other 
altruistic  or  innovative  purposes.  Targeted  measures  would  address  situations  in  which  more 
technical, legal and organisational support would be necessary to make such data available.  

4.2.3  Overcoming  technical  obstacles:  improving  data  findability,  data  quality  and  data 

interoperability across sectors and countries 

Interoperability of data is a precondition for using the data in different contexts. Therefore, the 
third specific objective is to improve data interoperability to increase data sharing across sectors, 
Member States and different types of organisations. 

First,  interoperability  and  generic  standards  could  allow  data  to  be  reused  across  sectors  and 
Member States more smoothly. Second, businesses, researchers and other actors should be able 
to easily find the data they need and ascertain that the quality of such data is fit for purpose.  

Concerns  about  data  quality  affect  all  sorts  of  data-sharing  situations,  including  for  public 
interest  purposes.  This,  together  with  the  issues  around  interoperability,  stand  in  the  way  of 
increasing data sharing. 

5.  WHAT ARE THE AVAILABLE POLICY OPTIONS? 

In Chapter 2 the following problem drivers were identified: lack of trust in data sharing, issues 
related to the reuse of public sector data and collecting data for the common good, and technical 
obstacles to data reuse. 

The specific objectives defined in Chapter 4 aim to overcome these issues by: reinforcing trust 
in data sharing, making more data available for use in the common European data spaces, and 
overcoming technical obstacles. 

In order to achieve the specific objectives, four intervention areas were identified:  

95 ECLI:EU:C:2019:1145. 
96 OJ L 172, 26.6.2019, p. 56-83.  
97 Article 20 of the General Data Protection Regulation.  

21 

 
                                                           
-  mechanisms  to  enhance  the  reuse  of  public  sector  data  that  cannot  be  made  available  as 
open data: these would ensure that more data from public sector databases becomes available 
for use in a trusted way, and would increase the findability of such data; 

-  measures addressing data intermediaries, both in situations of B2B and C2B data sharing: 

this intervention area would increase trust in data sharing; 

-  measures to  facilitate  data altruism:  these would ensure that more data  becomes  available 

for the common good, and would increase trust in altruism schemes; 

-  mechanisms to coordinate and steer horizontal aspects of data governance: these would 
contribute to overcoming technical problems, in particular issues related to interoperability. 

The work of the support study for this  Impact Assessment was split into four separate streams, 
corresponding  to  these  four  intervention  areas.  A  cost-benefit  analysis  and  a  multi-criteria 
analysis was carried out for each of the areas. 

The study gathered evidence through case studies and workshops (on the use of data subject to 
the rights of others and on possible structures of data governance) as well as market research (on 
data intermediaries) and legal analyses (in particular on data altruism).  

5.1.  What is the baseline from which options are assessed? 

In  the  baseline  scenario98,  existing  horizontal  EU  practices  such  as  the  exchange  of  good 
practices between sectors and Member States would continue. An EU study predicts99 that in the 
absence  of  policy  and  legal  frameworks  supporting  the  data  economy,  the  value  of  the  data 
economy,  i.e.  the  overall  impact  of  the  exchange  of  data  on  the  economy,  would  still  increase 
from its current 2.6% of EU GDP, but only to 3.9% of EU GDP.  

On a more granular level, in the baseline scenario Member States would remain free to take their 
own  approach  with  regards  to  the  reuse  of  data  held  by  public  bodies  and  the  use  of  which  is 
subject to the rights of others. As a result, it is uncertain whether such data would become more 
available for reuse for research and development  purposes. More likely, the currently observed 
difficulties  in  allowing  the  reuse  of  datasets  containing  personal  data100  would  remain 
unchanged.  Likewise,  interoperability  issues  across  sectors  and  Member  States  would  likely 
persist while data holders would have no incentive to ensure their data is of the highest possible 
quality and accuracy. Fragmentation as regards access to, and combination of, data of sufficient 
quality would continue.  

5.2.  Description of the policy options 

A number of possible policy options of different strengths can be considered. In addition to the 
‘no  action’  scenario,  they  vary  from  putting  in  place  an  EU-level  coordination  mechanism 
underpinned by non-binding acts to fully-fledged legislation. The legislative intervention in turn 
can  be  split  into  measures  of  lower  and  higher  intensity,  measured  against  the  extent  to  which 

98  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 
99  European  Commission  (2020a).  Final  Study  Report  of  the  Updated  European  data  market  study,  SMART 
2016/0063. 
100 European Data Portal (2018). The PSI directive and GDPR.  

22 

 
                                                           
they deviate from the organisational and legal status quo. The range of options can be expressed 
as follows: 

  Policy option 0:  No horizontal action at EU level – baseline scenario 
  Policy option 1: Coordination at EU level and soft regulatory measures 
  Policy option 2: Regulatory intervention with low intensity  
  Policy option 3: Regulatory intervention with high intensity  

The  measures  under  all  policy  options  would  be  combined  with  investments  in  common 
European data spaces foreseen under the Digital Europe programme (DEP) and the Connecting 
Europe  Facility  2  (CEF).  More  specifically,  the  European  Commission  plans  to  invest  EUR 2 
billion  to  foster  the  development  of  data  processing  infrastructures,  tools,  architectures  and 
mechanisms  for  data  sharing  and 
trustworthy  cloud 
infrastructures  and  related  services.  In  particular,  the  Commission  will  co-finance  technical 
solutions  (common  standards,  profiles  and  technical  specifications)  for  federating  European 
cloud capacities in order to ensure portability, trust, data protection, security and interoperability. 
Such funding is independent from this initiative, since it will support the creation of a technical 
infrastructure for the development of common European data spaces, without directly affecting 
the legal  and governance arrangements for data sharing. On the other hand, the  effects and the 
efficiency  of  the  spending  will  be  augmented  by  the  impact  of  the  legislation,  which  aims  at 
reinforcing trust in data sharing and increasing the overall amount of data being shared. 

to  federate  energy-efficient  and 

The  assessment  does  not  take  into  account  the  interplay  with  further  legislative  measures,  in 
particular the Data Act, which will deal with the issue of fairness in data access and use, and the 
rights and obligations of persons and organisations on data. 

5.2.1 Policy option 0: Baseline scenario - No horizontal action at EU level  

In  the  baseline  scenario,  no  horizontal  action  is  taken  at  EU  level  on  data  governance  and 
interoperability of common European data spaces. However, action may be taken at sectoral or 
Member State level.  

5.2.2 Policy option 1: Coordination at EU level and soft regulatory measures only  

limited 

EU  coordination  and  soft  measures  have  been  used  in  the  area  of  data  sharing  over  the  past 
the  Commission  would  adopt  a 
decade,  with 
Recommendation or guidelines. An exchange of good practices could be organised between the 
Member  States  on  an  ad  hoc  basis.  Investment  actions  would  support  the  deployment  of  data 
infrastructures that can underpin the common European data spaces in specific sectors. 

impact.  Under 

this  scenario, 

5.2.3 Policy options 2 and 3: Regulatory intervention with low or high intensity  

Policy  options  2  and  3  consider  regulatory  intervention  of  low  and  high  intensity  respectively. 
Both policy options have similar objectives, but may lead to a different level of impact in terms 
of costs, benefits and administrative burden. 

Both  regulatory  options  are  presented  together  in  the  following  sections  in  order  to  clarify  the 
difference between them. 

23 

 
A)  Mechanisms for the enhanced reuse of public sector data 

This  intervention  would  allow  for  more  data  to  be  made  available  for  reuse.  It  builds  on  the 
experience of some Member States in the areas of statistics101, mobility102 and health103, which 
have  spurred  further  data-driven  innovation  in  their  countries104.  The  regulatory  intervention 
would require that Member States ensure that public sector bodies set in place the organisational 
structures  and  mechanisms  to  enhance  the  use  of  public  sector  data,  the  reuse  of  which  is 
conditional on the respect of rights of others, and which therefore cannot be made available for 
reuse  under  the  Open  Data  Directive.  This  concerns  public  sector  databases  that  include 
information on individuals or company information (e.g. information on financial systems, or on 
the approval of pharmaceutical drugs). Very few public sector bodies currently have mechanisms 
in place that allow certain types of data analyses (e.g. data mining) on such data.  

The policy options considered are as follows. 

  Under  the  low  intensity  option,  individual  public  sector  bodies  allowing  the  reuse  of  data 
subject  to  the  rights  of  others  would  need  to  allow  such  reuse  in  line  with  a  set  of 
harmonised conditions. Member States would have to establish one single entry point (one-
stop shop) through which reusers can contact public registers holding the data. The one-stop 
shop would provide advice to  reusers. Member States would have to  comply with  a broad 
obligation to have capacity and services in place to facilitate further compatible uses of the 
data.  They  would  be  free  to  decide  upon  the  exact  form  of  these  mechanisms,  taking  into 
account differences between individual sectors. 
In  practice  this  would  mean  that  a  reuser  from  Member  State  A  could  contact  the  single 
entry point in country B to see how to get access to a certain type of data. The single entry 
point would channel the request to the relevant public sector body or bodies. These public 
sector  bodies  would  receive  technical  and  legal  support  for  making  re-use  possible,  but 
would  remain  responsible  for  the  operations.  Member  States  would  have  to  invest  in  this 
support system. 

  The high intensity option would oblige Member States to create one single data authorisation 
body  as  a  central  decision-making  point.  It  would  be  competent  to  decide  on  all  further 
compatible uses.  
In practice this would mean that reusers would be served by a single organisation that would 
offer  technical  solutions  for  querying  the  data  (e.g.  safe  digital  reading  rooms,  or 
mechanisms  to  bring  algorithms  to  the  data)  and  would,  where  relevant,  issue  permits  for 
data  re-use.  This  would  require  national  legislation  to  be  in  place  underpinning  the 
operations  of  the  organisation,  including  in  terms  of  compliance  with  data  protection 
legislation. It could also imply a change in the way in which public registries are managed. 

101 RatSWD (German Data Forum). 
102  Aholainen  J.,  Finnish  solutions  for  opening  up  fare  data,  TRAFICOM;  European  Data  Portal  (2017).  Smart 
mobility in Finland.  
103 Cuggia M. and Combes S. (2019).  The French health data hub and the German medical informatics initiatives: 
two national projects to promote data sharing in healthcare, Yearbook of Medical Informatics. 
104 SITRA website.  

24 

 
                                                           
Both options would include a prohibition for exclusive arrangements for data held by the public 
sector  and  set  out  the  conditions  under  which  situations  having  de  facto  the  effect  of  granting 
exclusive access  would  be lawful.  This  would avoid  discriminatory practices,  and in  particular 
the risk that powerful players in the market get exclusive access to the data (e.g. health data)105. 
Neither option would create a right to re-use. They would both build on situations where re-use 
of the public data is allowed in the Member States for commercial or non-commercial purposes. 

In the design of the options, a number of dimensions were considered, such as centralisation of 
the  decision-making  on  who  can  use  what  type  of  public  register  data  as  compared  to  the 
responsibility of individual bodies, and how to assist potential reusers (other than by centralising 
the decision-making).  

Under both options, Member States would have to ensure that these mechanisms comply with a 
number  of  harmonised,  compulsory  criteria  that  would  ensure  trust  in  the  mechanisms,  also 
across  borders.  Member  States  would  be  required  to  provide  a  secure  data  processing 
environment  to  allow  innovative  processing  of  data  to  which  access  can  be  granted  under 
conditions  controlled  by  the  public  sector  (a  ‘safe  reading  room  for  data’).  Whenever  data  is 
being  transferred  to  a  reuser,  assurances  should  be  in  place  that  ensure  compliance  with  the 
GDPR and preserve the commercial confidentiality of the data. Both options would benefit from 
the use of the technical infrastructures and tools developed with the support of the DEP and CEF 
programmes to ensure interoperability between the solutions offered by Member States. 

B)  A certification/labelling framework for data intermediaries  

In  order  to  lower  transaction  costs  for  data  sharing  or  pooling  within  common  European  data 
spaces,  businesses  and/or 
to  data-sharing 
intermediaries106. In light of distrust in platform business models107, novel service providers are 
emerging but with limited brand recognition. Their business model is based on transaction fees 
or  regular  subscriptions.  It  excludes  own  use  of  the  data  the  exchange  of  which  they  offer  to 
facilitate.  

individuals  may  want 

to  have 

recourse 

The  emergence  of  data  intermediaries  (providers  of  data-sharing  services),  such  as  ‘data 
marketplaces’,  is  largely  supported  by  stakeholders.  Almost  60%  of  respondents  to  the  2020 
online consultation considered that they are useful enablers in the data economy108. Both in reply 

105  Similar  arrangements  have  been  tested  and  worked  well  in  the  context  of  re-use  based  on  the  Open  Data 
Directive. The need for a similar provision for data not covered by the open data Directive was already signalled in 
the evaluation report of the Directive. 
106 OECD (2019). Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across 
Societies, OECD Publishing, Paris, pp. 36-39; The ODI (2020). How do we create trustworthy and sustainable data 
institutions? Blog piece.   
107  Bradbury  D.  (2020).  Distrust  of  Big  Tech  is  contact  tracing’s  biggest  hurdle,  InfoSec  Blog;  Hutchinson  A. 
(2020).  New  report  shows  universal  distrust  in  social  media  as  a  news  source,  SocialMediaToday;  CISION  PR 
Newswire (2019). Brand reputation at risk from consumers' data distrust.  
108 European Commission (2020b). Outcome of the online consultation on the European strategy for data. 

25 

 
 
                                                           
to  the  online  consultation  and  in  a  workshop  on  data  intermediaries  held  in  May  2020109, 
stakeholders mentioned that this new type of facilitator would increase opportunities for cross-
sectoral innovation. They underlined the importance of the neutrality of data intermediaries as a 
tool for businesses’ and individuals’ data sovereignty, contrary to what has been seen until today 
with existing data aggregators110. 

A certification or labelling framework would allow novel data intermediaries to increase their 
visibility  as  trustworthy  organisers/orchestrators  of  data  sharing  or  pooling.  Legislation  would 
define a set of core criteria that should be met by all certified/ labelled intermediaries in order to 
demonstrate  their  neutrality:  absence  of  conflict  of  interest,  no  competition  with  data  users 
(e.g.  no  development  of  own  data  apps  in  competition  with  others,  so  as to  avoid  any  risks  of 
self-preferencing)  and  commitment  to  not  discriminate  between  companies  that  would  like  to 
offer data services (openness obligation). Two types of intermediaries would be covered by this 
scheme: those addressing business users and those addressing individuals (providers of ‘personal 
data  spaces’).  Furthermore,  they  should  be  able  to  ensure  through  technical  and  organisational 
measures that the data are transferred in compliance with the stated preferences of the company 
or individual. 

The two policy options considered are as follows. 

  Under  the  lower  intensity  option,  labelling/certification  would  be  voluntary  for  actors 
involved in data sharing. The awarded labels would be equally valid in all Member States. 
In  practice,  the  provision  of  data  intermediary  services  remains  an  unregulated  activity. 
Data intermediaries could obtain a label or certificate in order to show that their business 
model is in line with a series of requirements set at the EU level. The label/certificate would 
not be a requirement for offering data intermediary services in the EU. 

  Under  the  higher  intensity  option,  the  certification  of  providers  of  data-sharing  services 
would  be  compulsory.  A  compulsory  scheme  would  ensure  that  all  data  intermediaries 
operating  in  the  Union  would  comply  with  the  requirements.  Certification  would  be 
complementary  to  existing  certification  frameworks  (e.g.  under  the  GDPR  and  the 
Cybersecurity Act).  
In  practice,  data  intermediary  services  would  have  to  comply  with  the  requirements  of  the 
certification scheme before they would be able to start operating and offering data-sharing 
services. This would make data sharing a regulated activity.  

Under both options, the labels/certificates could  be awarded by public authorities or by private 
conformity assessment bodies, based on criteria developed at the European level. 

Self-regulation was discarded, as a) there is no natural industry forum for this emerging market 
and  b)  it  was  deemed  that  the  stakeholders  involved  would  not  be  able  to  agree  upon  strict 
criteria  of  neutrality.  Self-regulation  would  also  potentially  lead  to  the  emergence  of  different 

109  European  Commission  (2020c).  Report  of  the  workshop  on  labels  for/certification  of  providers  of  technical 
solutions for data exchange.  
110 Barclays, BBVA, Deutsche Bank AG, HSBC, ING Group and Banco Santander (2019). Advancing the EU data 
framework: user data sharing, Policy Paper sent to DG CNECT.  

26 

 
                                                           
solutions in different sectors and countries, thus increasing fragmentation. Currently there is no 
such self-regulatory certification scheme in place. 

C)  Measures facilitating data altruism  

In order to address the lack of means to manage consent-based sharing of personal data and the 
availability of data in general, the regulatory intervention would require Member States to enable 
data  altruism  by  putting  in  place  the  necessary  laws  and  processes  that  allow  companies  and 
individuals  to  make  their  data  available  for  the  wider  common  good  based  on  consent.  As  the 
2020 online consultation showed, a large proportion of respondents (87%) consider that there are 
not sufficient mechanisms in place for altruistic data sharing, while 83.3% see the need for such 
enabling tools and mechanisms to be able to share their data for the common good111. Thus, it is 
the lack of tools, not of willingness, that hampers data sharing for the common good.  

The two options considered are as follows. 

  The  lower  intensity  option  would  require  that  Member  States  have  in  place  certification 
schemes  for  data  altruism  mechanisms  and/or  organisations  offering  such  mechanisms. 
Certification would be voluntary. Certificates would be issued by private certification bodies, 
or  by  a  public  authority.  Certification  would  be  complementary  to  existing  certification 
frameworks.  
In practice, an organisation engaging in data altruism could apply for certification to show 
that it is a trusted intermediary (this would be voluntary). The application would be handled 
by a public authority or a private certification body. 

  The higher intensity  option  would require Member States  to  have in  place an  authorisation 
scheme  for  data  altruism  mechanisms  and/or  organisations  offering  such  mechanisms. 
Organisations that seek to perform activities facilitating data altruism would have to comply 
with  the  requirements  and  seek  authorisation  before  launching  their  operations.  The 
authorisation  would  be  compulsory,  and  would  be  handled  and  issued  by  a  designated 
national  authority  (which  could  be  an  existing  body).  The  authorisation  could  be  general 
(allowing  data  activities  to  start  upon  notification)  or  ex  ante  (approval  by  the  competent 
authority is a prior requirement for starting the activities). The granted authorisations would 
be  equally  valid  in  all  Member  States.  Member  States’  authorities  would  monitor 
compliance.  As  such,  a  mandatory  authorisation  regime  would  act  as  a  filter  and  an  entry 
barrier  for  entities  that  wish  to  start  providing  such  mechanisms.  It  would  create  an 
intervention that is of higher intensity than a voluntary certification scheme. 
In practice, data altruism activities in the EU could only be carried out by organisations that 
have sought an authorisation from a public authority. 

At  the  core  of  both  options  is  the  wish  to  ensure  that  data  altruism  mechanisms  (operated  by 
public sector organisations, NGOs and other private sector organisations) are truly altruistic. The 
scheme should prevent attempts to describe a data-sharing activity as altruistic, when in fact the 

111 European Commission (2020b). Outcome of the online consultation on the European strategy for data. 

27 

 
 
                                                           
consent  to  commercial  usages  is  ‘hidden’  in  long  and  hard-to-understand  consent  statements. 
Furthermore, organisations engaging in data altruism should be able to ensure through technical 
and organisational measures that the data are used in compliance with the stated preferences of 
the company or individual. 

In  line  with  the  rights  conferred  by  the  GDPR,  these  mechanisms  for  data  altruism  would  be 
based on consent under Article 7 GDPR and build on the portability right provided by Article 20 
GDPR. In line with the GDPR, they should also provide for individuals to withdraw consent 
for the processing of their data. 

Both  options also  foresee the development  of a  European data altruism  portability and consent 
form  similar  to  those  existing  in  the  field  of  blood,  tissue  and  organ  donation,  which  could  be 
tailored to specific sectors and types of data, to be able to easily give and withdraw consent. 

For the higher intensity option, only a public authorisation scheme would qualify. This would be 
justified given the importance of trust and the nature of acts of data altruism, where people and 
companies are making their data (sometimes sensitive data) available for the common good (e.g. 
improving traffic conditions, contributing to health research). For the lower intensity regulatory 
intervention, both certification by a public authority and by private conformity assessment bodies 
are  possible.  For  this  lower  intensity  intervention,  the  Impact  Assessment  study  focused  on 
certification  by  private  conformity  assessment  bodies,  in  view  of  assessing  the  impact  of  two 
clearly contrasting options, representing the key parameters at stake. 

As for the labelling/certification of data intermediaries under B), centralising the authorisation in 
a European body was discarded due to reasons of costs and political feasibility. 

D)  Mechanism  to  coordinate  and  steer  horizontal  aspects  of  governance 

(European Data Innovation Board) 

A European Data Innovation Board would be created to coordinate efforts in Member States and 
at  European  level  to  support  data-driven  innovation,  to  lower  transaction  costs  and  prevent 
further sectoral fragmentation. 

It would coordinate national efforts to make more public sector data available, play a role in the 
certification  or  labelling  of  trusted  providers  of  data-sharing  services  and  take  a  lead  in 
governing  standardisation  and  the  prioritisation  on  standardisation  around  data  sharing,  in 
particular across sectors. The achievements on prioritisation would feed into the Commission’s 
ICT rolling plan for standardisation. 

The two options considered are as follows.  

  In the lower intensity option, the European Data Innovation Board would be a formal Expert 
Group, with a secretariat provided by the Commission. It would include among its members 
representatives of the sectoral data spaces and other interested parties, aiming for a balanced 
representation of the different sectors (avoiding duplication with existing expert groups). 
It would be responsible for facilitating the exchange of national practices and policies on data 
altruism and the use of public data that cannot be made available as open data, and advising 
on the prioritisation of standards for cross-sector data reuse for the Commission’s rolling plan 

28 

 
for ICT standardisation, and on the establishment and maintenance of a schema of standards 
(technical and legal) related to problems common to all data-sharing situations irrespective of 
a sector112. It would also be tasked with facilitating the exchange of national best practices on 
voluntary labels for trusted providers of data-sharing services. As a Commission expert group, 
it would include experts from authorities from each Member State. It would not interfere with 
the  roles  and  powers  of  the  Member  State  authorities,  given  that  it  would  only  advise  the 
Commission and support it in facilitating the exchange of national practices. 
In practice, the European Data Innovation Board would advise and support the Commission 
on matters related to data sharing, focusing on cross-sector issues. 

  In the higher intensity option, the European Data Innovation Board would be a self-standing 
European body with legal personality, in which representation of sectoral data spaces would 
be ensured. It would be supported by a secretariat. In addition to the above functions, it would 
supervise the award process of voluntary labels and, where relevant, authorisations performed 
by the designated Member State authorities. In this sense, the relationship between the Board 
and  the  Member  State  authorities  would  be  closer,  as  they  would  be  overseen  by  this 
European  level  body.  It  would  keep  a  register  of  the  organisations  that  obtained  a  label  or 
authorisation.  These functions go beyond the power of a Commission  expert  group and  can 
only be entrusted to an independent body.  
In  practice,  the  European  Data  Innovation  Board  would  advise  the  Commission,  but  also 
carry out activities autonomously, including supervisory functions. 

In designing the options, the possibility of setting up an informal Commission expert group was 
also  examined.  It  was  found  that  the  political  importance  of  the  subject  matter  warrants  the 
establishment of a formal group or a self-standing independent body. The examples that served 
as inspiration both  for the form  and the tasks of  the body are either  formal  expert groups (e.g. 
European  Union  Ecolabelling  Board)  or  independent  bodies  (e.g.  European  Data  Protection 
Board - EDPB, European Union Agency for Cybersecurity - ENISA).  

Bringing the required functions under the remit of the EDPB was also explored. The EDPB deals 
with the specific issue of personal data protection. Data sharing additionally requires expertise in 
competition  law,  and  in  sector-specific  data  access  and  usage  regimes,  as  well  as  a  technical 
knowledge  of  technical  sharing  mechanisms  and  standards.  Also,  the  composition  of  the 
decision-making  instance  in  the  EDPB,  currently  composed  of  representatives  of  national  data 
protection authorities, would need to be modified or at least complemented, which would require 
amending the legislative text of the GDPR. Therefore, this possibility was not discussed further.  

112 Examples of such standards are: description of actors in a data sharing ecosystem, identification of persons, legal 
entities  and  connected  objects,  authentication,  permissions  on  data  use  (consent  in  the  case  of  personal  data), 
portability of permissions (consent).  

29 

 
                                                           
Summary table 

Policy options 2 and 3 for regulatory intervention with lower and higher intensity 

Intervention area 

Regulatory intervention with low intensity  Regulatory intervention with high intensity 

Mechanisms 
for 
enhanced  reuse  of 
public sector data 

The reuse of public sector data that is subject 
to the rights of others  would have to comply 
with  basic  EU-wide  rules  (in  particular  non-
exclusivity). 

The reuse of public sector data that is subject 
to the rights of others  would  have to comply 
with  basic  EU-wide  rules  (in  particular  non-
exclusivity). 

Member  States  should  create  a  single  data 
licence 
authorisation  body  competent 
further  compatible  uses  of  data  contained  in 
any public register that is subject to the rights 
of others.  

to 

Individual  public  sector  bodies  allowing  this 
type  of  reuse  would  need  to  be  technically 
equipped 
that  privacy  and 
to  ensure 
confidentiality are fully preserved. 

Member  States  should  have  a  single  entry 
point (one-stop shop) in place for persons or 
organisations  that  seek  to  reuse  this  data. 
Member  States  should  have  capacity  and 
services  in  place  to  support  public  sector 
bodies for this type of reuse. 

Certification/labelling 
framework  for  data 
intermediaries  

scheme 

labelling 

Voluntary 
data 
intermediaries  offering  B2B  data-sharing 
services  and  those  offering  personal  data 
spaces. 

for 

to 

key 

criterion 

obtain 
the 
A 
label/certification: 
intermediary 
cannot  use  the  data  as  part  of  its  business 
model. 

the  data 

Compulsory  certification  scheme  for  data 
intermediaries  offering  B2B  data-sharing 
services  and  those  offering  personal  data 
spaces. 

key 

criterion 

the 
A 
label/certification: 
intermediary 
cannot  use  the  data  as  part  of  its  business 
model. 

for 
the  data 

obtaining 

Measures  facilitating 
data altruism  

Obligation  on  Member  States  to  have  legal 
and  administrative  arrangements  in  place  to 
enable data altruism. 

Obligation  on  Member  States  to  have  legal 
and  administrative  arrangements  in  place  to 
enable data altruism. 

European 
Innovation Board  

Data 

Voluntary  certification  scheme 
for  data 
altruism  mechanisms  and/or  organisations 
offering such mechanisms. 

Compulsory  authorisation  scheme  for  data 
altruism  mechanisms  and/or  organisations 
offering such mechanisms. 

Certification  issued  by  private  certification 
bodies or a public authority. 

Authorisation issued by a public authority. 

The  European  Data  Innovation  Board  would 
be  a  light  coordination  mechanism  at  EU 
level  in  the  form  of  a  formal  Expert  Group, 
hosted  by  the  Commission.  It  would  be 
composed  of  representatives  of  the  Member 
States and of representatives for the different 
domains (health, statistics, etc). 

It  would  facilitate  the  exchange  of  national 
practices  on  the  items  covered  by  the  legal 

The  European  Data  Innovation  Board  would 
be  an  independent  European  structure  with 
legal  personality  and 
supported  by  a 
secretariat  (e.g.  inspired  by  the  structure  of 
EDPB).  

In  addition  to  the  functions  under  the  lower 
intensity  option,  it  would  be  tasked  with 
supervisory functions and keeping registers of 
awarded labels and authorisations. 

30 

 
 
 
 
 
 
 
instrument,  and  would  address  cross-sector 
standardisation issues. 

Source: European Commission 

Relation  with  sectoral  initiatives:  The  relation  between  the  horizontal  framework  and  the 
sectoral initiatives is shown in the image at the end of Chapter 1. The horizontal framework will 
provide the building bricks for individual data spaces so that they can be established faster. The 
governance of the individual data spaces should, however, reflect the needs of the sector and the 
set-up of the stakeholder ecosystem and thus be defined by the sector itself and not be prescribed 
by the horizontal framework.  

A specific data space may have its own standards (which can be either EU standards or standards 
devised by stakeholders). Existing governance frameworks, such as the eHealth network in  the 
area  of  health,  will  not  be  affected.  The  European  Data  Innovation  Board  will  include 
representatives  of  individual  common  European  data  spaces  as  they  emerge.  The  horizontal 
framework would leave room for sector-specific lex specialis rules. 

5.3.  Options discarded at an early stage 

No options were discarded from the outset. 

6.  WHAT ARE THE IMPACTS OF THE POLICY OPTIONS? 

6.1.  Economic impact 

The Impact Assessment support study considered as the baseline the total economic value of the 
data  economy  for  the  EU-27  in  2020,  which  is  EUR  325  billion  (2.6% of  GDP).  This  number 
takes into account a correction linked to COVID-19’s impact on the overall EU economy.  

The  graphs  below  illustrate  the  expected  evolution,  compared  to  the  baseline  scenario,  of  the 
direct  economic  value  of  data  under  the  lower  and  higher  intensity  scenarios,  as  well  as  the 
preferred  option  of  a  package  of  lower  and  higher  intensity  interventions  (see  Chapter  8).  The 
fact that the results of the top-down (based on contribution to GDP) and bottom-up (validation 
calculation  based  on  cost-benefit  analyses)  approaches113  are  almost  identical  confirms  the 
solidity of the methodology. 

113  For  more  information  on  these  approaches,  see:  European  Commission  (2020).  Support  Study  to  this  Impact 
Assessment, SMART 2019/0024, prepared by Deloitte. 

31 

 
 
 
                                                           
The graph shows the compared economic impact of the different policy packages for the indicated years. Policy 
package 1 includes low intensity regulatory intervention in all four areas, policy package 2 contains high intensity 
regulatory intervention in all areas, while policy package 3 denotes the preferred, mixed option. Source: SMART 
2019/0024 
In  2028,  the  value  of  the  data  economy  would  increase  from  EUR  533.5  billion114  (3.87%  of 
GDP) under the baseline scenario: 

- 

- 

to between EUR 540.5 and 544.0 billion if the lower intensity regulatory intervention was 
introduced (from 3.92% to 3.94% of GDP); 
to  between  EUR  542.7  and  547.3  billion  if  the  higher  intensity  regulatory  intervention 
was introduced (from 3.93% to 3.97% of GDP). 

The impacts are calculated until 2025 on the basis of the value of the data economy as projected 
by the International Data Corporation (IDC) for the baseline. The IDC forecast projects a growth 
of the data economy of approx. 8% per year115. The IDC forecast for the growth of the EU data 
economy, however, ends in 2025. In order to calculate impacts beyond 2025, the support study 
took  a  conservative  approach  and  calculated  the  impacts  on  the  basis  of  the  GDP  growth  rate 
forecast of the OECD (1.5% per year)116. For this reason, the impacts beyond 2025 are based on 
a much lower per annum growth rate. 

At first sight, the gains (of between EUR 7 and EUR 10.5 billion for the lower intensity option 
and between EUR 9.2 and EUR 13.8 billion for the higher intensity option) seem relatively small 
compared to the overall size of the data economy that is taken as the baseline for the calculation. 
It should, however, be borne in mind that they are based on a conservative approach, focusing on 
the direct impact, and only to a very limited extent on the indirect impact, of the set of measures 
under consideration. Indeed, the calculations in the support study do not cover the full range of 
potential impacts of the measures on the economy and society. This also explains the large gap 
between the impact, as calculated in the impact assessment study, and more general studies that 
look  at  the  potential  of  data  sharing  for  the  economy  and  society.  Examples  are  the  estimated 
EUR  1.3  trillion  in  increased  productivity  by  2027  in  manufacturing  through  IoT  data117,  or 
savings  of  approximately  EUR  120118  billion  a  year  in  the  EU  health  sector.  Ultimately,  as 
estimated  by  the  OECD,  the  economic  value  of  improved  data  sharing  could  amount  to  up  to 
2.5% of GDP119. 

This broader potential should be kept in mind when assessing the effects of the measures. The 
initiative is a necessary first step in the process of creating common European data spaces. It can 

114  For  more  information  on  these  approaches,  see:  European  Commission  (2020).  Support  Study  to  this  Impact 
Assessment, SMART 2019/0024, prepared by Deloitte. 
115  European  Commission  (2020a).  Final  Study  Report  of  the  Updated  European  Data  Market  Study,  SMART 
2016/0063. 
116 OECD (2019). Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across 
Societies, OECD Publishing, Paris. 
117  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 
118 McKinsey (2020). Shaping the digital transformation in Europe. 
119 OECD (2019). Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across 
Societies. 

32 

 
                                                           
make data markets in different sectors function better by creating trust. However, the full range 
of benefits from the measures rely on actors in the common data spaces seizing the opportunities 
offered by these building blocks. The measures taken by the initiative would act as a catalyst to 
increase data sharing across the EU120. This would lead to the creation of more efficient services 
and  new  products  based  on  data,  including  AI.  This  catalyst  effect  would  not  only  benefit  the 
data economy, but the EU economy and society as a whole.  

The  Commission  has  announced  that  it  intends  to  invest  EUR  2  billion  in  data  infrastructures 
through  the  DEP  and  CEF  programmes.  These  investments  in  the  creation  of  a  European  data 
sharing and processing infrastructure will lower the cost for technically implementing the policy 
options  proposed  in  the  current  instrument.  At  the  same  time  the  proposed  legislation  will 
reinforce the impact of the investment by increasing trust and making more data accessible. The 
exact effect of the envisaged investments on the different options are hard to establish, and have 
not been taken into account into the calculations. 

The support study to this Impact Assessment shows that SMEs in particular stand to benefit from 
the initiative: in addition to benefits from higher interoperability, standardisation and simplified 
access  to  public  sector  data,  they  would  benefit  from  the  certification/labelling  schemes.  The 
one-off  costs  of  certification/labelling  (EUR  20  000-50 000  for  a  voluntary  label,  and  EUR  35 
000-75 000  for  a  compulsory  certification)  for  data  intermediaries  would  be  countered  by  the 
high gains in both client base and revenue (25-50% increase)121. 

Member States would incur costs to establish the necessary mechanisms to provide services and 
to  carry  out  the  different  tasks,  in  particular  in  relation  to  the  measures  to  facilitate  the  use  of 
public sector data that cannot be available as ‘open data’. However, as outlined below, the direct 
economic  gains  alone  would  outweigh  these  costs  under  both  scenarios122.  Besides,  Member 
States  would  recuperate  a  large  part  of  the  investments  through  fees  for  the  different  services 
related to reuse, and data holders would benefit from significant cost reductions. 

A harmonised horizontal governance framework across the EU would create a level playing field 
for all the Member States. The initiative would ensure a minimum level of harmonisation across 
the EU, while leaving a certain leeway for the Member States in terms of how to organise public 
registries and authorisation mechanisms, building on existing structures. It would create certainty 
for data users across the EU and for those who want to make data available, and increase trust in 
data  intermediaries  and  in  mechanisms  for  making  more  data  available  for  use.  Even  though 
some differences between the Member States would remain (e.g. in terms of the supply of public 
sector  data),  overall  the  measures  would  be  an  important  step  towards  a  more  harmonised 
framework and the creation of a real internal market for data. 

The  positive  impacts  of  the  initiative  are  expected  to  be  spread  across  the  EU  rather  than 
benefiting specific countries. Data-focused start-ups are emerging across the EU, in larger and in 

120  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 
121 Idem. 
122 Idem. 

33 

 
                                                           
smaller Member States. For example, in Romania and Bulgaria the share of data companies’ total 
revenues in 2019 as part of the total revenues of all companies was 3.5% and 3.9% respectively, 
which is similar to France (3.8%)123. Highly harmonised conditions for reuse would help reusers 
from all Member States, regardless of their size or economy. 

6.1.1. Baseline scenario 

In  the  absence  of  EU  intervention,  the  data  economy  would  continue  to  grow  to  an  estimated 
EUR 533.5 billion in 2028124. Without an alternative European model, there would be a risk of 
platformisation and the hegemony of the Big Tech companies in this field. There would only be a 
moderate  increase  in  data  use,  which  would  limit  the  capacity  for  productivity  gains  in  all 
sectors,  in  particular  in  the  traditional  sectors  that  are  currently  undergoing  a  major  paradigm 
shift due to data-driven innovation. 

Industry-driven initiatives paired with national initiatives to support data sharing in sectors that 
are  key  to  the  particular  Member  State  (e.g.  industrial  manufacturing  in  Germany  and  France, 
logistics or agriculture in the Netherlands, forestry in Finland) would emerge, but remain limited 
in terms of impact. Companies would remain wary of data sharing: they would either encounter 
significant costs in doing it themselves, or face the choice of relying on integrated tech vendors 
(which would have stronger negotiating power) or on start-ups (with no brand recognition  and 
capacity to become a relevant player in facilitating data sharing).  

Individuals may come across initiatives, for example driven by the research communities, asking 
them to make available data on altruistic grounds, but would not be provided with trusted means 
to do so. Similarly, researchers would be faced with uncertainty when collecting consent on this 
basis  and  would  thus  be  more  reticent  to  make  use  of  this  mechanism,  resulting  in  losses  in 
advances in science.  

Overall, this would lead to a scenario in which large, integrated tech companies that have already 
collected large volumes of data would further strengthen their position to decide on data access. 
They  would  become  centre  points  of  additional  ecosystems  as  they  expand  into  new  activities 
such as health, insurance or finance. Furthermore, they would be able to reinforce their position 
by acquiring additional data or start-ups that are dependent on them. This would have an impact 
on  the  quality  of  machine-leaning  outcomes  (e.g.  facial  recognition  algorithms),  and  result  in 
concerns regarding data quality and bias.  

6.1.2. Coordination at EU level and soft regulatory measures 

The impact of this policy option depends on the uptake of the Commission’s Recommendations 
or guidelines by Member States. Experience with the two existing soft law measures related to 
data  sharing125  shows  that,  due  to  their  non-binding  character,  they  have  been  taken  up  with 

123  E.g.  in  Romania,  and  Bulgaria  the  share  of  data  companies’  total  revenues  in  2019  were  3.5%  and  3.9% 
respectively,  similarly  to  Member  States  such  as  France  (3.9%).  Source:  The  European  Data  Market  Monitoring 
Tool. 
124  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 
125 SWD(2018) 125 final; OJ L 134, 31.5.2018, p. 12-18.   

34 

 
                                                           
different  intensities  and  at  a  different  pace  by  actors  in  the  data  economy  and  Member  States. 
Therefore,  this  policy  option  would  be  unlikely  to  provide  the  swift  and  harmonised  action 
necessary  for  the  EU  to  become  a  key  player  in  this  emerging  market.  Soft  measures  alone 
cannot  be  relied  upon  to  prevent  the  further  development  of  regulatory  divergences  between 
Member  States.  Additionally,  coordination  at  EU  level  would  also  be  achieved  under  policy 
options 2 and 3. 

Mechanisms to enhance the reuse of public sector data subject to the rights of others  

The  impacts  of  this  policy  option  would  rely  on  the  willingness  of  Member  States  to  set  up 
structures  (such as a one-stop  shop  akin  to  the Health Data Hub, or a single data authorisation 
body like Findata), which would also be subject to a set of uniform conditions. According to a 
workshop  organised  in  the  context  of  the  support  study,  only  an  estimated  nine  to  13  Member 
States  would  likely  implement  such  recommendations126.  In  addition,  the  level  of  ambition  of 
such  guidelines  or  recommendations  would  likely  be  inversely  proportional  to  the  number  of 
Member States adopting them. Ensuring that similar requirements in relation to the use of such 
public  sector  data  are  available  throughout  the  EU  is  a  matter  of  legislation  and  cannot  be 
achieved by soft law. 

Certification/labelling framework for data intermediaries  

Stakeholders interviewed in the context of the support study generally considered that this policy 
option would have little added value compared to the baseline scenario. Developing requirements 
for any label in this emerging market would be difficult as it was deemed that industry would not 
be able to agree upon strict criteria of neutrality. Moreover, soft measures would not guarantee a 
fair and representative selection of certification criteria/requirements for the various types of data 
intermediaries active in the EU. This policy option could lead to the adoption of different labels 
in the Member States and sectors and, thus, to further fragmentation. 

Measures facilitating data altruism  

Similarly to the baseline scenario, individuals would not have trusted means to share their data 
on  altruistic  grounds.  The  Commission  could  host  expert  exchanges  and  publish  guidance  to 
support  individuals  and  researchers,  who  would  also  face  uncertainty.  Such  guidance  would, 
however, not provide sufficient assurances to consumers or researchers for concrete use-cases.  

Some interviewed Member States considered that an EU-level coordination mechanism for data 
altruism mechanisms would reduce their workload by avoiding multiple bilateral discussions, but 
would  not  necessarily  accelerate  the  discussions.  In  addition,  they  considered  that  only  the 
Member  States  that  are  already  actively  pursuing  data  altruism  mechanisms  would  likely 
participate. Private sector interviewees considered that coordination at EU level could take very 
long  and  not  result  in  concrete  action.  As  adoption  of  the  measures  would  be  voluntary,  this 
could widen the data altruism gap between different Member States and companies. 

126  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 

35 

 
                                                           
Last,  but  not  least,  protecting  individuals  against  data  altruism  mechanisms  that  are  not  truly 
altruistic is a matter of legislation and cannot be guaranteed by soft-law measures. 

European level mechanisms for coordination of standardisation 

The costs of an informal group of 10 experts participating in four 3-day meetings per year would 
amount to around EUR 24 000 per  year. In addition, the employers of the participating experts 
would incur costs. The costs related to the adoption of standards would be borne by industry, as 
this option does not entail any mandatory standards127. 

However, it was found that  the creation of an informal expert group for governance aspects  of 
data  sharing  would  be  unlikely  to  have  any  effects  at  all,  due  to  its  informal  nature.  Indeed, 
according  to  the  study  team’s  estimates,  it  would  increase  the  number  of  data  users  only  by 
0.1%128. 

 Multi-criteria analysis 

A  multi-criteria  analysis  (see  Chapter  7)  was  not  performed  for  this  policy  option  because,  as 
indicated  above,  its  effectiveness  is  limited  and  dependent  on  uptake  by  Member  States  (and 
hence it is not quantifiable). Furthermore, during the interviews and workshops conducted with 
stakeholders  in  the  context  of  the  support  study,  shortcomings  were  identified  for  each 
intervention area. 

6.1.3. Policy option 2: Lower intensity legislation 

This policy option entails the softer and less expensive options in all four intervention areas. The 
measures  are  expected  to  yield  considerable  benefits  in  the  form  of  enhanced  reuse  of  public 
sector data, elevated trust in data intermediaries and data altruism, as well as better coordination 
in  the  field  of  standardisation.  Compared  to  the  baseline  scenario,  it  would  also  directly 
contribute  to  the  growth  of  the  data  economy  by  between  EUR  7  and  EUR  10.5  billion  in 
2028129. 

Mechanisms to enhance the reuse of public sector data subject to the rights of others – one-stop 
shop 

Under this option, public sector bodies which grant permissions for the reuse of data  subject to 
the rights of others would need to be technically equipped in a way that ensures that privacy and 
confidentiality  are  fully  preserved.  Member  States  would  have  to  set  up  a  one-stop  shop  for 
reusers  and  support  mechanisms  to  provide  public  sector  bodies  with  the  necessary  legal  and 
technical expertise.  

This  option  would  foster  trust  through  transparency  between  data  reusers  and  data  holders,  as 
well  as  trust  among  the  general  public  –  particularly  if  the  one-stop  shop  provides  expert 
guidance to citizens on their rights under data protection laws.  

127  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 
128 Idem. 
129 Idem. 

36 

 
                                                           
Benefits to public sector bodies, researchers and businesses as reusers include:  

  Time  and  resources  saved  in  identifying  the  data  holder  with  the  desired  data  and  in 

 

accessing already interoperable data across sectors; 
Increased fairness in access to such data, i.e. all reusers would have equal access to valuable 
information on how to acquire permission to re-use that data, which would likely result in an 
increase in such reuse; 

  Access to expert guidance, potentially resulting in time and resources savings related to legal 

training; 

  Access to data of a higher quality  (since holders would have an incentive to ensure quality 
knowing  that  the  data  would  be  reused)  and  potentially  to  better  tailored  data  (since  data 
holders would have a clearer views of reusers’ needs). 

Benefits to individual public sector bodies (as data holders) would include: 

  Access to expert guidance, potentially resulting in time and resources savings related to legal 

training; 

  Access to technical guidance on how to allow data reuse, resulting in a decreased risk of data 

breach and the associated costs;  

  Time  and  resources  saved  by  not  providing,  and  maintaining,  a  secure  data  processing 

environment;  

  Access  to  an increased  amount of research  resulting from  a higher demand for such data  – 

leading to better policymaking.  

In  order  to  determine  and  calculate  the  costs  and  benefits  of  this  intervention  area,  national 
experiences  with  such  mechanisms  (e.g.  Findata,  Centre  d’accès  sécurisé  aux  données, 
Forschungsdatenzentren) were taken into account. 

Mechanisms to enhance the reuse of public sector data subject to the rights of others: 
Costs and benefits130 

Costs 

Benefits 

One-off  investment  of  €10.6  million  for  Member 
States  to  establish  the  mechanisms  to  handle  the 
data and create the one-stop shops.  

Annual  maintenance  costs  for  Member  States  of 
€600 000 per year. 

Income  across  the  Member  States  for  providing 
services  would  amount  to  approximately  €41.8 
million per year (assuming an average fee of €500 
per application).  

Public  sector  bodies  across  the  EU  would  save 
around €684 million/ year due to the lower cost of 
data processing and management.  

Cost savings for reusers of €49.2 million /year as a 
result  of  easier  reuse  of  data  (e.g.  easier  data 
discovery). 

130  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 

37 

 
 
 
 
 
 
                                                           
Voluntary certification/labelling scheme 

Data  intermediaries  would  bear  the  cost  of  obtaining  and  maintaining  the  certification  or 
label as well as implementation costs to ensure compliance with the requirements. However, as 
this would be a purely voluntary mechanism, SMEs would not be disproportionately burdened. 
Data reusers might be impacted by indirect transaction and implementation costs, as the certified 
intermediaries might increase the user charges to cover the cost of certification. 

The  benefits  mainly  include  the  increased  trust  between  actors,  leading  to  further  efficiency 
gains, time savings, increase of the client base and data transactions and therefore increase in 
revenues,  allowing  data  intermediaries  to  scale  up,  both  regarding  gains  in  client  base  and 
revenue. As an indirect benefit, there would be a competition increase for data intermediaries in 
both the B2B and C2B markets131. 

Certification/labelling  would  have  a  cumulative  benefit  in  terms  of  company  growth132. 
Increased  trust  in  the  market  could  also  lead  to  an  increase  in  funding,  as  investors  would 
consider  it  safer  to  invest  in  certified  companies.  Data  holders  would  have  the  opportunity  to 
monetise more from data sharing while more individuals would be willing to share their personal 
data through the certified platforms. 

Since certification would be voluntary, the positive impacts of this policy option depend on the 
number of data intermediaries that decide to obtain certification. Given that this is an emerging 
market,  stakeholders  indicated  that  they  favour  a  voluntary  scheme,  as  it  would  provide  an 
opportunity to see what works and what does not, without disturbing data markets133.  

The contrast between the seemingly low overall impacts and the high benefits for the individual 
intermediaries  is  justified  by  the  narrow  scope  of  the  specific  intervention  measures.  Even 
though the individual benefits are high, the total impact on the overall value of the data economy 
remains low. 

Voluntary certification/labelling scheme: 
Costs and benefits134 

Costs 

Benefits 

One-off  cost  of  €20  000-50 000  for  obtaining  the 
label/certification. 

Efficiency  gains,  time  savings:  25%-50%  business 
development time acceleration. 

€20 000-35 000/ 
label/certification. 

year 

for 

renewing 

the 

Increase  in  client  base  and  data  transactions  leading  to 
increase  of  revenues  (25%-50%  expected  increase  in 
revenues and client base). 

Up to 25% competition increase for data  intermediaries 

131  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 
132  European  Commission  (2020c).  Report  of  the  workshop  on  labels  for/certification  of  providers  of  technical 
solutions for data exchange. 
133 Idem.  
134  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 

38 

 
 
                                                           
in  both  the  B2B  and  C2B  markets  in  a  2-5  years’ 
timeframe. 

In  the  first  year  after  certification,  company  revenue  is 
expected  to  double,  the  following  year  to  increase  by 
50%, and the third year to increase by 25%. 

Additional  revenues  of  €48  million  per  intermediary  in 
the year 2028. 

Voluntary certification framework for data altruism services 

An  obligation  on  Member  States  to  implement  a  voluntary  certification  scheme  for  data 
altruism mechanisms would create trust, and would result in more data being made available for 
the common good.  As certification could be done also by public sector bodies, costs could be 
subsidised  for  certain  entities  depending  on  size,  for  example  for  an  SME  (if  for-profit 
approaches are also allowed) or NGO. In addition, NGOs could receive an approximately 10% 
discount  for  authorisation.  Alternatively,  certification  could  be  acquired  without  any  fees,  for 
free. 

A  certification  mechanism  would  allow  a  new  category  of  entities  in  the  data  ecosystem  to 
flourish (e.g. data charities, data cooperatives for the common good, certification entities and the 
development of a new non-for-profit business opportunity for existing NGOs). It is expected that 
by  the  year  2028  there  would  be  around  1 250  intermediaries  facilitating  data  altruism,  with 
around 5 million citizens and 500 companies participating in such schemes135. This policy option 
would ultimately streamline data altruism and reduce organisational, technical and legal costs in 
the long run.  

As for the altruistic individuals and companies, this would ensure that their data is secure and the 
mechanism is legally compliant and resilient to cyberattacks, thereby increasing transparency of 
and trust in data altruism. Internationally, this could offer an opportunity for the EU to be a front-
runner  in  privacy-enhanced  and  secure  data  altruism  and  to  set  global  standards,  attracting 
foreign  researchers  and  innovators  to  the  EU.  The  benefits  of  this  policy  option  relate  to 
providing an easy and transparent way to access data from various fields, contributing to research 
and  development  as  well  as  improving  decision-making.  This  only  includes  to  a  very  limited 
extent  the  downstream  societal  benefits,  such  as  faster  research,  better  cures  for  diseases  or 
improved mobility, due to the lack of available data to quantify this. 

Voluntary certification framework for data altruism services: 
Costs and benefits136 

Costs 

Benefits 

One-off  cost  for  data  holders  or  data  altruistic  €22  million  for  the  period  2024-2028,  based  on  the 

135 Idem. 
136  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 

39 

 
 
 
 
                                                           
organisations  to  obtain  certification  of  €20 000-
50 000.  If  the  certification  is  carried  out  by  private 
sector bodies, costs could be lowered to €3 800-10 500 
for SMEs and €3 420-9 450 for NGOs. 

€20 000-35 000/ year for renewal. 

predicted  revenues  of  the  intermediaries  and  the  total 
value of data. 

European Data Innovation Board as an expert group 

Costs related to the creation of a formal expert group including all the Member States would 
stem mainly from organising and participating in the meetings as well as the related activities.  

As for the benefits, traditional businesses would benefit from an increased adoption of standards 
by the standardisation organisations, leading to a reduction in costs for acquiring, integrating and 
processing data. Estimates from individual case studies show that adoption of standards for data 
sharing results in increased data-sharing activities. Benefits are calculated on the assumption that 
through  interoperability  made  possible  by  standardisation,  800  companies  would  save  15%  of 
EUR 50 million operational costs over 5 years137.   

European Data Innovation Board as an expert group: 
Costs and benefits138 

Costs 

€280 000/ year (including travel costs amounting to 
ca.  €50  000-70 000  and  operational  costs  of  €180 
000-210 000). 

Benefits 

€1.2 billion in 2028. 

6.1.4. Policy option 3: Higher intensity legislation 

As the analysis carried out in the support study shows, opting for the higher intensity regulatory 
intervention  is  expected  to  produce  the  highest  costs,  due  to  the  establishment  of  mechanisms 
that  would  generate  more  expenses.  However,  it  would  also  potentially  create  the  highest  net 
benefits.  Compared  to  the  baseline  scenario,  it  would  contribute  to  the  growth  of  the  data 
economy  by  between  EUR  9.2  and  EUR  13.8  billion  in  2028139.  For  this option,  the  legal  and 
political feasibility as well as its efficiency were also thoroughly considered. 

A single data authorisation body in each Member State to enhance the reuse of public sector data 
subject to the rights of others 

The costs of a single authorisation body would be higher than in policy option 2, due to the need 
to create a standalone body, which would perform more activities than under policy option 2. It 

137 Idem. 
138 Idem.  
139  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 

40 

 
 
 
 
                                                           
would employ an estimated 25 FTEs once fully running, with each FTE costing approximately 
EUR 75 000 and requiring 1 to 2 weeks of training140.  

In  addition  to  the  benefits  described  for  policy  option  2,  dealing  with  one  single  authorisation 
body would lead to substantial savings for reusers. One stakeholder estimates that not having to 
pre-process  data  from  different  holders  would  save  them  several  days  of  work  each  time.  Not 
having to submit separate data access applications for a given research project would save about 
half the overall time spent applying.  

As data holders, public sector bodies would gain time and resources as a result of lower costs for 
data processing and management (EUR 1 253.4 million /year).  

A single data authorisation body to enhance the reuse of public sector data: 
Costs and benefits141 

Costs 

Benefits 

One-off  costs  for 
the  establishment  of  data 
authorisation bodies of approximately €21.2 million. 

Costs saving of approximately €167 million/ year for the 
EU-27. 

Annual  running  costs  of  approximately  €12.2 
million. 

Additional gains for data holders of €212.7 million /year 
revenue from application fees (assuming an average fee 
of €500 per application). 

A compulsory certification/labelling framework for data intermediaries 

Compared to the lower intensity policy option, costs are expected to be higher. This would make 
a  compulsory  certification/labelling  framework  potentially  problematic  for  smaller  data 
intermediaries.  

The  benefits  of  this  policy  option  remain  similar  to  policy  option  2,  with  25%-50%  expected 
increase  in  revenues  and  client  base  and  up  to  50%  business  development  time  acceleration, 
which  is  related  to  the  increased  trust  between  the  actors  that  would  result  from  compulsory 
certification.  

The certification could be done by a public authority or a private conformity assessment body. 
While  setting  up  an  accreditation  process  for  this  new  field  of  activity  for  private  conformity 
assessment bodies would be time-consuming, certification by an existing public authority could 
be preferable in view of a quick start of the functioning of the scheme.  

A compulsory certification/labelling framework for data intermediaries: 
Costs and benefits142 

Costs 

Benefits 

One-off  costs  of  €35  000-75  000  for  obtaining  the  €16.7 million per intermediary of additional revenues in 

140 Idem. 
141 Idem. 
142  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 

41 

 
 
                                                           
certification. 

the year 2028. 

€20  000-50  000/  year 
certification. 

for 

renewal  of 

the 

Compulsory authorisation framework for data altruism services 

A compulsory authorisation framework for data altruism schemes could ensure generalised 
trust in data altruism within society. However, the public sector would incur costs for creating a 
national authorisation scheme as part of the one-stop shops.  

All organisations (including those that collect data for their own use as well as those that purely 
serve  as  intermediaries)  would  need  to  cover  costs  due  to  the  mandatory  authorisation.  As 
authorisation would be done by public sector bodies, costs could be subsidised for certain entities 
depending on size, for example for an SME (if for-profit approaches are also allowed) or NGO. 
In  addition,  NGOs  could  receive  a  discount  of  approximately  10%  for  authorisation. 
Alternatively, authorisation could be acquired without any fees, for free.  

At the same time, the benefits would be considerably higher than for policy option 2. Thanks to 
increased  trustworthiness,  security  and  awareness  of  the  data  altruism  schemes,  SMEs,  NGOs 
and citizens would be more likely to be willing to share data. It is estimated that by 2028, there 
would be more than 7 million citizens and more than 700 companies taking part in data altruism, 
‘donating’  their  data.  The  authorisation  and  the  trust  it  brings  (regarding  their  compliant  and 
trustworthy data handling and processing) would relieve citizens and companies from the burden 
of verifying the legitimacy of the operations and purposes of the organisations, and it would also 
bring  a  considerable  benefit  for  these  users  in  the  form  of  time  and  effort  savings.  Under  this 
policy  option,  benefits  include  an  easy  and  transparent  way  to  access  data  from  various  fields, 
contributing to research and development as well as improved decision-making143. As for policy 
option 2, the figure in the table below only includes to a limited extent the downstream societal 
benefits due to the lack of quantifiable data. 

Compulsory authorisation framework for data altruism services: 
Costs and benefits144 

Costs 

Benefits 

€3  800-10  500  for  SMEs  and  €3  420-9  450  for 
NGOs. 

€5 000/ year for the maintenance of the authorisation. 

€300 million in the period 2024-2028. 

143 Idem. 
144  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 

42 

 
 
 
 
 
                                                           
European Data Innovation Board as a self-standing entity 

This  option  would  help  achieve  the  objective  of  increasing  data  sharing  by  facilitating  the 
development  of  relevant  cross-industry  standards.  However,  as  for  policy  option  2,  its  success 
depends  on  the  ability  to  ensure  the  participation  of  companies  in  defining  and  adopting 
standards. 

The cost of setting up and running an independent body are higher than that of a formal expert 
group. The budget of comparable bodies (such as the European Data Protection Board) amount 
to  EUR  3.5  million  per  year,  which  is  more  than  10  times  higher  than  that  of  a  formal  expert 
group.  Other  costs  are  highly  variable  and  are  difficult  to  estimate,  such  as  the  costs  of 
documentation and education, guidelines, toolkits, tutorials or webinars. 

Under  this  scenario,  the  benefits  to  traditional  businesses  arise  from  an  increased  adoption  of 
standards by the standardisation organisations, and the resulting reduction in costs for acquiring, 
integrating  and  processing  data.  This  figure  in  the  table  below  is  calculated  on  the  assumption 
that through interoperability made possible by standardisation, 900 companies would save 15% 
of  EUR 50  million  operational  costs  over  5  years.  This  underlines  the  importance  of 
interoperability.  The  small  difference  in  benefits  between  the  lower  and  the  higher  intensity 
regulatory intervention is explained by the marginal increase in the number of companies taking 
up standards: it is estimated that 800 and 900 companies would be concerned respectively for the 
lower and higher intensity options, as the existence of a more formal and stronger body would 
only  marginally  increase  the  uptake  of  standards  by  industry.  The  form  of  the  mechanism 
enhancing standardisation would not  have a decisive impact  on the benefits as long as there is 
such a mechanism in place with the necessary industry representation.  

European Data Innovation Board as a self-standing entity: 
Costs and benefits145 

Costs 

Benefits 

€3.5 million/ year for setting up and running costs.  

€1.35 billion for traditional businesses in the year 2028. 

6.2. 

Social and environmental impact 

The  study  team  contracted  to  carry  out  the  impact  assessment  support  study  was  unable  to 
quantify the environmental and social benefits of the different policy options due to the lack of 
available data. However, based on their research and interviews with stakeholders, they provided 
a qualitative assessment of the likely impact of the different options. 

6.2.1. Baseline scenario 

The baseline scenario will see a slower realisation of the potential benefits of data. In the absence 
of coordinated EU action for the reuse of data subject to rights of others in the Member States 
and data altruism mechanisms, the societal and environmental benefits would be limited. Thus, 

145 Idem. 

43 

 
 
                                                           
the potential value of data altruism in the EU, in particular for scientific research and improved 
public policy and services, would not be unlocked 146. 

6.2.2. Coordination at EU level and soft regulatory measures 

As mentioned above, the impact of this option is contingent upon uptake by Member States.  

If  all  Member  States  decide  to  set  up  structures  to  facilitate  the  reuse  of  publicly  held  data 
subject  to  the  rights  of  others,  environmental  and  social  benefits  could  be  similar  to  those 
under policy options 2 and 3. However, this is unlikely to materialise. 

The  certification  of  intermediaries  via  an  industry-driven  self-regulatory  certification 
framework  may  incentivise  individuals  to  share  their  personal  data.  However,  as  explained 
above, this option is expected to have little added value as compared to the baseline.  

Indirectly, the creation of an informal Expert Group could lead to new discoveries for health, 
environmental efficiency and other new products. 

6.2.3. Policy option 2: Lower intensity legislation 

The creation of measures to facilitate the  reuse of publicly held data subject to the rights of 
others would result in positive social and environmental impacts due to the increased availability 
and reuse of such data. 

The  societal  benefits  of  setting  up  a  voluntary  certification/labelling  framework  would  be 
twofold:  on  the  one  hand,  society  would  benefit  as  the  potential  of  the  European  data  market 
would  be  unlocked  through  certification,  while  on  the  other  hand  data  flows  through 
intermediaries serving societal purposes (i.e. health, research) would increase.  

This  policy  option  would  lead  to  positive  societal  benefits  from  data  altruism  mechanisms, 
from  personalised  medicine  and  treatment  to  finding  new  forms  of  renewable  energy.  The 
availability of data would allow researchers to gather the necessary data at the necessary scale for 
insights  and  conclusions  to  be  representative  and  solid.  Data  altruism  would  also  help  public 
authorities in taking evidence-based decisions as well as improving the efficiency of their public 
services thanks to representative insights from individuals. Another important societal benefit is 
that  individuals  would  have  more  opportunities  to  make  their  data  available  for  the  common 
good, and would be confident that reuse of the data takes place in line with EU data protection 
legislation.  Indeed,  at  a  more  general  level,  the  proposed  measures  will  contribute  to  generate 
trust in data sharing, and ensure that European companies and citizens are in control of the data 
they generate. 

Beyond the direct impacts of data sharing, these measures would indirectly benefit both society 
and the environment. The creation of new products and services based on data would lead to, for 
example, better healthcare and mobility, as well as energy savings. At the same time, more data 
use  would  lead  to  more  energy  consumption,  which  underlines  the  importance  of  making  data 

146    European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 

44 

 
                                                           
processing  and  data  centres  more  energy  efficient,  as  indicated  in  the  European  Digital 
Strategy147. 

6.2.4. Policy option 3: Higher intensity legislation 

The environmental and societal benefits of a single data authorisation body would mirror those 
presented in policy option 2, as would the establishment of a compulsory certification/labelling 
framework. 

This  policy  option  would  also  create  similar  societal  benefits  to  policy  option  2  for  data 
altruism. However, due to the trust in public authorisation schemes, it would increase trust and 
security  in  data  altruism  schemes,  which  may  lead  to  more  individuals  making  their  data 
available for the common good.  

Finally, increased data sharing would also lead to the abovementioned indirect benefits to society 
and the environment.  

6.3. 

Impact on SMEs 

This initiative would have an impact on SMEs,  both in their capacity as data intermediaries as 
well as data reusers. In general, more data availability through an increase of trust in data sharing 
will benefit SMEs proportionally more than large organisations, as it is critical to their survival.  

However, as a Commission consultation shows, 40% of SMEs148 struggle to access the data they 
need to develop data-driven products and services, because of a lack of financial resources and 
because they do not have the power to negotiate with data holders. In the absence of EU action, 
SMEs would continue to suffer from the imbalance between them and large reusers that have the 
resources  to  reuse  data  and  adapt  to  change.  As  such,  SMEs  are  the  main  beneficiaries  of  the 
proposed instrument. 

Many  data  intermediaries  are  SMEs.  The  instrument  would  give  a  boost  to  such  SMEs  and 
startups  in  the data economy. The one-off costs for certification/labelling  (EUR 20 000-50 000 
for  a  voluntary  label,  and  EUR  35  000-75 000  for  a  compulsory  certification)  for  data 
intermediaries and renewal  costs would be countered by the high  gains  in  both  client  base and 
revenue (25-50% increase), as well as by a higher possibility to attract investors149. 

Conversely, a more level playing field and reduced legal uncertainty created through EU action 
would  allow  SMEs  and  startups  to  flourish  in  the  EU  data  market.  Taking  into  account  the 
associated  costs,  the  majority  of  stakeholders  consulted  (including  SMEs)150  agreed  on  the 
perceived benefits of such scheme (especially if certification/labelling is voluntary). 

147 European Commission (2020). The European Digital Strategy. 
148 European Commission (2019a). SME panel consultation B2B data sharing - Final Report. 
149  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 
150  European  Commission  (2020c).  Report  of  the  workshop  on  labels  for/certification  of  providers  of  technical 
solutions  for  data  exchange;  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART 
2019/0024, prepared by Deloitte.  

45 

 
                                                           
As regards the reuse of public data subject to the rights of others, businesses have to navigate 
through  the  same  challenges  related  to  finding  and  accessing  datasets  as  researchers.  SMEs, 
many  of  which  have  a  business  model  that  is  based  on  the  use  of  public  sector  data,  do  not 
always dispose of the resources and awareness  needed to  face these challenges, resulting in  an 
unequal access to data that is subject to the rights of others and therefore reduced innovation and 
business opportunities. This impact is cumulative, since in effect larger companies are in a better 
position than small ones to innovate and to develop new products and services. 

During a workshop organised in the context of the support study, stakeholders indicated that an 
industry  driven  self-regulatory  certification  framework  could  give  big  industry  players  a 
stronger role, which would potentially influence the outcome of the discussions taking place in 
the  stakeholder  forum151.  However,  at  the  same  time,  the  market  is  not  mature  enough  for  a 
compulsory certification scheme, as it would likely prevent many new businesses from entering 
the market.  

In  conclusion,  SMEs  would  benefit  both  as  data  intermediaries  and  as  data  users.  As  data 
intermediaries, they would primarily benefit from the voluntary labelling scheme. As the scheme 
would be voluntary, it would not pose a general market barrier. Such a voluntary framework is 
specifically supported by SMEs, as evidenced in the report on SME Panel Consultation152 (end 
2018-early  2019),  as  well  as  the  workshop  on  certification/labelling  in  May  2020153.  As  data 
users, SMEs would benefit from the easier availability of more data (public, personal and non-
personal). The importance of the economies of scale of data sourcing and processing would not 
diminish – but with easier access, and by facilitating the balance of supply and demand for such 
data  and  the  value  derived  from  it  (e.g.  by  supporting  data  marketplaces),  smaller  companies 
would have better access to the value of big data. 

6.4.  Member States’ and stakeholders’ views 

As  described  in  Annex  2,  the  consultation  process  sought  to  collect  the  views  of  EU  Member 
States and stakeholders by means of an online consultation and several workshops and meetings.  

The analysis contributed to the assessment and the choice of the preferred option on the basis of 
the  four  different  intervention  areas.  The  consultation  actions  tried  to  reach  out  to  various 
stakeholders from the public and the private sectors and citizens.  

The  public  online  consultation  was  the  main  consultation  action  targeting  the  citizens,  and  in 
total 201 citizens took part, all from the EU. Most of the views were aligned with those of the 
other stakeholders in general. They expressed strong support for the overall strategy on data and 
the development  of common  European data spaces. Their positive assessment of the initiatives 
on the reuse of data subject to the rights of others for research and innovation purposes, as well 
as on data altruism, was very strong, especially for the purpose of health-related research, as well 

151  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 
152 European Commission (2019a). SME panel consultation B2B data sharing - Final Report. 
153  European  Commission  (2020c).  Report  of  the  workshop  on  labels  for/certification  of  providers  of  technical 
solutions for data exchange; European Commission (2020, forthcoming). 

46 

 
                                                           
as  aspects  relating  to  the  city/municipality/region  of  the  individuals  (including  mobility, 
environment).  

These  findings  should  be  qualified  by  the  fact  that  individuals  would  be  willing  to  share  their 
data for research and for the common good if the right privacy-preserving and secure conditions 
are put in place. This finding is in line with the result of the 2017 public online consultation154.  

Member  States  were  consulted  both  as  policymakers  and  as  data  users.  Regarding  public 
authorities of the Member States, a workshop on a common European data space for the public 
services took place on 10 September 2019. The discussions showed that stakeholders welcome 
the  funding  of  actions  that  would  facilitate  the  participation  of  the  public  sector  in  a  common 
European  data  space,  cater  for  many  flows  (G2G,  B2G,  C2G,  as  well  as  G2B,  and  G2C)  and 
span  a  spectrum  from  bulk  data  transfer,  to  moving  algorithms  all  the  way  to  the  Once-Only-
Principle. They also concluded that a data space that would allow a one-stop shop for ‘data use 
permits’ across the public sector, could put an end to data duplication and facilitate reuse of data 
by others, including the public administration itself.  

In  the  online  consultation,  public  authorities  appeared  as  strong  supporters  of  developing 
governance  mechanisms  supporting  standardisation  activities  for  interoperability  purposes 
(especially application programming interfaces (APIs) and metadata). Even more than the rest of 
stakeholders,  they  considered  that  EU  or  national  government  bodies  have  a  role  to  play  in 
prioritisation  and  coordination  of  standardisation,  and  in  the  clarification  of  the  legal  rules. 
Finally, they appeared as strong supporters of public authorities making a broader range of  data 
that is subject to the rights of others available for R&I purposes and for the public interest.  

Industry organisations, including SMEs and business associations, agreed that the European 
Union needs an overarching data strategy to enable the digital transformation of the society (99% 
of business respondents to the 2020 online consultation). However, they are particularly affected 
by the problem of accessing data, highlighting technical problems (interoperability and transfer 
mechanisms) or simply denied access.  

During  the  workshops  conducted  in  2019  on  common  European  data  spaces,  feedback  from 
representatives  of  the  private  sector  showed  the  sectors  have  different  levels  of  maturity  and 
needs,  but  that  there  is  in  general  a  need  for  ensuring  fair  competition  on  data  markets.  In  the 
data economy in general, one can observe big companies keeping control over large quantities of 
data. In the workshops, companies confirmed common data spaces should allow more data to be 
shared  with  all  types  of  European  actors  (including  SMEs)  and  across  sectors,  allowing  new 
market  dynamics  to  be  created.  The  idea  of  a  voluntary  certification  scheme  for  data 
the  workshop  on 
intermediaries  was  supported  by  SMEs  during 
certification/labelling held in May 2020155. 

the  course  of 

154  European  Commission  (2018b).  Synopsis  report  of  the  public  consultation  on  Digital transformation  of  health 
and care in the context of the Digital Single Market.  

155  European  Commission  (2020c).  Report  of  the  workshop  on  labels  for/certification  of  providers  of  technical 
solutions for data exchange. 

47 

 
                                                           
Academic and research institutions would benefit directly from the decisions on secondary use 
of  data  and  data  altruism,  as  they  could  considerably  lower  their  compliance  costs  related  to 
using  data.  Unsurprisingly,  this  stakeholder  category  agree  with  facilitating  the  reuse  of  data 
subject to the rights of others for research and innovation purposes, and support the data altruism 
concept. Academic and research institutions see potential for the use of such data in areas that are 
similar to those where citizens think their ‘donated’ data could be useful: health-related research 
and  for  aspects  relating  to  the  city/municipality/region  of  the  individuals  (including  mobility, 
environment). 

The European Data Protection Supervisor (EDPS) 
On  16  June  2020  the  European  Data  Protection  Supervisor  adopted  Opinion  3/2020156  on  the 
European strategy for data. The approach of the EDPS towards the strategy in general is positive, 
considering that the implementation of the strategy will be an opportunity to set an example for 
an alternative data economy model (see complete reference in Chapter 1).  

The  opinion  raises  several  practical  issues  that  should  be  taken  into  account  when  moving 
forward with a possible legislative framework. For example, the EDPS considers that companies 
participating in data spaces should be subject to a ‘vetting’ process and data traceability tools and 
obligations could facilitate the role of data controllers when personal data are processed with a 
space. The EDPS also considers that the notion of data altruism and its interplay with the GDPR 
should be clearly defined (since it depends on the consent of the data subject and the portability 
right under article 20 GDPR). It underlines that exceptions for research on personal data cannot 
lead to a broad exemption of the scientific sector from GDPR obligations. GDPR obligations. 

Inception Impact Assessment 

Stakeholders  also  provided  feedback  to  the  Inception  Impact  Assessment  (published  on  the 
Better Regulation Portal between 3 and 31 July 2020). The contributions reflected the replies to 
the online questionnaire, as well as the papers. The feedback dealt with all aspects and measures 
foreseen  in  the  initiative.  Most  of  the  contributions  expressed  support  to  the  initiative  and 
contained  general  comments,  underlying  the  importance  of  fair,  transparent  and  non-
discriminatory  access  to  data,  of  voluntary  data  sharing  (from  private  entities  but  also  from 
individuals) and of standards and interoperability.  

7.  HOW DO THE OPTIONS COMPARE? 
In line with the European Commission’s Better Regulation Guidelines157 and its toolbox158, most 
importantly tool 63, the Impact Assessment study carried out a multi-criteria analysis (MCA)159 

156 EDPS (2020). Opinion 03/2020 on the European strategy for data. 
157 SWD/2017/350.  
158 Idem. 
159  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 

48 

 
                                                           
in order to take full account of the complexity of the subject matter and the level of granularity of 
the analyses carried out. 

As mentioned in section 6.1.2, the option of soft measures only was not analysed further as part 
of the multi-criteria analysis, given that such measures would not provide for a uniform structural 
enabling framework that is essential to achieving both the general and the specific objectives in a 
timely manner. Therefore, the table below contains an analysis of the lower and higher intensity 
regulatory interventions. 

Regulatory intervention with low intensity  Regulatory intervention with high intensity  

Efficiency 

This  option  presents  a  favourable  ratio  of 
costs  and  benefits  where,  in  most  of  the 
areas,  the  benefits  generated  will  likely 
is 
significantly  outweigh 
expected  to  generate  slightly  lower  direct 
and  indirect  economic  benefits  than  the 
higher intensity option (increase from 3.87% 
to  between  3.92%  and  3.94%  of  GDP  by 
2028). 

the  costs.  It 

For the enhanced reuse of public sector data, 
the  lower  intensity  option  would  cause  a 
one-off  cost  of  EUR  10.6  million  for  the 
establishment  of  the  mechanisms,  with  an 
annual  maintenance  cost  of  EUR  600  000 
per  year.  This  would  be  contrasted  by  the 
EUR  41.8  million  as  direct  benefits,  the 
EUR  684  million  per  year  benefit  of  cost 
savings  and  the  benefits  to  reusers  in  the 
amount of EUR 49.2 million/year. 

voluntary 

certification/labelling 
A 
framework  for  data  intermediaries  would 
cost around EUR 20-50 000, with an annual 
maintenance  cost  of  EUR  20-35 000.  The 
benefits  would  materialise  in  the  form  of  a 
25%-50% expected increase in revenues and 
client  base  and  up 
to  50%  business 
development time acceleration.  

Voluntary  certification  of  data  altruism 
schemes would cost approximately EUR 20-
50 000,  with  the  recurrent  costs  of  between 
EUR 20-35 000 for maintaining it. However, 
benefits  would  only  be  around  EUR  22 
million. 

the  costs 

In the case of the European Data Innovation 
Board, 
the  set-up  and 
for 
operations  of  a  formal  expert  group  are 
limited  (around  EUR  280  000  per  year) 
while  the  benefits  (EUR  1.2  billion)  are 
similar  to  those  expected  under  the  higher 
regulatory intervention. 

than 

The  option  also  presents  a  favourable  ratio  of 
costs  and  benefits.  It  is  expected  to  generate 
regulatory 
the 
higher  costs 
interventions,  but  also  greater  overall  direct 
and  indirect  economic  benefits  (increase  from 
3.87%  to  between  3.93%  and  3.97%  of  GDP 
by 2028). 

lower 

Setting  up a central data  authorisation body to 
enhance 
the  reuse  of  public  data  would 
produce  EUR  21.2  million  establishment  and 
EUR  12.2  million  maintenance  costs,  and 
benefits  of  EUR  1 253.4  million  per  year  in 
cost savings and EUR 212.7 million per year in 
the  form  of  revenues  from  application  fees. 
This would make this option less efficient. 

A  compulsory  certification  framework  would 
generate a EUR 35-75 000 one-off cost, with a 
yearly  EUR  20-50 000  as  a  recurrent  cost. 
With  the  benefits  very  similar  to  the  lower 
intensity regulatory option (25%-50% expected 
increase  in revenues and client base and  up to 
50%  business  development  time  acceleration), 
this would be a less efficient option. 

Compared  to  the  lower  intensity  option,  a 
compulsory  authorisation  for  data  altruism 
schemes,  would  produce  a  one-off  cost  of  a 
range  between  EUR  3 420  –  10 500  to  obtain 
the  authorisation,  with  an  annual  recurrent 
maintenance  cost  of  EUR  5 000.  At  the  same 
time,  the  increase  in  altruistic  data  sharing 
would  create  much  higher  direct  benefits,  in 
the  amount  of  EUR  300  million,  making  it  a 
more efficient option. 

For  the  European  Data  Innovation  Board,  the 
costs of setting  up a  self-standing body  would 
be  much  higher  (EUR  3.5  million)  than  a 
Commission  expert  group,  with  marginally 
higher benefits (EUR 1.35 billion). 

Effectiveness 

This option could significantly contribute to 
the  general  objective  of  leveraging  the 

This option is also expected to address the need 
to  leverage  the  potential  of  data  for  the  EU 

49 

 
 
 
the 

through 

technical, 

potential  of  data  for  the  EU  economy  and 
society  as  well  as 
three  specific 
objectives  of  reinforcing  trust  in  common 
European  data  spaces,  making  more  data 
available 
legal  and 
organization  support  as  well  as  overcoming 
technical  obstacles  (e.g. 
interoperability) 
across sectors. 
This  policy  option  would  also  further 
contribute  to  setting  the  foundations  of  a 
Single  Market  for  Data  and  strengthening 
the  EU  data  economy,  since  the  European 
data  market  overall  will  be  significantly 
boosted  through  the  voluntary  certification/ 
labelling  of  data  intermediaries,  which  will 
increase the volume of data flows. Similarly, 
the new opportunity to access and reuse non-
open  public  data  as  well  as  the  new  data 
the 
sharing  schemas  appearing  due 
voluntary certification would also contribute 
to data access and use across the EU. 

to 

The  effectiveness  of  an  expert  group  to 
facilitate  the  development  and  adoption  of 
standards  would  be  limited,  given  the  key 
role of industry’s willingness to take up such 
standards. 

economy  and  society  as  well  as  the  three 
specific  objectives  of  reinforcing 
in 
common  European  data  spaces,  making  more 
data  available  through  technical,  legal  and 
organization  support  as  well  as  overcoming 
technical obstacles (e.g. interoperability) across 
sectors. 

trust 

The  creation  of  a  single  data  authorisation 
body allows the centralisation of reuse requests 
that might contribute to further effectiveness. 

for 

intermediaries 

However,  concerns  have  been  raised  with 
the  ability  of  a  compulsory 
regard 
to 
to 
certification  scheme 
effectively  build  common  data  spaces,  as  the 
higher  certification  costs  and  the  compulsory 
nature  might  prevent  smaller  industry  players 
from  getting  into  the  market.  On  the  other 
hand,  it  would  establish  clear  rules  for  how 
data  intermediaries  are  supposed  to  act  in  the 
European data market. 

Regarding  the  compulsory  authorisation  of 
data  altruism  schemes,  it  is  expected  to  be 
more  effective 
intensity 
voluntary  certification,  given  that  the  trust 
generated by it would incentivise more citizens 
and businesses to altruistically share their data. 

lower 

than 

the 

Coherence 

The  effectiveness  of  a  self-standing  body  to 
facilitate  the  development  and  adoption  of 
standards  would  be  limited  as  well,  given  the 
key  role  of  industry’s  willingness  to  take  up 
such standards. 

This  option  is  in  line  with  the  EU  data 
strategy’s objective of creating common data 
spaces  as  well  as  other  horizontal  and 
sectoral  legislation  currently  in  effect.  It 
does not create coherence issues with major 
EU law. The sharing of “sensitive” data held 
by the public sector or personal data  shared 
under a data altruism scheme can be done in 
line with GDPR requirements. 

This option is also in line with the EU Digital 
strategy  of  creating  common  data  spaces  and 
the horizontal and sectoral legislation currently 
in effect. This option does not create coherence 
issues  with  major  EU  law.  The  sharing  of 
“sensitive”  data  held  by  the  public  sectors  or 
personal  data  shared  under  a  data  altruism 
scheme  can  be  done  in  line  with  GDPR 
requirements.  

This  option  has  the  potential  to  minimise 
friction  with  national  law  compared  to  the 
higher  intensity  intervention  with  regard  to 
the  possible  flexibility  in  the  set-up  of 
structures 
share 
and  mechanisms 
“sensitive”  public  data.  However,  more 
flexibility  would  result  in  a  lower  level  of 
harmonization of the horizontal governance.  

to 

The  far-reaching  horizontal  measure  proposed 
in  the  higher  intensity  regulatory  intervention 
could  be  difficult  to  reconcile  with  some 
national  laws  that  can  limit  the  reuse  of 
(sensitive)  data  held  by  the  public  sector  for 
strictly  non-commercial  purposes.  However,  it 
would  also  provide  for  a  higher  level  of 
harmonization  and  a  more  seamless  single 
market for data. 

Legal/political 
feasibility  

lower 

This  option  is  both  politically  and  legally 
feasible.  The 
intensity  regulatory 
intervention presents a clear advantage over 
the  higher  intensity  regulatory  intervention 
as  concerns  the  possible  flexibility  in  the 
setting up of  structures and  mechanisms  for 

50 

This option is legally feasible, although for the 
public  data 
single  data 
creating  one 
authorisation  body  could  imply  considerable 
legal  or  organisational  challenges.  Concerns 
might  be  raised  by  stakeholders  regarding  the 
for 
compulsory 

certification 

nature 

of 

 
the reuse of public sector data, as well as the 
voluntariness  of  the  certification/  labelling 
mechanisms for data intermediaries and data 
altruism schemes. 

Industry 

The  setting  up  of  a  Commission  expert 
group  presents  no  political  obstacle,  given 
that  it  is  established  by  a  Commission 
decision. 
also 
welcome  the  setting-up  of  a  formal  expert 
group  that  supports  the  coordination  of 
standardisation  rather  than  a  stronger  role 
from  the  EU  under  the  high  regulatory 
intervention. 

representatives 

Proportionality  This option is proportionate and is limited to 
the stakes at hand. It presents a balanced yet 
focused  policy 
intervention.  Allowing 
flexibility  both  regarding  the  structures  and 
mechanisms for the reuse of public data and 
the  voluntariness  of 
the  certification/ 
labelling  of  the  data  intermediaries  as  well 
as the data altruism schemes ensures that the 
proposed  measures  would  not  have  impacts 
beyond what the initiative aims to achieve.  

intermediaries, 
requirements for market entry. 

as 

it  would 

prescribe 

Setting  up  a  self-standing  European  central 
body  that  would  lead  efforts  in  the  domain  of 
standardisation  would  also  be  less  politically 
feasible due to the high costs it would attain. 

is 

stronger, 

This  option,  although 
still 
proportionate  to  the  stakes  at  hand.  Neither  of 
the planned  measures in the intervention areas 
would go beyond what is necessary to achieve 
the  objectives  of  the  initiative.  Given  that  the 
measures  proposed  under  this  option  would 
only  represent  a  more  centralized  or  binding 
variant  of  the  measures  under  the  lower 
intensity regulatory intervention, the difference 
in  proportionality  between  the  two  options  is 
insignificant. 

Source: European Commission, based on the support study SMART 2019/0024 

Efficiency 

Effectiveness   Coherence  

Legal/political 
feasibility  

Proportionality 

Regulatory intervention 
with low intensity 

Regulatory intervention 
with high intensity 

++ 

+ 

++ 

++ 

+ 

+/- 

+ 

+/- 

+ 

+ 

Source: European Commission, based on the support study SMART 2019/0024 

For efficiency, effectiveness and coherence, the scores are given on the expected magnitude of 
impact  as  explained  above:  ++  being  strongly  positive,  +  positive,  and  –  negative.  For 
legal/political  feasibility  and  proportionality,  +  means  that  the  assessment  is  positive,  and  – 
means that it is negative. 

8.  PREFERRED OPTION 

Based  on  the  evidence  presented  above,  a  mixed  package  of  lower  and  higher  intensity 
regulatory interventions is  the preferred option.  Although, based on the  cost-benefit and multi-
criteria analyses, for three of the intervention areas the lower intensity option is more favourable, 
the  higher  intensity  intervention  for  data  altruism  would  yield  higher  economic  and  societal 
benefits, while incurring fewer costs. 

For the enhanced reuse of public sector data, the lower intensity regulatory option would cause 
a one-off cost of EUR 10.6 million for the establishment of the mechanisms and the single entry 
point, with an annual maintenance cost of EUR 600 000 per year for Member States. This would 

51 

 
 
be contrasted by the EUR 41.8 million as direct benefits, the EUR 684 million per year benefit of 
cost  savings  and  the  benefits  to  reusers  in  the  amount  of  EUR  49.2  million/year.  This  option 
would  be  more  favourable  than  the  higher  intensity  regulatory  intervention,  which  would 
produce EUR 21.2 million establishment and EUR 12.2 million maintenance costs for Member 
States,  which  would  be  partially  counterbalanced  by  the  EUR  1 253.4  million  per  year  in  cost 
savings and EUR 212.7 million per year in the form of revenues from application fees160. 

For  increasing  trust  in  data  intermediaries,  in  a  voluntary  certification/labelling  framework 
would  cost  around  EUR  20 000-50 000  to  obtain  the  certificate/label,  with  an  annual 
maintenance cost of EUR 20 000-35 000. The benefits would materialise in the form of a 25%-
50%  expected  increase  in  revenues  and  client  base  and  up  to  50%  business  development  time 
acceleration. Compared to this, a compulsory certification framework would generate an amount 
of  EUR  35 000-75 000  one-off  cost  for  obtaining  the  certificate,  with  a  yearly  EUR  20 000-
50 000 as a recurrent cost for maintaining it. With the benefits very similar to the lower intensity 
regulatory  option  (25%-50%  expected  increase  in  revenues  and  client  base  and  up  to  50% 
business  development  time  acceleration),  the  more  favourable  option  would  be  option  2161. 
However, this option could be considered as an alternative given its structuring function for the 
European  market  for  data  intermediaries,  which  would  lead  to  higher  trust  in  these 
intermediaries.  

To  obtain  a  certificate  under  a  voluntary  certification  mechanism  for  data  altruism  services 
would cost approximately EUR 20 000-50 000, with the recurrent costs of between EUR 20 000-
35 000  for  maintaining  it.  However,  benefits  would  only  be  around  EUR  22  million.  A 
compulsory authorisation would produce a one-off cost ranging between EUR 3 420 – 10 500 to 
obtain  the  authorisation  if  the  public  sector  decides  to  apply  fees,  with  an  annual  recurrent 
maintenance cost of EUR 5 000. Higher trust is expected to lead to an increase in altruistic data 
sharing. This  would create much higher benefits  in  the order of EUR 300 million,  making it a 
more favourable option162. 

The  creation  of  the  European  Data  Innovation  Board  in  the  form  of  a  formal  Commission 
expert group would trigger a yearly cost of EUR 280 000, while yielding around EUR 1 billion 
in  benefits  through  standardisation.  In  contrast,  the  set-up  of  an  independent  body  would  cost 
EUR 3.5 million, more than ten times the amount for an expert group, while at the same time, 
benefits would remain around 1.2 billion for the year 2028163. Thus, the less costly expert group 
would achieve the same goals, with more efficiency. 

Packaging  the  lower  intensity  options  together  with  the  higher  intensity  regulatory  option  for 
data-altruism allows for a targeted and proportional intervention, taking into account the different 
impacts of the individual policy options on the intervention areas, which will lead to a significant 

160  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 
161 Idem. 
162  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte. 
163 Idem. 

52 

 
                                                           
improvement  over  the  baseline  scenario.  It  is  broadly  acceptable  to  stakeholders  and  can  be 
realistically enacted within a reasonable timeframe, which is critical given the expected value of 
the initiative in post COVID-19 recovery programmes. 

This leads to a preferred option that is based on the following elements (schematically captured 
in the image at the end of this section): 

  Mechanisms  for  enhanced  reuse  of  certain  public  sector  data:  a  lower  intensity 
regulatory  intervention  would  prescribe  for  Member  States  to  provide  services  to 
facilitate  the  reuse  of  publicly  held  data  that  is  subject  to  the  rights  of  others  in 
accordance  with  a  set  of  conditions,  without  determining  the  exact  institutional  and 
administrative form. 

  Certification/labelling  framework  for  data  intermediaries:  the  lower  intensity 
regulatory intervention would create a voluntary certification/labelling mechanism, where 
the  designated  authorities  would  handle  the  application  process  and  award  the 
labels/certificates to the compliant data intermediaries. 

  Measures facilitating data altruism: the higher intensity regulatory intervention would 
provide  for  a  compulsory  European  authorisation  scheme  as  a  requirement  to  offering 
services facilitating data altruism. The processing and issuing of authorisations would be 
handled by designated authorities. 

  European Data Innovation Board: as part of a lower intensity regulatory intervention, 
it  would  function  as  a  formal  expert  group,  with  a  secretariat  provided  by  the 
Commission. 
the 
include 
enhancement of interoperability, and the facilitation of the exchange of national practices. 

facilitating  standardisation  and 

functions  would 

Its 

Source: European Commission 

53 

 
 
 
8.1. Estimated impact of the preferred option 
The  Impact  Assessment  support  study164  indicates  that,  while  in  the  baseline  scenario  the  data 
economy  and  the  economic  value  of  data  sharing  are  expected  to  grow  to  an  estimated  EUR 
533.5 billion (3.87% of the GDP) by 2028, this would increase to between EUR 540.7 and EUR 
544.4 billion (3.92% to 3.95% of the GDP) under the preferred option. 

At  the  same  time,  this  policy  option  would  make  it  possible  to  create  an  alternative  European 
model  for  data  sharing  to  the  current  business  model  for  Big  Tech  platforms,  through  the 
emergence  of  neutral  data  intermediaries.  This  initiative  can  make  the  difference  for  the  data 
economy  by  creating  trust  in  data  sharing  as  a  precondition  for  the  development  of  common 
European data spaces, where individuals and companies are in control of the data they generate, 
and are comfortable with the way in which the data are used in innovative ways. 

Indeed, as indicated in section 6.1, the actual impact of this initiative is likely to be far greater 
than  the  benefits  that  can  be  directly  attributed  to  its  different  elements.  By  increasing  trust  in 
data sharing, the initiative would function as a catalyst for the data economy. It would facilitate 
data  sharing  across  the  EU,  unleashing  the  power  of  data-based  innovation  and  supporting  the 
creation of new services and products and more efficiency in industry. It would also contribute to 
new tools for tackling societal challenges, such as climate change, and to better policymaking. 

9.  HOW WILL ACTUAL IMPACTS BE MONITORED AND EVALUATED? 

Due to the dynamic nature of the data economy, monitoring the evolution of impacts constitutes 
a  key  part  of  the  intervention.  To  ensure  that  the  selected  policy  measures  actually  deliver  the 
intended  results  and  to  inform  possible  future  revisions,  the  Commission  would  set  up  the 
monitoring and evaluation process described below. 

The  European  Data  Innovation  Board  would  bring  together  evidence  about  the  situation in  the 
Member  States  and  in  the  different  sectors.  It  would  compile  best  practice  examples  based  on 
feedback from Member States on their implementation measures, and the relative strengths and 
weaknesses  of  these  measures.  Member  States  would  be  asked  to  report  regularly  on  the 
efficiency and impact of the different strands of action in their data market.     

This would help the Commission to closely monitor the uptake of the measures in Member States 
and  amongst  stakeholders,  also  in  view  of  compliance.  If  necessary,  the  Commission  would 
launch infringement procedures. 

Through the Support Centre for Data Sharing, which is planned to be established under the DEP, 
evidence  from  stakeholders  will  be  gathered  on  the  market  efficiency  and  effectiveness  of 
measures taken under this initiative to enhance the reuse of public sector data, data altruism and a 
labelling scheme for data intermediaries.  

The  monitoring  is  divided  into  two  operational  parts:  monitoring  of  the  specific  objectives 
identified  in  the  section  4.2  and  monitoring  of  the  individual  components  that  constitute  the 

164  European  Commission  (2020).  Support  Study  to  this  Impact  Assessment,  SMART  2019/0024,  prepared  by 
Deloitte.  

54 

 
                                                           
preferred  policy  option  described  the  Chapter  8.  For  both  parts,  the  tables  below  present 
operational  objectives  corresponding  to  the  identified  specific  policy  objectives/preferred 
option, indicators that would be used to monitor progress as well as sources of information. 

9.1.  Monitoring of the specific objectives 

Operational objectives 

Indicators 

Sources of information 

Specific 
objectives 

Reinforcing 
trust in data 
sharing 

Making more 
data available 
for reuse 
within the 
common 
European data 
spaces 

Trust  in  data  sharing  increases  as 
clear  rules  are  available  for  data 
exchanged  or  pooled  by  data 
and 
be 
holders 
secure 
processed 
in  compliance  with 
applicable  legislation  as  well  as 
with  the  conditions  they  set  on 
use of such data. 

to 

More  data  are  made  available  for 
reuse on voluntary grounds based 
on  the  existing  legislation  and 
where data holders agree to this. 

Increase  in  the  level  of 
trust 
in  data  sharing 
reported  by  data  users 
and suppliers. 

Representative 
survey  among 
stakeholders  carried  out  by  the 
Support  Centre  for  Data  Sharing 
under  DEP  and  an  evaluation 
study to support the review of the 
instrument  within  3  years  of  its 
adoption.  

of 

Volume 
data 
processed in secure data 
processing 
environments, 
data 
collected  by  authorised 
data 
altruism 
mechanisms  and  data 
shared  among  business 
and/or 
partners 
contributed 
data 
pools. 

to 

and 

Records  of  the  European  Data 
Innovation  Board 
the 
Support  Centre  for  Data  Sharing 
under DEP on reuse of such data 
reported 
dedicated 
the 
national authorities. 

by 

Representative 
survey  among 
stakeholders  carried  out  by  the 
Support  Centre  for  Data  Sharing 
under  DEP  and  an  evaluation 
study to support the review of the 
instrument  4  years  after  its  date 
of application. 

Evaluation  study  to  support  the 
review  of  the  instrument  4  years 
after its date of application.  

Ensuring 
interoperability 
across sectors 
and countries 

and 

Interoperability 
generic 
standards  contribute  to  reduction 
of  transaction  costs  and  allow 
data  to  be  reused  across  sectors 
and Member States. 

Decrease in the share of 
stakeholders  that  have 
encountered  difficulties 
in using data from other 
organisations. 

Source: European Commission (also of the table just below) 

9.2.  Monitoring of the preferred option       

Area 

Operational objectives 

Indicators 

Sources of information 

Mechanisms 
for enhanced 
reuse of certain 
public sector 
data 

data 

Reusability  of  publicly  held  data 
subject  to  the  rights  of  others  is 
ensured by Member States having 
secure 
processing 
environments in place. Findability 
increased  as 
is 
of  such  data 
national  single  entry  points  for 
data  reusers  to  contact  the  public 
sector are available. 

Number  of  data  reuse 
permits  to  process  data 
in 
data 
secure 
processing 
environments 
processing 
carried out. 

issued, 
sessions 

Data  on  reusability  of  such  data 
the 
by 
dedicated 
reported 
national 
the 
to 
authorities 
European Data Innovation Board, 
analysed  by  the  Support  Centre 
for Data Sharing under DEP. 

Certification/ 

Novel types of data intermediaries  Number 

of  Data on the certification/labelling 

55 

 
 
reported  by 

the 
framework 
dedicated  national  authorities  to 
the  European  Data  Innovation 
Board,  analysed  by  the  Support 
Centre  for  Data  Sharing  under 
DEP. 

Data on data altruism reported by 
the dedicated national authorities 
to  the  European  Data  Innovation 
Board  analysed  by  the  Support 
Centre  for  Data  Sharing  under 
DEP.  

Survey  among 
national authorities. 

the  dedicated 

on 

prioritisation 

Records  of  the  Data  Innovation 
Board 
of 
standards  and  publication  of 
technical 
for 
interoperability/peer-to-peer  data 
sharing schemes. 

guidance 

Evaluation  study  to  support  the 
review  of  the  instrument  4  years 
after its application. 

labelling 
framework for 
data 
intermediaries 

to  scale  up  at 

the 
are  able 
sufficient  speed 
to  provide  a 
viable  alternative  to  the  platform 
model. 

organisations awarded a 
trust label. 

Measures 
facilitating data 
altruism  

Companies  and  individuals  are 
able  to  make  their  data  available 
securely  for  the  wider  common 
good through trusted data altruism 
mechanisms.  

of 

Volume 
data 
contributed  through  the 
authorised data altruism 
mechanisms. 

European Data 
Innovation 
Board 

ensures 

The  European  Data  Innovation 
Board 
effective 
coordination  of  the  labelling  and 
the  authorisation  scheme  for  data 
intermediaries  and  data  altruism 
mechanisms; 
of 
standards  for  cross-sector  data 
reuse; and maintains the European 
data-sharing  schema  to  support 
peer-to-peer  data  sharing  without 
an intermediary. 

prioritisation 

of 

Assessment 
the 
support  received  by  the 
national 
dedicated 
authorities. 

of 
Number 
contributions 
the 
Rolling  Plan  for  ICT 
standardisation. 

to 

Number  of  functioning 
data 
peer-to-peer 
sharing 
in 
place. 

schemes 

56 

 
Glossary 

Term or acronym 

Meaning or definition 

Common European Data Space 

An arrangement composed of an IT environment for secure processing of data 
by  an  open  and  unlimited  number  of  organisations,  and  a  set  of  legislative, 
administrative and contractual rules that determine the rights of access to and 
processing of data.  

Data altruism 

The  act  of  granting  access  to  and  sharing  of  data  held  by  individuals  or 
companies, without seeking direct reward, for the common good. 

Data-driven innovation 

The  use  of  data  and  analytics  to  improve  or  create  new  products,  services, 
markets and organisational methods. 

Data intermediary 

Data portability 

Data sharing 

An  entity  (of  either  the  public  or  the  private  sector)  that  facilitates  data 
sharing, access and use by data holders and data users. 

Capacity  to  transfer  data  to  which  an  individual  or  entity  has  a  specific 
relationship  from  one  IT  environment  (or  similar)  to  another,  based  on 
legislative rights (e.g. Article 20 of the GDPR) or contractual agreement.  

An  act  of  the  data  holder,  data  producer,  or  data  intermediary  providing 
access  to  a  data  user  for  the  purpose  of  joint  or  individual  use  of  the  data, 
based  on  voluntary,  commercial  or  non-commercial  agreements,  or 
mandatory rules. It should not be understood as making data available for free 
and to an undefined group of users. 

Data the use of which is conditional 
on respecting the rights of others 

Data that might be subject to data protection legislation, intellectual property 
and main contain trade secrets or other commercially sensitive information. 

Internet of Things (IoT) 

Secondary use or reuse 

A  network  of  physical  devices,  vehicles,  home  appliances  and  other  items 
embedded with connectivity software, which enables these objects to connect 
and exchange data. 

The  use  by  persons  or  legal  entities  of  documents  held  by  public  sector 
bodies,  for  commercial  or  non-commercial  purposes  other  than  the  initial 
purpose within the public task for which the documents were produced. 

57 

 
 
 
ANNEX 1: PROCEDURAL INFORMATION 

1.  LEAD DG, DeCIDE PLANNING/CWP REFERENCES 

The legislative proposal on the governance of common data spaces was prepared under the lead 
of the Directorate-General Communication Networks, Content and Technology. In the DECIDE 
Planning of the European Commission, the process is referred to under item PLAN/2020/7446. 
The  Commission  Work  Programme  for  2020  includes  a  legislative  action  on  data,  under  the 
header “10. A European approach to AI”.  

2.  ORGANISATION AND TIMING 

An  Inter-Service  Steering  Group  (ISSG)  assisted  DG  Communication  Networks,  Content  and 
Technology  in  the  preparation  of  the  Impact  Assessment  and  legal  proposal.  It  included 
Commission services of 18 Directorate-Generals, together with the Commission’s Legal Service 
and Secretariat General. 

Work  for  the  preparation  of  this  initiative  started  with  the  design  of  the  European  Strategy  on 
data,  adopted  in  February  2020,  which  announced  measures  for  a  cross-sectoral  governance 
framework  for  data  access  and  use.  Discussions  were  initiated  during  the  Inter-Service 
Consultation in view of the strategy (January 2020). Subsequently, the ISSG contributed to the 
initiative  preparation  in  March  2020  (discussion  on  the  consultation  strategy  and  the  Inception 
Impact Assessment), and in July 2020 (discussion on the draft Impact Assessment). 

An Inception Impact Assessment was published on 3 July 2020 and was open to feedback from 
all stakeholders on the Better Regulation Portal for a period of 4 weeks.  

The  draft  Impact  Assessment  report  and  all  supporting  documents  were  submitted  to  the 
Regulatory Scrutiny Board (RSB) on 20 July, in view of a hearing on 9 September 2020. After a 
negative opinion, the report got improvements, mainly through the strengthening of the narrative 
and  the  clarification  of  the  problem  definition  and  expected  impacts.  The  second  opinion 
delivered by the Board on 5 October 2020 was positive with reservations. The report was further 
improved on the basis of the comments provided.  

An Inter-Service Consultation took place, with all services that are members of the inter-service 
group on data, and closed on 28 October 2020. 

3.  CONSULTATION OF THE RSB 

The Impact Assessment report was reviewed by the Regulatory Scrutiny Board on 9 September 
2020.  Based  on  the  Board's  recommendations165,  the  Impact  Assessment  has  been  revised  in 
accordance with the following points: 

165 url to be added when created 

58 

 
 
                                                           
Comments of the RSB 

How and where comments have been addressed 

(B) Summary of findings 

(1) The report does not explain the problem 
clearly  enough  and  why  the  EU  should 
promote a new model for data sharing. 

(2)  The  report  does  not  elaborate 
in 
sufficient detail the design and composition 
of the options and how they would work in 
practice. 

(3)  The  scale  of  the  quantified  direct 
impacts  is  not  in  line  with  the  impacts 
presented in the text. 

(4) The analysis is  not  sufficiently  granular 
to  underpin  the  choice  of  the  preferred 
option. 

(C) What to improve 

Chapter  2  has  been  substantially  reworked  to 
better  explain  the  problem,  the  problem  drivers 
and  their  interrelation.  The  key  element  of  trust 
has been made much more prominent as a separate 
problem  driver  in  section  2.2.1,  and  has  been 
disentangled from the more technical issues. 

The explanation on why there is a need for a new 
European  model  for  data  sharing  has  been 
reinforced  by  an  analysis  of  the  role  of  Big  Tech 
platforms  in  this  area  and  of  the  lack  of  trust  in 
data-sharing solutions  they may provide  (sections 
2.1  and  2.3).  The  report  now  also  explains  better 
why  a  model  of  neutral  data  intermediaries  is 
preferable  to  the  current  model  of  Big  Tech 
platforms (section 2.1) in terms of fostering trust. 

The  description  of  the  policy  options  has  been 
further  detailed  (section  5.2).  This  section  now 
also  explains  the  reasoning  behind  the  design  of 
the  options  and,  where  relevant,  the  composition 
of the options is explicit. 

The description of how each option would work in 
practice  for  the  different  intervention  areas  has 
been fine-tuned (section 5.2). This is also reflected 
in Chapter 6. 

An  analysis  of  the  soft  law  option  has  been 
included,  also  covering  each  of  the  different 
intervention areas (section 6.1.2). 

The report now also describes the indirect impact 
that  the  initiative  could  have  as  a  catalyst  of 
seamless  cross-border  cross-sector  data  sharing, 
which would result in wider economic and societal 
benefits (section 6.1). These benefits are expected 
to be substantially higher than the direct impact on 
the data economy. 

Chapters  6  and  7  now  go  into  greater  analytical 
depth  on  all 
thus  better 
underpinning  the  choice  of  the  preferred  mixed 
package in Chapter 8. 

intervention  areas, 

(1)  The  report  should  better  describe  the 
current situation on data sharing in Europe. 
It  should  explain  why  it  does  not  examine 

The  description  of  the  current  situation  on  data 
sharing has been improved by adding information 
and  reorganising  the  ‘Problem  definition’  in 

59 

 
the  current 
data 

the  creation  of  data  markets.  It  should 
analyse drawbacks and risks stemming from 
the  current  role  of  data  intermediaries.  It 
needs  to  provide  more  evidence  on  the 
insufficiency  of  the  existing  arrangements, 
for  example  regarding  findability,  quality 
and  neutrality  of  data.  The  report  should 
tendencies  of 
inform  on 
concentration 
by 
intermediaries.  It  should  expand  on  the 
problems  arising  from  access  to  data  being 
concentrated  outside  the  EU.  The  report 
should  elaborate  on 
that 
emerging  European  data  sharing  initiatives 
internal  market 
their 
are 
dimension.  The  report  should  detail  the 
governance 
data 
problems 
intermediation. 

the  problems 

facing  and 

supply 

of 

of 

the 

(2)  The  report  should  be  clear  on  the 
objective  of 
intervention.  It  could 
explain  that  the  initiative  might  help  to 
mitigate  the  Covid-19  and  climate  crises. 
However, the resolution of these crises does 
not form an integral part of the intervention 
logic and should therefore not be the general 
objective.  In  addition,  the  report  should 
make evident that the initiative is not about 
‘free  data  for  all’.  The  objectives  should 
also  better  consider  the 
importance  of 
access to data for competitiveness. 

Chapter 2, in particular the problem drivers. 

Section  2.1  of  the  report  now  describes  the  risks 
related  to  the  current  role  of  data  intermediaries 
under  a  dedicated  sub-heading  entitled  ‘The  role 
of  platforms  in  the  data  economy’.  It  signals  the 
risk  of  generalising  the  business  model  of  Big 
Tech  platforms 
that 
concentrate  large  volumes  of  data  to  the  area  of 
data sharing (sections 2.1 and 2.3). 

from  outside  Europe 

This issue is interlinked with the low level of trust 
in  data  sharing,  which  now  appears  as  a  main 
problem  driver  in  section  2.1,  and  which  is 
disentangled  from 
issues 
the  more 
(interoperability,  findability).  The  same  section 
also explains in more detail the importance of the 
neutrality  of  data  intermediaries  as  a  means  to 
increase trust. 

technical 

The  section  dedicated  to  the  necessity  for  EU 
action  (section  3.2)  better  explains  how,  in  order 
to  roll  out  EU-wide  products  and  services  based 
on data, businesses should be able to benefit from 
the size of the internal market. 

In  section  4.1,  the  general  objective  of  the 
initiative  has  been  reformulated,  linking  a  higher 
level of data sharing (which is not a goal in itself) 
to  realising  the  enormous  potential  of  the  use  of 
data for the EU’s economy and society. 

The report now explicitly states upfront under the 
subheading  ‘The  importance  of  data  for  the 
economy’ (section 1.1.) that data sharing does not 
imply that all data will be available for free reuse 
by all. This is further exemplified in the report, for 
example  in  the  box  on  common  European  data 
spaces  (section  1.2)  and  by  highlighting  the 
incentives for companies and individuals to  share 
data in a separate sub-heading (section 2.1). 

The report emphasises the essential role of access 
to  and  use  of  data  for  competitiveness,  including 
innovation  in  areas  such  as  artificial  intelligence, 
more  efficiency  across  industry,  and  data  as  a 
critical  resource  for  SMEs  and  start-ups  (sections 
1.1 and 2.1). 

(3) The report should explain the interaction 
between 
in  common 
investments 
European data spaces by the Digital Europe 
programme  and  the  Connecting  Europe 

the 

The report now describes in more detail in section 
5.2  how  the  Commission  will  invest  through  the 
Digital  Europe  Programme  and  the  Connecting 
Europe  Facility2  in  the  development  of  data 

60 

 
Facility, and this initiative. It should include 
their effects in the baseline and the analysis 
of options. 

(4)  The  report  should  better  explain  the 
composition  and  completeness  of 
the 
options. It should justify why it discards all 
soft  regulatory  measures  upfront.  It  should 
elaborate  the  reasons  for  the  combinations 
of  measures  under  the  ‘low’  and  ‘high’ 
intensity  options,  and  explore  further  if  the 
set  of  options  is  complete.  The  report  also 
needs  to  explain  clearly  how  each  option 
would  work  in  practice.  In  particular,  it 
should  describe  in  more  detail  the  role  and 
functioning of the different supervising and 
coordinating 
under 
consideration. It should also clarify to what 
extent the initiative would rely on altruism, 
and  whether  this  poses  concerns  regarding 
supply  and  scarcity  of  data.  It  should 
explain  how  control  interests  of  primary 
data suppliers would be protected. It should 
consider  the  possible  role  of  the  public 
sector  as  a  data  intermediary  with  the 
digitalisation of public administrations. 

bodies 

that 

are 

processing infrastructures, tools, architectures and 
mechanisms for data sharing. It also describes the 
interplay  of  these  investments  with  the  current 
initiative:  the  impacts  of  spending  on  common 
the 
European  data  spaces  will  depend  on 
efficiency  of  the  measures  under  the  current 
initiative. 

It has been clarified that none of the policy options 
were  discarded  upfront.  An  analysis  of  the  soft 
law  option  has  been  included,  also  covering  each 
of the different intervention areas (section 6.1). As 
part  of  the  soft  law/coordination  measures,  a 
system of industry-driven certification/labelling of 
data  intermediaries  has  been  considered  (section 
6.1.2). 

Section 5.2 of the report (description of the policy 
options)  has  been  reinforced  with  additional 
explanations  on  all  policy  options.  The  low  and 
high  intensity  options  for  each  measure  are  now 
described in more detail, as well as the reasoning 
behind the design of various combinations. 

The  report  also  explains  more  clearly  in  section 
5.2  how  the  different  options  would  work  in 
practice,  including  the  role  of  the  supporting  and 
supervising bodies at the national level, as well as 
the European Data Innovation Board (status, role, 
composition,  who 
the 
secretariat). 

responsible 

for 

is 

altruism 

addresses 

Data 
data 
specifically 
availability  for  the  common  good.  The  need  to 
protect  the  interests  of  the  data  suppliers  in  the 
context  of  data  altruism  is  now  more  explicit  in 
sections 5.2 and 6.2, and is a key element for the 
retained  option  for  this  intervention  area.  The 
notion that organisations engaging in data altruism 
should ensure that the data is  used in  compliance 
with  the  stated  preferences  of  the  company  or 
individual giving the data has been added (section 
5.2.3.C). 

The  roles  of  the  public  and  private  sectors  in 
relation  to  data  intermediary  functions  have  been 
further calibrated (section 5.2). 

(5)  The  report  should  explain  why  the 
calculated  economic benefits  of the options 
are  marginal  compared  with  the  expected 
evolution of the data sector. If necessary, it 

the  methodology 

Section  6.1  of  the  report  now  explains  in  further 
for  calculating 
detail 
the 
the  policy  options, 
economic 
concentrating  on  direct  impacts,  and  to  a  limited 

impacts  of 

61 

 
could  rely  more  on  qualitative  arguments. 
The  analysis  should  look  into  effects  on 
SMEs  and  costs  for  Member  States.  The 
report  should  better  justify  the  benefits  of 
creating the European Innovation Board. 

extent on the indirect impacts. 

At  the  same  time,  section  6.1  (echoed  in  Chapter 
8)  now  indicates  why  the  overall  benefits  of  the 
initiative  are  expected  to  be  significantly  higher 
than the direct impact: the measures would act as a 
catalyst  to  increase  data  sharing  across  the  EU, 
which  would  benefit  not  only  the  data  economy, 
but the EU economy and society as a whole.  

Chapter  6  of  the  report  now  better  explains  the 
expected  consequences  of  each  policy  option  on 
the  economy,  as  well  as  on  society  and  the 
environment. The section on the impacts on SMEs 
(section 6.3) has been further enriched. The notion 
that  the  initiative  is  likely  to  benefit  companies 
from  across  the  EU  and  not  only  from  some 
Member  States  has  been  added  (section  6.1).  A 
reference to national initiatives has been added in 
relation  to  the  calculation  of  the  costs  (and 
benefits) for Member States (section 6.1.3). 

The  potential  benefits  of  a  European  Data 
terms  of 
Innovation  Board, 
standardisation,  are  further  elaborated  in  section 
6.2 of the report. 

in  particular 

in 

(6)  The  report  therefore,  needs  to  present  a 
more granular analysis of the impacts of the 
different  intervention  areas  to  better  justify 
the choice of the preferred option. 

Chapter  6  of  the  report  now  investigates  in  more 
detail  the  economic,  social  and  environmental 
impacts  of  each  policy  option,  including  soft  law 
measures. In addition, the multi-criteria analysis in 
Chapter  7  has  been  enriched,  thus  providing  a 
stronger  foundation  for  the  chosen  package  in 
Chapter 8. 

The Regulatory Scrutiny Board delivered a second opinion that was positive, provided that the 
following recommendations were taken into account in the report.  

Comments of the RSB 

How and where comments have been addressed 

(B) Summary of findings and (C) What to improve 

Options 

(B1)  Options  are  not  sufficiently  clear  on 
how  they  would  work  in  practice.  The 
justification  for  the  composition  of  the 
options is not always convincing.  

(C1)  The  report  should  further  clarify  the 
content  of  the  options.  It  should  explain 
how  the  self-regulation  option  would  differ 
from current practices (which are part of the 

Chapter  5  of  the  report  (description  of  policy 
options) now specifies, for each intervention area, 
how  the  policy  options  2  and  3  would  work  in 
practice. Examples are provided to clarify what is 
expected and by whom. 

All of the comments mentioned in (C1) have been 
(description  of 
section  5.2.3 
addressed 
regulatory intervention with low or high intensity). 

in 

62 

 
 
 
baseline). For the options on reuse of public 
data,  it  should  justify  why  other  possible 
dimensions  of  the  options  were  considered, 
but  not  further  analysed.  It  should  better 
explain how the high intensity option would 
work 
the 
in  practice.  […]  Regarding 
European Data Innovation Board, the report 
foreseen 
specify 
could 
functioning  under  the  options,  including  its 
role  and  powers  vis-à-vis  Member  State 
authorities. 

further 

its 

Impacts 

(B2)  The  analysis  lacks  depth  regarding 
impacts  on  SMEs,  Member  States  and  the 
internal market. 

(C2)  The  report  should  deepen  the  analysis 
of  SME  specific  impacts  and  costs  for 
the 
Member  States.  It  should  analyse 
possible  impact  on  the  internal  market  of 
different  implementation  approaches  across 
Member States. It should explain better why 
the  expected  benefits 
impact 
assessment  are  much  smaller  than  in  the 
referenced research studies.  

the 

in 

(C4)  The  report  needs  to  present  a  more 
granular  overview  of  the  impacts  of  the 
different intervention areas in tabular form. 

Funding Programmes 

(C3)  The  report  should  better  integrate  the 
expected  effects  of  the  Digital  Europe 
programme  and  the  Connecting  Europe 
Facility in the analysis of options. 

It  also  better  explains  how  the  high  intensity 
option  would  work  in  practice.  The  role  of  the 
European  Data 
Innovation  Board  vis-à-vis 
national  authorities  has  been  clarified  under  each 
policy option.  

Chapter  6  of  the  report  provides  more  detailed 
information  on  the  expected  impacts  on  SMEs  in 
the  EU  (impact  of  the  policy  options),  as  well  as 
on the expected costs for Member States.  

The  explanation  on  the  difference  between  the 
expected  benefits  in  the  Impact  Assessment  and 
the  referenced  studies  is  strengthened  in  section 
6.1. 

In  the  same  section,  the  impact  on  the  internal 
market of diverging approaches between Member 
States is addressed. 

To address comment (C4), eight tables have been 
inserted in Chapter 6. These tables summarise the 
economic  impact  (costs  and  benefits)  of  the 
different policy options for each intervention area. 

Chapter  5  describes  in  more  detail  how  the 
different  options,  including  the  baseline  scenario, 
would  benefit  from  the  technical  infrastructures 
and  tools  developed  with  the  support  of  the  DEP 
and CEF programmes. This concerns in particular 
actions  to  ensure  interoperability  and  the  use  of 
common standards across Member States. 

The description of the expected economic impacts 
(section  6.1)  now  includes  information  on  how 
investments  in  the  creation  of  a  European  data 
sharing  and  processing  infrastructure  would  help 
lower 
technical 
related 
implementation  of  the  measures  proposed  in  this 
initiative. 

the  costs 

the 

to 

Options on data altruism 

(B3) The report does not convincingly argue 
the  choice  of  the  preferred  option  for  data 

The  reasoning  for  selecting  the  preferred  option 
in 
for  data  altruism  has  been  strengthened 

63 

 
 
 
 
Chapters  6  and  8.  In  particular,  section  6.1.4  (on 
the  high  intensity  option)  highlights  the  benefits 
for  citizens,  companies  and  data  users  of  this 
option. 

Section 5.2.3 of the responds to comment (C1) on 
the  justification  of  the  low  and  high  intensity 
options. 

Chapter  9  of  the  report  now  describes  in  more 
depth  how  the  impact  of  the  initiative  will  be 
monitored  and  evaluated  on  a  regular  basis.  It 
explains that the European Data Innovation Board 
will  collect  experiences  from  the  Member  States 
and assess the effectiveness of their practices. The 
Support Centre for Data Sharing, which is planned 
to  be  established  under  the  DEP,  will  ensure  a 
similar role with stakeholders. 

altruism. 

(C1)  For  the  options  on  data  altruism,  the 
report  should  better  justify  why  the  low 
intensity  option  foresees  voluntary  private 
certification  and  the  high  intensity  option 
compulsory  public  authorisation.  It  should 
consider 
including  a  voluntary  public 
certification option as an alternative. 

(C4)  It  should  better  justify  its  choice  for 
the  high  intensity  option  for  data  altruism, 
especially as it does not analyse a voluntary 
public certification option (see above). 

Monitoring and evaluation 

(C5)  The  report  should  examine  in  more 
depth  how  it  intends  to  organise  future 
monitoring  and  evaluation  on  an  ongoing 
basis.  Given  that  it  is  experimenting  with 
new, untried approaches, waiting five  years 
for  their  evaluation  seems  a  rather  static 
approach.  It  should  clarify  how  increased 
trust  in  data  sharing  will  be  measured  and 
monitored.  It  should  describe  how  the 
effectiveness  of  these  new  approaches  will 
be assessed in a timely manner. 

4.  EVIDENCE, SOURCES AND QUALITY 

Evidence-collection process  

Extensive  work  was  carried  out  during  the  previous  Commission’s  mandate  to  identify  the 
problems  that  are  currently  preventing  Europe  from  realising  the  full  economic  and  societal 
potential of data-driven innovation, in  particular  by  ensuring  greater access  to  and use of data. 
This work resulted in earlier Commission policy documents166, the consultation of stakeholders 
and  extensive  exploratory  study  work167.  The  analyses  have  identified  technical  barriers 
(interoperability, safety and security requirements), legal obstacles (uncertainty about access and 

166 COM/2017/9; COM/2018/232 . 
167 Everis (2018). Study on data sharing between companies in Europe, Study prepared for DG CNECT.  
European  Commission  (2018c).  Study  on  emerging  issues  of  data  ownership,  interoperability,  (re-)usability  and 
access to data, and liability, study prepared by Deloitte.  
European Commission (2017). Synopsis report consultation on the ‘building a European data economy’ initiative. 
European Commission (2019a). SME panel consultation B2B data sharing - Final Report.   
European Commission (2018d). Study to support the review of Directive 2003/98/EC on the re-use of public sector 
information, study prepared by Deloitte.   

64 

 
 
 
 
 
                                                           
 
use rights in relation with the data, the costs of compliance with existing legal obligations as well 
as  costs  of  licensing),  organisational  challenges,  the  difficulty  to  control  downstream  use,  the 
fear of misappropriation and the limited availability of skilled labour. 

Through  an  Impact  Assessment  support  study  (SMART  2019/0024),  additional  evidence  was 
gathered in  terms  of the specific costs and benefits  of the concrete  elements  of the instrument. 
These costs, benefits and burden reduction/simplification potential were identified and quantified 
for each of the measures proposed in the initiative (secondary use of sensitive data held by the 
public sector, data altruism, governance aspects of data sharing, and certification options for data 
intermediaries). The contractors analysed each of these elements, combining desk research with 
surveys, interviews and focus groups with representatives of businesses. 

The findings of the EC-funded European Data Market study measuring the size and trends of the 
EU data economy (SMART 2016/0063) also fed into the preparation of the initiative. Based on 
alternative development paths driven by different macroeconomic and framework conditions, the 
study monitors several indicators. This included the number of data workers, data companies and 
their  revenues,  data  user  companies  and  their  spending  for  data  technologies,  the  market  of 
digital products and services, the data economy and its impacts on the European economy, and 
medium-term forecast scenarios of all the indicators, based on alternative market trajectories.  

Stakeholders' consultation process 

Recent  stakeholder  consultation  processes  provided  input:  the  2017  public  consultation  on 
building a European data economy, the 2018 public consultation on the revision of the Directive 
on the reuse of public sector information, and the 2018 SME panel consultation on the B2B data 
sharing principles and guidance.  

In addition, a series of 10 workshops on common European data spaces took place in 2019 and 
an  additional  one  in  May  2020.  The  stakeholders  generally  supported  the  creation  of  common 
European  data  spaces,  and  considered  that  they  should  provide  for  the  clarification  and 
harmonisation  of  data  governance  models  and  practices,  as  well  as  for  the  necessary 
infrastructures for the sharing of good quality and interoperable data. 

Together  with  the  adoption  of  the  European  Strategy  on  data,  an  online  public  consultation, 
targeting  all  stakeholders,  was  launched  on  19  February  2020.  It  ran  until  31  May  2020.  The 
consultation explicitly indicated it was launched in view of preparing the current initiative, and 
addressed the items covered in the initiative with relevant sections and questions. The feedback 
on  the  Inception  Impact  Assessment  also  targeted  all  types  of  stakeholders,  as  did  the 
Eurobarometer on the impact of digitisation.  

65 

 
 
 
ANNEX 2: STAKEHOLDER CONSULTATION  

INTRODUCTION 

The  stakeholders’  consultation  process  aimed  at  understanding  how  stakeholders  consider  that 
data governance mechanisms and structures can best maximise the social and economic benefits 
of data usage in the EU. This provided valuable input for the preparation of the proposal  for a 
Regulation on the governance of common European data spaces.  

The  proposal  also  builds  on  past  consultation  actions,  such  as  the  2017  public  consultation  on 
building a European data economy, the 2018 public consultation on the revision of the Directive 
on the reuse of public sector information, and the 2018 SME panel consultation on the B2B data 
sharing principles and guidance. 

The  consultation  actions  conducted  between  July  2019  and  June  2020  covered  general  and 
horizontal  issues,  such  as  the  design  and  main  features  of  the  common  European  data  spaces, 
relevant  data  governance  mechanisms,  as  well  as  more  specific  horizontal  questions 
(standardisation,  secondary  use  of  data,  data  altruism  and  data  intermediaries).  Some 
consultation  actions  covered  the  specificities  of  sectors,  and  the  conditions  to  facilitate  such 
spaces  in  domains  of  public  interest.  Therefore,  the  consultation  process  targeted  all  types  of 
stakeholders (Member States and public authorities, academic and research institutions, industry 
stakeholders/businesses  including  SMEs,  as  well  as  individuals)  across  the  EU,  and  across 
sectors. Different types of stakeholders are interested in the initiative for different reasons: 

  Member  States  are  interested  in  the  initiative  from  a  policy  perspective,  given  the 
potential  of  data  for  the  economy  and  society.  Their  public  authorities  are  directly 
concerned by the proposed measures on unlocking and reusing more public sector data. 
EU  level  coordination  would  facilitate  the  work  of  public  sector  bodies  in  streamlining 
how data can be used and who can access it. 

  Academic  and  research  institutions  as  well  as  researchers  will  directly  benefit  from  the 
measures on secondary use of data and data altruism, which will considerably lower their 
compliance costs related to using data. 

 

 

finance/banking,  energy, 

Industry  stakeholders/  businesses,  including  SMEs,  in  the  different  sectors  (e.g. 
transport,  sustainability/environment,  public 
agriculture, 
services, smart manufacturing and data market places) will in particular benefit from the 
opportunities  provided  by  easier  cross-sectoral  data  use.  They  will  also  be  providers  of 
data and as such need to be aware of the rules and limitations on data sharing. 

Individuals  will be empowered to allow use of data related to them for the public good 
(e.g. people with rare or chronic diseases allowing for use of data in order to help cure or 
improve  treatment  of  those  diseases)  (‘data  altruism’)  and  more  in  general  by  the 
opportunities to get more control over their data, e.g. through personal data spaces.  

The  consultation  actions  foreseen  in  the  Consultation  Strategy,  discussed  in  an  inter-service 
group in March 2020, were carried out. However, due to the COVID-19 outbreak, some actions 
were modified (i.e. workshops turned into webinars). 

66 

 
Online consultation 

A public online consultation was published on the day of adoption of the European strategy for 
data168 (19 February 2020) and closed on 31 May 2020. The consultation explicitly indicated it 
was launched in view of preparing the current initiative, and addressed the items covered in the 
initiative with relevant sections and questions. It targeted all types of stakeholders. In addition to 
issues related to the governance of common European data spaces, it gathered input on the EU-
wide  list  of  high-value  datasets  that  the  Commission  will  draw  up  under  the  Open  Data 
Directive,  and  explored  issues  related  to  cloud  computing.  Furthermore,  it  contained  some 
generic questions on the European data strategy 

In total, 806 contributions were received, of which 219 were on behalf of a company, 119 from a 
business association, 201 from EU citizens, 98 on behalf of academic / research institutions, and 
57  from  public  authorities.  Consumers’  voices  were  represented  by  7  respondents,  and  54 
respondents  were  non-governmental  organisations  (including  2  environmental  organisations). 
Amongst the 219 companies / business organisations, 43.4% were SMEs. Overall, 92.2% of the 
replies came from the EU-27. Very few respondents indicated whether their organisation had a 
local, regional, national or international scope. 

230 position papers were submitted, either attached to questionnaire answers (210) or as stand-
alone contributions (20). The papers provided different views on the topics covered by the online 
questionnaire, in particular in relation to the governance of common data spaces. They provided 
opinions  on  the  key  principles  for  those  spaces,  and  expressed  a  high  level  of  support  for  the 
prioritisation of standards as well as the data altruism concept. They also indicated the need for 
safeguards in developing measures related to data intermediaries. 

Inception Impact Assessment 

As foreseen by the Better Regulation guidelines, an Inception Impact Assessment was published 
on the Better Regulation portal on 3 July 2020, and was open for feedback for 4 weeks. It also 
targeted  all  types  of  stakeholders.  The  Commission  received  107  contributions  on  the  Better 
Regulation  Portal169,  mainly  from  businesses  (35%)  and  associations  representing  businesses 
(29%).  Other  types  of  stakeholders  participated,  although  in  a  smaller  proportion:  non-
governmental organisations (11%), academic/research institutions (6%), consumer organisations 
(3%), EU citizens (2%), trade unions (2%) and others (9%). Some of these stakeholders had also 
contributed to the public online consultation.  

Expectedly,  the  contributions  reflected  the  replies  to  the  online  questionnaire,  as  well  as  the 
papers.  Most  of  the  contributions  expressed  support  to  the  initiative  and  contained  general 
comments, underlying the importance of fair, transparent and non-discriminatory access to data, 
of voluntary data sharing (from private entities but also from individuals) and of standards and 
interoperability.  The  feedback  dealt  with  all  aspects  and  measures  foreseen  in  the  initiative. 

168 COM/2020/66 final. 
169 https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/12491-Legislative-framework-for-the-
governance-of-common-European-data-spaces  

67 

 
                                                           
Stakeholders highlighted some concerns and strong needs they have as regards access to and re-
usability of data. They also indicated the need for guidance to accompany any legislation.  

Other consultation actions 

-  Series of workshops on “common European data spaces” 

In  order  to  explore  with  the  relevant  experts  the  framework  conditions  for  creating  common 
European data spaces in the identified sectors, a series of 10 workshops was organised between 
July and November 2019.  

Gathering in total more than 300 stakeholders, mainly from the private and the public sectors, the 
workshops  covered  different  sectors  (agriculture,  health,  finance/banking,  energy,  transport, 
sustainability/environment,  public services, smart  manufacturing)  as well as more cross-cutting 
aspects  (data  ethics,  data  market  places).  The  different  DGs  concerned  were  involved  in  these 
workshops. A report is available online. 

-  The latest Eurobarometer on the impact of digitisation 

This  general  survey  on  the  daily  lives  of  Europeans  includes  questions  on  people’s  control  on 
and  sharing  of  personal  information.  The  report,  published  on  5  March  2020,  provides 
information on the willingness of European citizens to share their personal information and under 
which conditions. 

-  Workshop  on  labels  for  or  certification  of  providers  of  technical  solutions  for  data 

exchange  

Around 100 participants from businesses (including SMEs), European institutions and academia 
attended  this  webinar,  on  12  May  2020.  Its  aim  was  to  examine  whether  a  labelling  or 
certification scheme could boost the business uptake of data intermediaries by enhancing trust in 
the data ecosystem. A report is available online. 

-  BDVA Survey  

The  survey  (May-July  2020)  designed  by  the  Big  Data  Value  Association  (BDVA)  aimed  to 
capture  the  current  state  of  data-sharing  practices  by  businesses,  research  institutions, 
governmental  or  non-governmental  organisations.  The  objective  was  to  understand  the 
predominance  of  data  sharing  and  exchange  activities,  the  value  that  such  practices  bring  to 
organisations  and  the  difficulties  faced  by  stakeholders,  as  well  as  to  gather  insights  into  what 
needs to be done to increase participation in data sharing, in view of the ever increasing need for 
greater access to data.  

-  The Opinion of the European Data Supervisor on the European strategy for data  

On  16  June  2020,  the  European  Data  Protection  Supervisor  adopted  Opinion  3/2020  on  the 
European strategy for data. The approach of the EDPS towards the strategy in general is positive, 
considering that the implementation of the strategy will be an opportunity to set an example for 
an alternative data economy model. 

-  Position of the Member States  

68 

 
The  European  Strategy  for  Data  was  welcomed  by  the  Member  States  in  the  Council 
Conclusions of 9 June 2020, specifically calling the European Commission “to present concrete 
proposals  on  data  governance  and  to  encourage  the  development  of  common  European  data 
spaces for strategic sectors of the industry and domains of public interest”170. On 9 July 2020, 
the Digital Single Market Strategic Group, composed of Member States representatives, was also 
presented  initial  ideas  for  the  legislative  framework  on  the  common  European  data  spaces  and 
expressed a strong support to the improvement of data governance at EU level. 

RESULTS OF THE CONSULTATION PROCESS 

  On the challenges around data sharing 

The  2017  consultation  process  on  ‘Building  a  European  Data  Economy’  investigated  the 
magnitude  of  data-sharing  limitations  and  the  relevance  of  measures  envisaged  by  the 
Commission  to  foster  a  thriving  EU  data  economy  (synopsis  report  available  online).  Through 
the online questionnaire, meetings and workshops, virtually all stakeholders confirmed that more 
data should be made available for reuse in B2B contexts. Most stakeholders also shared the view 
that the European Commission should be cautious when taking any measures to make more data 
available for reuse, stressing that the main issue is how to maximise and organise access to and 
reuse of data, rather than questions about data access rights.   

On  the  basis  of  the  business-to-business  data-sharing  principles  and  guidance  that  the 
Commission  issued  in  the  April  2018  data  package,  further  consultation  actions,  including  an 
online  consultation  (October  2018  to  January  2019),  provided  the  views  of  979  SMEs  (report 
available online). Some 39% of responding SMEs encountered difficulties in accessing data from 
other companies.  

The 2020 online consultation confirmed this statement, with almost 80% of the 512 respondents 
to  the  question  indicating  that  they  have  encountered  difficulties  in  using  data  from  other 
companies.  These  difficulties  relate  to  technical  aspects  (data  interoperability  and  transfer 
mechanisms), denied data access, and prohibitive prices or other conditions considered unfair or 
prohibitive.  Some  companies  also  fear  that  they  might  lose  their  competitive  advantage  within 
their market or in prospective markets if they engage in data sharing. In this online consultation, 
some companies highlighted the reluctance of other companies to share data due to this fear, as 
well  as  more  technical  problems  such  as  data  quality  and  granularity.  At  the  same  time,  the 
position papers received showed that many stakeholders consider that data sharing should remain 
voluntary.  

The  2019  workshops  on  the  common  European  data  spaces  revealed  that  companies  often 
struggle  to  find  or  obtain  the  data  that  they  need,  including  from  different  markets.  The 
findability issue was also raised during the workshop on labels for/certification of providers of 
technical solutions for data exchanges in May 2020.  

170 Council of the European Union Conclusions (9 June 2020). 

69 

 
 
                                                           
  On the need for common European data spaces and data governance mechanisms 

Throughout  the  various  2019  and  2020  consultation  actions,  stakeholders  strongly  supported 
common  European  data  spaces  as  a  concept.  During  the  2019  workshops,  they  stated  that 
common European data spaces should help to establish data governance models leading to more 
standardised  approaches  for  data  sharing,  and  should  provide  the  necessary  infrastructures, 
including  pan-European  sustainable  cloud  federations,  for  the  sharing  of  good  quality  and 
interoperable data. 

Stakeholders considered that such data spaces could become the key instance for clarifying data 
control rights  and rules  on data access  and use. This  particularly relates to  areas where control 
rights  are  an  important  concern  because  of  sensitive  data  at  stake  (e.g.  health),  or  because  of 
existing competition between the different actors within these sectors (e.g. agriculture, transport, 
energy). In the workshops and in the position papers several stakeholders expressed the concern 
that Big Tech platforms could move into their sectors, and would get an undue advantage based 
on the use of data.  

The results of the online consultation, conducted from February to May 2020, confirmed those 
trends.  From  the  772  respondents  to  the  question,  90%  considered  that  data  governance 
mechanisms are needed to capture the enormous potential of data, in particular for cross-sector 
data  use,  and  86%  supported  the  development  of  common  European  data  spaces  in  strategic 
industrial sectors and domains of public interest. In the papers received, stakeholders described 
in more detail the key principles that they consider should underpin the data spaces: open to all/ 
non-discriminatory, voluntary, preserving ‘sovereignty’ of the data provider, agile, decentralised, 
based  on  trust  and  transparency,  ethical  framework,  human-centric,  industry-led  and  inclusive, 
accountable. They indicated that any legislation should be accompanied by clear guidance, and 
that an EU level coordination body should be established to maximise the benefits of data. 

From the 554 respondents to the question, 91% of stakeholders considered standardisation to be 
necessary, in view of improving interoperability and ultimately data reuse across sectors. Only a 
very  small  share  (1,6%)  of  all  respondents  considered  that  EU  or  national  government  bodies 
should  take  no  role  in  standardisation.  Public  funding  was  considered  necessary  to  open 
standards and for testing, and EU and national bodies are expected to take an active role in the 
prioritisation and coordination of standardisation needs, as well as the creation and updating of 
standards. 

The  papers  received  provided  additional  input:  whereas  many  stakeholders  consider  that 
interoperability  (both  legal  and  technical)  is  a  key  challenge  for  EU  businesses,  there  are 
concerns  that  the  implementation  costs  will  unfairly  impact  SMEs  and  may  ultimately  fall  on 
consumers. They explained that standards should be market-led and global, building on existing 
standards (e.g.  ISO), and that the role of the EU is to coordinate the prioritisation of standards 
and ensure that they are not imposed by big market players. 

The  2019  workshops  also  revealed  that  interoperability  and  data  quality  issues  could  be 
addressed  through  the  common  data  spaces.  For  instance,  in  the  workshop  on  labels  for  or 
certification  of  providers  of  technical  solutions  for  data  exchange,  it  was  highlighted  that  an 

70 

 
obligation for interoperability with other providers of data-sharing services would be difficult to 
certify  in  the  absence  of  standards  for  interoperability.  Participants  in  various  workshops  also 
stated that there is a need for a structured prioritisation of standards on data, especially in view of 
increasing the opportunities for cross-sectoral reuse. 

  On the secondary use of public sector data 

On enhancing the secondary use of public sector data that is subject to rights of others (personal 
data, trade secrets and other commercially confidential data), the Commission has interacted with 
national organisations that have set up technical  mechanisms allowing controlled processing of 
such  data,  for  instance  in  the  fields  of  statistics  (Germany),  mobility  (Finland)  and  health 
(France). This provided a better understanding of how privacy-preserving technologies can help 
to  allow  the  extraction  of  certain  insights  from  the  data  under  controlled  conditions  while 
preserving information privacy.  

In the online consultation question about making a broader range of ‘sensitive’ public sector data 
available for R&I purposes for the public interest, more than three quarters of respondents to the 
question  considered  that  public  authorities  should  do  more,  especially  mentioning  the 
anonymisation  of  specific  data  for  concrete  use-cases,  and  the  clarification  of  the  legal  rules. 
Unsurprisingly,  the  vast  majority  (87%)  of  respondents  from  academic  and  research 
organisations  agreed  on  the  need  to  facilitate  the  reuse  of  sensitive  data  for  research  and 
innovation  purposes.  In  open  questions,  stakeholders  also  suggested  that  public  authorities 
should support the adoption of private portals for the reuse of data, enabling third party trust and 
quality  services.  Sensitive  data  needs  robust  governance  and  can  benefit  from  third  parties  as 
gatekeepers.  In  particular  regarding  health  data,  research  ethics  committees  or  ethics  review 
boards should be involved. 

Papers received  confirmed that stakeholders consider that public authorities should do more to 
make  data  that  is  subject  to  the  rights  of  others  available  for  reuse  for  R&I  purposes,  but  this 
should  be  strictly  regulated.  Decisions  to  allow  reuse  should  be  based  on  the  public  interest 
(which needs to be defined) and use-case specific risk assessment. Anonymization is important, 
but it could prevent the data from being reusable. Transparency is essential (how the data will be 
shared, processed, etc.). Data made available should follow a minimization principle (i.e. defined 
temporal scope and sensitive data should only be made available when needed). 

The  European  Data  Protection  Supervisor  underlined  in  his  Opinion  that  the  contours  of 
scientific  research  versus  commercial  innovation  are  not  clear-cut.  Therefore,  exceptions  for 
research on personal data cannot lead to a broad exemption of the scientific sector from GDPR 
obligations. 

  On data altruism 

In a workshop organised on 24 May 2019,  experts  discussed issues related to  data donation in 
healthcare.  A  number  of  experts  questioned  the  use  of  the  term  ‘data  donation’,  as  it  could 
suggest an irreversible process and could presuppose ‘data ownership’ (as a result, this initiative 
now uses the term ‘data altruism’). However, according to the GDPR, consent by data subjects to 
processing  of  personal  data  pertaining  to  them  can  be  withdrawn  at  any  time,  including  when 

71 

 
such processing is based on altruistic motivations of the data subject. Experts also suggested that 
better  support  structures  and  services  are  needed  for  data  altruism  to  become  widely  accepted 
and used, including interoperability and standards. More success stories and good practices (e.g. 
models  and  incentives  for  data  altruism)  are  also  needed  to  improve  understanding  of  the 
governance and support requirements.  

In the online consultation, a large proportion of respondents considered that law and technology 
should  enable  citizens  to  make  available  their  data  for  the  public  interest,  without  any  direct 
reward.  Citizens,  particularly,  would  be  willing  to  make  such  data  available,  especially  for 
health-related  research  and  for  aspects  relating  to  the  locality  they  live  in  (e.g.  mobility, 
environment). More than 60% of all respondents considered that there are no sufficient tools and 
mechanisms  to  ‘donate’  their  data.  On  the  mechanisms  to  support  ‘data  altruism’,  respondents 
favoured a European approach to obtaining consent, in compliance with the GDPR as well as the 
establishment  of  technical  infrastructures  such  as  personal  data  intermediaries  (see  below)  and 
information campaigns. In open questions, stakeholders suggested more supporting mechanisms 
(model contractual clauses or data sharing agreements; mechanisms (e.g. blockchain) to  ensure 
data  chain  of  custody  in  order  to  capture  where  and  how  the  data  was  used;  information  and 
transparency ensured by the public sector with regard to the protection of "contributed" data, e.g. 
the use of technical safeguards such as pseudonymisation). 

The papers received confirmed the high level of support for putting individuals in control of their 
own data: solutions are needed to reconcile privacy rights with the use of data for the  common 
good. Trust is key, and a clear legal basis defining how individuals can make data available for 
altruistic purposes  in  full  compliance with  the GDPR would be welcome. Transparency is  also 
critical: the individual should know what their data is being used for. Individuals should not be 
‘nudged’  into  sharing  more  data  than  they  normally  would  by  labelling  such  sharing  ‘data 
altruism’.  Individuals  should  remain  free  not  to  ‘donate’.  The  term  ‘altruism’  was  sometimes 
considered  misleading.  Lack  of  representativeness  could  be  an  issue.  Finally,  several 
stakeholders considered that personal data should not be monetised. 

In its Opinion, the EDPS made the comment that the GDPR already provides principles and rules 
on consent, hence giving the possibility for the ‘data altruism’ concept. Therefore, the initiative 
should clearly define the scope, including various purposes. 

  On data intermediaries 

In the online consultation, almost  60% of respondents  to  this section considered that emerging 
novel intermediaries, such as ‘data marketplaces’, are useful enablers to the data economy, while 
almost 22% don’t know or remain neutral to the question. In open questions and papers received, 
stakeholders  confirmed  such  intermediaries  play  an  important  role  in  providing  fluidity  of  the 
data economy, but  said  a strict accountability framework is  needed. A data intermediary  could 
verify the connected datasets of a particular individual, which would increase the reliability and 
therefore relevance of the data for the recipient.  However, an intermediary also adds additional 
contracts and costs. 

72 

 
Some stakeholders indicated that a uniform and binding definition of data trustee systems should 
be  created  and  corresponding  specifications  for  certification  processes  should  be  developed. 
There  is  also  the  view  that  the  EU  should  support  the  development  of  data  platforms  and 
marketplaces allowing private and public sectors alike to sell, trade and access quality datasets. 

A workshop organised on “labels for or certification of providers of technical solutions for data 
exchange”  in  May  2020  showed  strong  interest  in  the  topic  with  almost  100  participants.  
Participants  were  mostly  companies  or  initiatives  active  in  the  field  of  data  intermediation  or 
sharing  both  in  B2B  situations  and  supporting  individuals  (personal  information  management 
services).  They  stressed  the  importance  of  trust  in  data  sharing  and  explored  mechanisms  for 
creation of such trust, namely neutral data intermediation services but also trust frameworks or 
data sharing ‘schemas’ that would lay down relevant technical and legal rules to be respected in 
data  sharing  situations.  This  could  ensure  ‘data  sovereignty’  by  businesses  in  data-sharing 
situations and empowerment of individuals with respect to use of their data.  

CONCLUSION: CONSIDERATION OF STAKEHOLDERS’ FEEDBACK IN THE IMPACT 
ASSESSMENT 

The consultation of stakeholders on the general issues of data sharing (obstacles across borders 
and sectors, and possible solutions at EU level for enhancing data sharing) has been an ongoing 
process  from  2017  onwards.  The  concept  of  common  European  data  spaces  has  been  explored 
for the preparation of the European strategy for data, notably with workshops of horizontal and 
sectoral  nature  held  in  2019  and  2020.  These  results  were  completed  with  input  from  all 
stakeholders on more technical questions such as governance mechanisms or standardisation, as 
well as input on specific types of action as data  altruism  or the enhanced use of certain  public 
sector data.  

All consultation actions revealed a strong support for the development of common European data 
spaces, and the human-centric approach to data sharing in general, as presented in the European 
Strategy on data.  

73 

 
 
 
 
 
ANNEX 3: WHO IS AFFECTED AND HOW? 

1.  PRACTICAL IMPLICATIONS OF THE INITIATIVE 

The  planned  legislative  framework  will  have  a  range  of  practical  implications  for  different 
groups of stakeholders from the entire data value chain: data holders (public bodies), data reusers 
(businesses  and  the  research  community),  data  intermediaries  (public  bodies,  patients 
association,  health  insurance  schemes,  and  research  organisations)  and  data  (co-)producers 
(individuals and other public sector authorities).  

The  initiative  will  benefit  public  sector  bodies  (e.g.  health  institutions,  transport  authorities, 
statistical  offices)  in  a  number  of  ways.  EU  level  coordination  will  facilitate  their  work  by 
clarifying how data can be used and who can access it, as well as by facilitating the sharing of 
legal and technical expertise. With more data available for reuse, the public sector will be able to 
deliver  more  efficient  public  services  and  make  more  informed  decisions,  leading  to  better 
policies.  This  will  help  enhance  public-service  delivery  and  facilitate  the  identification  of 
emerging governmental and societal needs. It can help improve forecasting and the reliability of 
infrastructures (such as in transportation and utilities).   

In the  context  of the secondary use of data subject  to  rights  of others, two broad  categories of 
data  holders  and  public  data  intermediaries  can  be  differentiated:  statistical  offices  and  health- 
and  social-related  data  holders/  intermediaries.  In  terms  of  data  holders:  as  regards  statistical 
offices  (and  other  public  authorities  responsible  for  the  development,  production  and 
dissemination of statistics), the European Statistical System keeps an up-to-date list that currently 
contains 286 entities, of which 27 are related to health (and therefore excluded from this count to 
avoid  double-counting). As a result, the number of data holders in  the EU27 when it comes to 
statistical  microdata  can  be  estimated  to  be  around  260.  As  regards  health-  and  social-related 
data, there are roughly 530 data holders in the health and social domains. In total, therefore, there 
are  around  800  impacted  data  holders.  In  terms  of  public  data  intermediaries,  there  are  around 
110 public data intermediaries in total171 (except those with a federal structure).  

Academic  and  research  institutions  will  benefit  from  the  increased  availability  for  reuse  of 
public  sector  data,  the  reuse  of  which  can  be  essential  for  research  purposes  for  the  common 
good, (e.g. health, location, or social media data) for research and innovative purposes through 
the proposed measures on the secondary use of data and data altruism. The possibility to reuse 
new  datasets  can  help  review  and  replicate  scientific  results,  and  foster  new  instruments  and 
methods  of  data-intensive  exploration  and  scientific  experimentation.  Academic  and  research 
institutions  will  benefit  from  the  availability  of  support  structures  in  Member  States.  In 
particular,  this  initiative  will  help  researchers  reuse  publicly  held  data  subject  to  conflicting 
rights under secure and privacy-enhanced environments in a similar way across the EU. This will 
contribute  to  the  scientific  developments  and  innovation  in  the  EU  as  a  whole,  particularly 
important in situations where EU coordinated action is necessary, like the COVID-19 crisis.  

171 It is unlikely that a given Member State would have more than one public data intermediary for the same domain, 
since the reason behind their existence is to streamline procedures. 

74 

 
                                                           
An  estimated  number  of  reusers  of  statistical  microdata  can  be  derived  from  Eurostat’s  list  of 
recognised research entities, which lists a total of 666 recognised research entities in the EU27. 
The  total  number  of  data  reusers  for  health  and  social  data  overlaps  with  the  research  entities 
recognised  by  Eurostat:  48  of  these  conduct  research  in  inter  alia  social  sciences,  while  22 
conduct research in a health-related domain. However, it also includes a large number of private 
companies  –  that  number  is  estimated  to  be  147 000  companies172.    Thus,  there  are  roughly 
150 000 data reusers impacted in total.  

Based  on  the  input  collected  from  the  interviews  organised  through  the  IA  support  study, 
providing high-quality metadata and documentation for scientific datasets requires 5 to 10% of 
the total project budget, which represents a substantial expenditure. Other sources estimate that 
the production of metadata and the contextual descriptions of datasets could span an estimated 2 
to 3 weeks from an average of a 2-year research grant application (OpenAire 2019).  

Industry  stakeholders  and/  businesses  (including  SMEs  and  start-ups)  across  the  economy 
(e.g. agriculture,  finance/banking, energy, transport, sustainability/environment, public services, 
smart manufacturing and data market places) will in particular benefit the measure taken in this 
initiative to facilitate cross-sectoral data use at the scale of the EU. They will also be providers of 
data and as such will be affected by the rules and limitations on data sharing. They will provide 
information and insights on the type of data governance mechanisms (organisational, technical, 
legal) needed to capture the potential of data in particular for cross-sector data use, in different 
data-sharing  configurations.  Through  enhancing  interoperability  at  the  technical  level  and 
making  available  generic  enabling  standards,  the  initiative  will  lower  transaction  costs  of  data 
sharing  and  facilitate  cross-sector  data  sharing.  The  benefits  of  standardisation  translate  into 
lower  technical  adaptation  costs  for  a  larger  range  of  companies  as  well  as  public  authorities, 
lower barriers to  enter markets or to develop entirely novel products or services. Such benefits 
influence  standardisation 
should 
prioritisation. SMEs would also substantially benefit from wider availability of public sector data 
as they typically cannot create large data pools themselves.  

in  particular  benefit  SMEs 

that  normally  cannot 

Enhanced access to data for reuse will create new business opportunities for smaller and larger 
firms. Better access to open government data, for instance, will allow entrepreneurs to develop 
innovative  commercial  and  social  goods  and  services.  An  example  is  RowdMap,  an  analytics 
company  that  uses  open  data  to  help  healthcare  plans,  physician  groups  and  hospital  systems 
identify, quantify, and reduce low-value care. In July 2017, the company was acquired for USD 
70 million by Cotiviti, a provider of analytics-driven payment accuracy solutions.   

172 This estimation was reached using:  
a) 

b) 
c) 

the number of people employed in the healthcare industry (800,000 in 2012 in the EU). See the  website of the 
European Commission on Healthcare Industries.  
the number of active businesses in the EU (27,5 million in 2017), and  
the number of employed persons in the EU (150 million persons in 2017). See Eurostat,  Business demography 
statistics.  These  figures  were  used  to  reach  an  average  number  of  employees  per  active  business 
the  number  of  healthcare  businesses  was  derived 
(150,000,000/27,500,00=5,45); 
(800,000/5,45=146788.99) and rounded-up. 

from  which 

75 

 
                                                           
In  the  era  of  the  Internet  of  Things,  data  collection  by  sensors  will  provide  consumers  with 
innovative smart products and services that will increasingly replace traditional products. Also, 
the data collected in  this industry will be of particular utility to  private actors in  very different 
business sectors and to public entities. Hence, data collected by smart products will become an 
important input both for other businesses and for the public authorities. 

In addition, the initiative supports the emerging offer of data intermediaries that can make the 
data  economy  more  fluid,  i.e.  entities  that  enable  any  kind  of  data  holder  (persons,  business, 
public sector bodies, academic or not-for profit organisations) to share their data of all types with 
other  organisations,  and  which  may  provide  additional  value-added  services.  Enhanced  data 
access and sharing will enable many business opportunities for data intermediaries, mobile apps 
and personal information management systems.  

The planned initiative will lower transactions costs in data sharing by supporting the offer of data 
intermediaries.  Companies  providing  data-sharing  services  may  face  an  additional  burden  in 
terms  of  certification  or  labelling,  but  only  if  such  certification  or  labelling  would  become 
compulsory. Such burden would need to be balanced against the advantages such certification or 
labelling  would  provide  to  them  in  terms  of  increased  business  resulting  from  more  market 
participants trusting them.  

An  estimation  of  the  total  number  of  data  intermediaries  active  in  the  European  market  could 
include  100-150  organisations,  while  the  number  of  data  users  or  data  holders  affected  could 
entail  any  European  company  or  individual  wishing  to  buy  or  sell  data  through  the 
intermediaries.  The  companies  present  big  differences  in  the  scale  of  client  base.  In  particular, 
Siemens’ Mindsphere counted more than 6 100 customers in March 2020; the client base of the 
personal data operator Peercraft includes approximately 100.000 uses, while Dawex’ client base 
include more than 10 000 organisations. Finally, the example of the data trust UK Biobank holds 
data from about 0.5m people and it includes the number of 946 researchers using its data in its 
annual  accounts  of  2018.  This  would  therefore  give  a  ratio  of  roughly  50 000:1:1 000  (data 
holders: data intermediary: data reusers). 

The  initiative  will  bring  enormous  benefits  to  individuals,  for  example  through  improved 
mobility,  more  personalised  medicine,  reduced  energy  consumption  and  more  effective 
responses  to  tackle  pressing  societal  challenges,  such  as  climate  change  and  recovering  from 
today’s  health  pandemic.  It  will  be  easier  for  individuals  to  allow  the  use  of  their  data  for  the 
public good (e.g. people with rare or chronic diseases allowing for use of data in order to help 
cure or improve treatment of those diseases) (‘data altruism’). The framework will also empower 
individuals interested in reusing the data for their own benefit (e.g. for personalised dashboards, 
services, etc.). Other benefits to the European economy would include: lower switching costs for 
users  when  changing  providers;  lower  entry-barriers  for  firms  in  digital  markets;  increased 
personalisation  of  goods  and  services;  and  increased  innovation  driven  by  valuable  user-level 
insights.  In  addition,  access  to  a  greater  variety  of  data  to  train  models  and  test  results  could 
contribute to the ethical and effective use of AI.   

The proposed framework envisages structures, mechanisms, technical guidance and standards so 
that  individuals  can  exercise  their  rights  in  a  simple  and  not  overly  burdensome  way  and 

76 

 
organisations, including research ones, can create value for society while respecting the privacy 
of individuals. 

The wider benefits to society are manifested in cost reduction, quality improvement and greater 
choice  for  consumers.  Benefits  such  as  reduced  healthcare  costs,  improved  levels  of  care  and 
reduced environmental degradation that are derived from more intelligent and efficient systems 
accrue to society as a whole, not just particular sectors or groups of consumers. 

2.  SUMMARY OF COSTS AND BENEFITS 

The figures cited in the tables below illustrate the costs under the preferred option in relation to 
its specific elements for different types of stakeholders. They are based on the quantitative model 
developed as part of the Support study by Deloitte. 

The  overall  methodology  used  by  the  study  to  estimate  the  baseline  scenario,  as  well  as  the 
impacts of the policy options, are provided in Annex 4. 

Overview of Benefits (total for all provisions) – Preferred Option 

Description 

Direct benefits 

Amount 

Comments 

Effect on Gross Domestic Product (GDP) 

EUR  10.9  billion 
in 
2028  (0.079  %  of  GDP 
in 2028). 

Costs  Savings  and  efficiency  gains  - 
Easier discovery and reuse of data (due to 
the  creation  of  mechanisms,  including  a 
one-stop shop) 

EUR 49.2 million/year  Benefits  for  data  reusers  for 
the EU-27, assuming a saving 
of  20  hours  of  work  per 
application. 

Costs  Savings  and  efficiency  gains  - 
Lower  cost  of  data  processing  and 
management  (due 
the  creation  of 
to 
mechanisms, including a one-stop shop) 

EUR 684 million/year  Benefits  for  data  holders  for 
the EU-27, assuming that 20% 
of data holders relinquish their 
dedicated 
processing 
data 
environment  and  30%  of  the 
data  pre-processing  work  is 
passed  on 
the  one-stop 
to 
shops. 

Costs Savings and efficiency gains linked 
to 
the  set-up  of  a  European  Data 
Innovation  Board  in  charge  of  enhanced 
governance of standardisation 

EUR 5,335.6 million 

assuming 

for  participating 
Efficiency 
companies 
800 
companies  and  50M  EUR 
turnover 
IDS 
based 
examples 

on 

Business  development 

linked 

to  data  25%-50% 

business   

77 

 
 
 
 
intermediary certification/labelling 

Easy  and  transparent  way  to  access  data 
of  various  fields,  contributing  to  research 
and  development  as  well  as  improved 
decision-making 

development 
acceleration 
intermediaries 

time 
for  data 

EUR 300 million 

Indirect benefits 

Contribution  to  societal  goals  through 
improved policy- and decision-making 

Not  quantifiable  due  to 
lack of data 

Improved  policy  making  for 
government  as  for  example 
data altruism has proved to be 
valuable  during  the    COVID-
19  pandemic.  Other  examples 
are  smart  city  initiatives  and 
the 
environmental  data  for 
public good. These would then 
be  improve  public  services 
and goods. 

Especially data altruism could 
enhance societal goals such as 
achieving 
environmental 
goals,  building  smart  cities  of 
the  future  and  help  eradicate 
pandemics (as  is  currently  the 
case with COVID-19). 

R&I  and  competition  advancement  for 
data intermediaries in the B2B market 

R&I  and  competition  advancement  for 
data intermediaries in the C2B market 

Between 1%-25% 
competition increase in 
data intermediaries 
B2B market, in a  2-5 
years' timeframe, 

and  between  1%-25% 
competition  increase  in 
intermediaries 
data 
in  a 
B2B  market, 
beyond 
years' 
timeframe. 

5 

Between 1%-25% 
competition increase in 
data intermediaries 
C2B market within a 
one-year timeframe 
after obtaining the 
certification/label in 2- 
5 years' timeframe; 

and between 25%-50% 

78 

 
 
 
 
 
competition increase in 
data intermediaries 
C2B market, beyond 5 
years' timeframe 

II. Overview of costs – Preferred option 

Data holders  

Data intermediaries 

Data (re)users 

One-off 

Recurrent 

One-off 

Recurrent 

One-off 

Recurrent 

Public sector bodies 

Mechanisms  (incl.  one-stop-
shop) 

Researchers 
businesses 

and 

EUR 
million/year 

7.6 

EUR 
million 

286.4 

EUR 
million/year 

16.5 

-  

EUR 
41.8 
million/year 

- 

- 

- 

- 

Measures 
facilitating 
secondary  use 
of 
sensitive 
data  held  by 
public 
the 
sector 

(low intensity) 

Concerne
d parties 

Direct 
costs173 

Indirect 
costs 

- 

- 

Certification/la
belling 
framework  for 
data 
intermediaries(
low intensity) 

Concerne
d parties 

Businesses, 
academia, researchers 

citizens, 

Certified/labelled 
intermediaries 

data 

Businesses 

Direct 
costs 

Indirect 
costs 

- 

- 

- 

- 

- 

- 

EUR  20 000-
50 000 

EUR  20 000-
35 000/year 

- 

Approximately 
25% 
decreased 
market 
competition  in 
B2B  market 
within  the  1st 
after 
year 
obtaining 
certification  

- 

- 

Non-
quantifiable 
costs  due  to 
lack of data 

An  EU-wide 
data  ‘altruism’ 

Concerne
d parties 

Citizens,  businesses,  public 
sector authorities 

Public 
sector 
research orgs, businesses 

authorities, 

sector 

Public 
researchers 

bodies, 

173These numbers show the aggregate amount for the entire EU27, including the costs for all Member States. 

79 

 
 
 
 
 
 
                                                           
scheme  

(high intensity) 

Giving 
consent  to 
make  data 
available 

Giving consent 
to  make  data 
available 
be 
(could 
recurrent  if  it 
is revoked) 

Non-
quantifiable 
costs  due 
lack of data  

to 

Direct 
costs 

- 

Maintain  data 
altruism 
authorisation 
EUR 5 000 

Becoming 
authorized  (if 
applicable) 

3 800-

EUR 
10 500 
depending  on 
the  size  of  the 
organization 

Establish 
scheme/author
ization 
process    and 
national 
oversight body 
(for 
public 
authorities) 

Non-
quantifiable, 
however  every 
state 
EU-27 
has  a  data 
authority 
(or 
equivalent) 
that 
implement 
this. 

could 

Indirect 
costs 

- 

Concerne
d parties 

Businesses 

Direct 
costs 

Indirect 
costs 

- 

- 

- 

- 

- 

for 

European 
structure 
governance 
aspects  of  data 
sharing 

(low intensity) 

- 

- 

- 

- 

Public 
organisations 

and 

private 

Other  businesses  and 
researchers 

EUR 
280.000/year 
for 
the group 

running 

- 

- 

- 

- 

- 

- 

- 

80 

 
 
 
 
 
 
 
ANNEX 4: ANALYTICAL METHODS 

1.  Overall methodology of the study 

For each of the sub-tasks, the Study to support an Impact  Assessment on enhancing the use of 
data  in  Europe  (VIGIE  2020-0694)  was  carried  out  in  three  Phases  (inception,  data  collection, 
and  analysis).  With  regard  to  the  collection  of  data,  the  following  key  methodological  and 
analysis tool were implemented174:  

Interviews with stakeholders; 

-  Desk research; 
- 
-  Case studies; 
-  Workshops with key stakeholders; 
-  Analysis of the public consultation175 launched by the European Commission 
-  Targeted questionnaires to legal experts. 

An overview of these data collection tools is provided below.   

Details 

Tool 
Desk research  Desk research was a continuous exercise throughout the study and 
informed the stakeholder mapping, the preparation of the interview 
guidelines, drafting of case studies, as well as the draft reporting of 
findings. It provided information on the state of play and context for each 
subtask.  It was based on academic publications, databases and data 
marketplaces (e.g. Gartner, Forrester Research, Economist Intelligence 
Unit). 
Semi-structured  interviews  were  conducted  to  collect  first-hand  material 
from key stakeholders, both on the state of play of the topic concerned and 
the  impact  of  the  different  policy  options.  Interviews  were  particularly 
useful to discuss the costs and benefits of the different options. 
Interviews were conducted with the following types of stakeholders:  

Interviews  

  Data holders  
  Data (re)users 
  Data intermediaries 

Workshops 

Two workshops were organised to enable an in-depth discussions with key 
stakeholders on certain topics: 

  Measures  facilitating  secondary  use  of  sensitive  data  held  by  the 

public sector 

  Establishment a European structure for governance aspects of data 

sharing 

174 The data collected through the implementation of the above tools will be analysed through the application of the 
following analytical methods and processes: Legal analysis; Triangulation; Analysis of costs and benefits; and 
Multi-Criteria Analysis. 
175 https://ec.europa.eu/digital-single-market/en/news/online-consultation-european-strategy-data 

81 

 
                                                           
Tool 

Case studies 

Public 
consultation 
analysis 

Details 
Case studies (i.e. in-depth and detailed investigations) were carried out to 
demonstrate what is going on in certain domains, what works, what does 
not  work  and  whether  ‘types’  of  approaches  can  be  discerned.  As  such, 
they  were  particularly  useful  for  defining  the  baseline  scenarios  for  the 
different  sub-tasks  and  developing  hypotheses  on  the  impact  of  the 
different policy options. 
A  public  consultation  on  the  European  strategy  for  data  was  carried  out 
from 19 February 2020 to 31 May 2020.  
The questions included in the public consultation were taken into account 
when  the  interview  guides  were  prepared  in  order  to  avoid  duplication. 
The  results  of  the  public  consultation  were  used  to  support  the  analyses 
during the study.  

2.  Data analysis activities 

A market  analysis was carried out  for sub-task 1.4 (‘Data intermediaries’) to  better understand 
the business environment and data based value chains as well as to identify the key players and 
key positions on the market. 

A legal analysis was carried out for all sub-tasks, with a more in-depth assessment for sub-task 
1.2 (‘Establishing an EU wide “Data Altruism” scheme’). 

The cost-benefit  analysis was  elaborated individually  for each of the sub-tasks. The evaluation 
process  considered  the  costs  and  benefits  for  the  different  (main)  stakeholders  associated  with 
each  task.  The  stakeholders  were  divided  into  the  following  categories:  data  holders,  data  co-
producers, data reusers, and data intermediaries. Impacts on society, environment, economy and 
fundamental rights are also taken into account. 

The key steps in the CBA are outlined in the figure below. 

82 

 
 
 
It is in general possible to calculate the project economic performance measured by the following 
indicators176: 

  Economic Net Present Value (ENPV): The ENPV is defined as the difference between the 
discounted  total  socio-economic  benefits  and  the  discounted  total  costs.  The  ENPV  is 
comparable with the Net Present Value in financial analysis, but it also takes into account the 
broader  socio-economic  effects.  A  positive  (economic)  net  present  value  indicates  that  the 
projected  benefits/earnings  generated  by  a  project  or  investment  (in  present  euros)  exceeds 
the  anticipated  costs  (also  in  present  euros).  Generally,  an  investment  with  a  positive 
ENPV/NPV will be a profitable one and one with a negative ENPV/NPV will result in a net 
loss. This  concept  is  the basis for the Net  Present  Value Rule,  which dictates that the only 
investments that should be made are those with positive NPV values.  

  Economic Rate of Return (ERR): The ERR is defined as the rate that produces a zero value 
for  the  ENPV;  it  is  comparable  with  the  ROI  (Return  on  investment)  respectively  the  IRR 
(Internal  rate  of  Return)  in  financial  analysis.  It  is  another  metric  commonly  used  as  an 
ENPV/NPV alternative. Calculations of ERR/IRR rely on the same formula as ENPV/NPV 
does, except with slight adjustments. ERR/IRR calculations assume a neutral ENPV/NPV (a 
value of zero) and one instead solves for the discount rate. The discount rate of an investment 
when ENPV/NPV is zero is the investment’s ERR/IRR, essentially representing the projected 
rate  of  growth  for  that  investment.  Because  ERR/IRR  is  necessarily  annual  –  it  refers  to 
projected returns on a yearly basis – it allows for the simplified comparison of a wide variety 
of types and lengths of investments.  

  Benefit/Cost-ratio  (B/C-ratio):  The  Benefit-Cost  ratio  is  defined  as  the  ratio  between  the 
sum  of  the  discounted  economic  benefits  and  the  sum  of  the  discounted  costs.    By  putting 
together the outcomes of the several factors analysed and calculated, it is possible to compute 
and interpret these three pillars of economic analysis. The different expressions are defined 
as follows. 

176  Source:  European  Commission,  2014:  Guide  to  Cost-Benefit  Analysis  of  Investment  Projects  –  Economic 
appraisal tool for Cohesion Policy 2014 – 2020.   

83 

 
 
 
 
                                                           
The  economic  performance  indicators  were  calculated  for  each  task  as  well  as  for  each 
stakeholder, to the extent possible. To do so, assumptions were defined considering the limited 
availability of quantitative data. 

Any CBA is  based on a number of assumptions (statistical  input as well as certain  estimations 
made by the various stakeholders) that could be critical to the outcome of the analysis. As part of 
the risk and sensitivity analysis, the critical assumptions were identified and their effects on the 
outcome  determined.  Various  sensitivity/scenario  and  risk  analyses  were  performed  to  analyse 
the robustness and sensitivity of the results with regard to critical variables.  

Impacts that could not be monetized were evaluated in a qualitative manner.  

Quality standards for impact modelling  

Specific data on costs and benefits is often scarce, inconclusive, and patchy. Any CBA is based 
on a number of assumptions (statistical input as well as certain estimations made by the various 
stakeholders) that could be critical to the outcome of the analysis, e.g. qualitative information to 
fill existing gaps. Oftentimes, these assumptions are based on expert judgment. This means that 
the  data  used  in  the  underlying  formulas  is  based  on  the  best  data  available,  challenged  and 
refined (where necessary) by the experts of the consortium for this assignment.  

Therefore, in practice, the assumptions used for the CBA are subject to an internal, in-depth peer 
review  process.  As  part  of  this  process,  different  assumptions  are  introduced  in  the  model  to 
compare the different outcomes. Thus, the critical assumptions are identified and their effects on 
the outcome are determined. This means the risk and sensitivity analysis indicates variances of 
economic effects  as  a result of changes of operational  figures. Various sensitivity/scenario  and 
risk analyses were performed to analyse the robustness and sensitivity of the results with regard 
to critical variables. 

Figure  – Abstract for subtask 1.1 

The  extent  to  which  an  effective  sensitivity  analysis  can  be  conducted  is  closely  linked  to  the 
quality  of  the  CBA.  Each  of  abovementioned  calculations  was  carried  out  within  a  Microsoft 
Excel  model  that  was  built  specifically  for  this  assignment.  Deloitte’s  Excel  models  generally 
follow  the  FAST  standard177,  consisting  of  practical,  structured  design  rules  for  financial 
modelling.  

  Flexible: Model design and modelling techniques must allow models to be both flexible in 
the  immediate  term  and  adaptable  in  the  longer  term.  Models  must  allow  users  to  run 
scenarios  and  sensitivities  and  make  modifications  over  an  extended  period  as  new 

177 See: http://www.fast-standard.org/wp-content/uploads/2016/06/FAST-Standard-02b-June-2016.pdf    

84 

 
  
                                                           
information becomes available - even by different modellers. A flexible model is not an all-
singing, all-dancing template model with an option switch for every eventuality. Flexibility is 
born of simplicity.  

  Appropriate:  Models  must  reflect  key  business  assumptions  directly  and  faithfully  without 
being overbuilt or cluttered with unnecessary detail. The modeller must not lose sight of what 
a  model  is:  a  good  representation  of  reality,  not  reality  itself.  Spurious  precision  is 
distracting,  verging  on  dangerous,  particularly  when  it  is  unbalanced.  For  example,  over-
specifying  tax  assumptions  may  lead  to  an  expectation  that  all  elements  of  the  model  are 
equally  certain  and,  for  example,  lead  to  a  false  impression,  if  the  revenue  forecast  is 
essentially guesswork.  

  Structured:  Rigorous  consistency  in  model  layout  and  organisation  is  essential  to  retain  a 
model’s  logical  integrity  over  time,  particularly  as  a  model’s  author  may  change.  A 
consistent  approach  to  structuring  workbooks,  worksheets  and  formulas  saves  time  when 
building, learning, or maintaining the model.  

  Transparent:  Models  must  rely  on  simple,  clear  formulas  that  can  be  understood  by  other 
modellers and non-modellers alike. Confidence in a financial model’s integrity can only be 
assured  with  clarity  of  logic  structure  and  layout.  Many  recommendations  that  enhance 
transparency also  increase the flexibility of the  model to  be adapted over time and make it 
more easily reviewed.  

Multi-criteria analysis  

In line with the EC’s Better Regulation Guidelines, a Multi-Criteria Analysis (MCA) was carried 
out, in parallel to the Cost-Benefit Analysis, to identify the preferred policy option for each sub-
task. 

The MCA is  a largely qualitative analysis of the policy options, based on ratings and rankings 
with  quantitative  data  supporting  the  assessment.  For  this  reason,  MCAs  accompany  Cost 
Benefit  Analyses  and  Economic  Modelling  but  do  not  replace  them.  As  part  of  the  Multi-
Criteria-Analysis,  the  most  significant  impacts  were  assessed  as  a  comparison  to  the  baseline 
scenario:  

  Economic impacts;  
  Societal impacts; and  
  Environmental impacts.  

The impacts on Fundamental Rights was used as exclusion criterion.  

The following criteria were taken into to assess these impacts:  

  Effectiveness, i.e. the extent to which different options would achieve the objectives;  
  Efficiency,  i.e.  comparing  the  benefits  of  the  options  versus  the  costs  (incl.  additional  and 

reduced compliance costs);  

  Coherence with the overarching objectives of EU policies; 
  Legal and political feasibility;  
  Compliance of the options with the proportionality principle.  

The proportionality principle was used as an exclusion criteria. 

The sources of information were also defined, i.e. existing data (i.e. secondary data from other 
studies  or  databases),  new  data  (i.e.  primary  data)  derived  from  interviews,  as  well  as  the 
workshops.  

85 

 
 
The  same  assessment  criteria  were  used  for  all  policy  options.  Using  the  same  criteria  ensures 
comparability across the policy options, which is imperative for the comparison of the options.  

When carrying out the assessments, the expected timing of the impacts (one-off, short term, long 
term) was taken into account, considering changes in the baseline scenario for the specific time-
frame considered.  

While  the  impacts  were  assessed  from  the  point  of  view  of  society  as  a  whole,  impacts  on 
different  groups  of  society  (e.g.  data  holders,  data  intermediaries,  data  reusers)  were 
differentiated.  

The picture bellows summarises the key steps leading to a full Multi-Criteria-Analysis. 

86 

 
 
 
 
 
 
ANNEX 5: SUBSIDIARITY GRID 

1.  Can the Union act? What is the legal basis and competence of the Unions’ 

intended action? 

1.1 Which article(s) of the Treaty are used to support the legislative proposal or 
policy initiative? 

This initiative follows from the 2020 European Strategy for data, which aims to create a 
Single Market for Data. With a growing digitalisation of the economy and society, there 
is a risk that Member States increasingly regulate data-related issues in an uncoordinated 
way;  this  will  intensify  fragmentation  in  the  internal  market.  Therefore,  this  legislative 
proposal is based on Article 114 of the Treaty on the Functioning of the European Union 
(TFEU). This article provides for the EU to adopt measures for the approximation of the 
provisions laid down by law, regulation or administrative action in Member States which 
have as their object the establishment and functioning of the internal market in the EU.   

1.2 Is the Union competence represented by this Treaty article exclusive, shared or 
supporting in nature? 

Digital policies are a shared competence between the EU and its Member States. Articles 
4(2) and (3) of the TFEU specify that, in the area of the internal market and technological 
development, the EU can carry out specific activities, without prejudice to the Member 
States’ freedom to act in the same areas. 

2.  Subsidiarity Principle: Why should the EU act? 

2.1 Does the proposal fulfil the procedural requirements of Protocol No. 2178: 

-  Has there been a wide consultation before proposing the act? 

A consultation process supported the preparation of this proposal and its accompanying 
Impact  Assessment.  An  online  public  consultation  was  launched  on  19  February  2020, 
targeting  all  types  of  stakeholders.  It  ran  until  31  May  2020  and  collected  806  replies. 
This  consultation  was  specifically  prepared  in  order  to  provide  input  to  this  initiative. 
The  Inception  Impact  Assessment  was  also  open  to  feedback  from  all  types  of 
stakeholders, as was the Eurobarometer on the impact of digitisation. 

Furthermore,  the  initiative  builds  on  recent  consultation  actions,  including  the  2017 
public consultation on building a European data economy,  the 2018 public consultation 

178 Protocol (No 2) - On the Application of the Principles of Subsidiarity and Proportionality. 

87 

 
                                                           
  
on the revision of the Directive on the reuse of public sector information, and the 2018 
SME panel consultation on the B2B data-sharing principles and guidance.  

In  addition,  a  series  of  10  workshops  on  common  European  data  spaces  took  place  in 
2019 and an additional one in May 2020, in view of exploring with the relevant experts 
the  framework  conditions  for  creating  common  European  data  spaces  in  the  identified 
sectors. Gathering in total more than 300 stakeholders, mainly from the private and the 
public  sectors, 
(agriculture,  health, 
finance/banking,  energy,  transport,  sustainability/environment,  public  services,  smart 
manufacturing)  as  well  as  more  cross-cutting  aspects  (data  ethics,  data  market  places). 
The concerned DGs were involved in these workshops. 

the  workshops  covered  different  sectors 

- 

Is  there  a  detailed  statement  with  qualitative  and,  where  possible,  quantitative 
indicators  allowing  an  appraisal  of  whether  the  action  can  best  be  achieved  at 
Union level? 

The  Explanatory  Memorandum  of  the  proposal,  as  well  as  the  Impact  Assessment 
(Chapter 3 – ‘Why should the EU act?’), contain dedicated sections on subsidiarity and 
added value, as explained in section 2.2 below. 

2.2 Does the explanatory memorandum (and any impact assessment) accompanying 
the Commission’s proposal contain an adequate justification regarding the 
conformity with the principle of subsidiarity? 

The  Impact  Assessment  accompanying the proposal  features a dedicated  section on the 
conformity of the proposed initiative with the principle of subsidiarity (Chapter 3). This 
is also reflected in the Explanatory Memorandum.  

The  problem  analysis  revealed  that,  despite  the  growing  digitisation  of  society  and  the 
economy, public and private actors in the data economy continue to struggle to access the 
data they need from other sectors or Member States to  develop  and roll  out  data-based 
products and services. Furthermore, some Member States are already legislating certain 
aspects  or  sectors  of  the  data  economy  while  others  are  not.  This  increasing  legal 
fragmentation  may  lead  to  inconsistent  regulatory  action  across  the  EU  and  even 
potential conflicts of law with the EU acquis. In addition to legislative intervention, some 
Member States are supporting industry-driven approaches to data governance (examples 
in section 3.2 of the Impact Assessment). This can lead to divergences between sectors 
and  Member  States,  as  they  have  different  priorities.  These  unresolved  problems  plead 
for  action  at  EU  level,  as  was  called  for  by  the  Member  States  in  their  Council 
conclusions of 9 June 2020179. 

2.3 Based on the answers to the questions below, can the objectives of the proposed 

179 Council of the European Union Conclusions (9 June 2020). 

88 

 
                                                           
action be achieved sufficiently by the Member States acting alone (necessity for 
EU action)? 

The assessment of the barriers related to data sharing in the Impact Assessment has led to 
the  conclusion  that  the  objectives  cannot  be  achieved  sufficiently  by  Member  States 
acting  alone  for  a  number  of  reasons.  Big  data  and  AI  need  large  datasets  that  also 
contain data on rarer situations (so-called ‘long tail’), which are hard to find in individual 
Member States alone. Also, the development of pan-European data services and products 
requires  data  from  more  than  one  Member  State.  Finally,  a  market  for  novel  data 
intermediaries  can  only  develop  at  the  scale  of  more  than  one  Member  State.  Member 
States  and  their  public  authorities  have  supported  this  initiative  at  the  political  level 
(Council conclusions of 9 June 2020), and through the different consultation actions.  

(a)  Are there significant/appreciable transnational/cross-border aspects to the 

problems being tackled? Have these been quantified? 

Hurdles  to  data  sharing  are  encountered  with  regard  to  sharing  between  economic 
operators (public or private), between sectors, but also between Member States.  

Such  obstacles  have  been  investigated  extensively  since  2017,  especially  through  the 
consultation  that  led  to  the  adoption  of  the  Regulation  on  the  free  flow  of  data 
(addressing the specific issue of data localisation restrictions). The study supporting the 
Impact Assessment for this proposal, together with the consultation process, showed that 
individual  Member  States  are  pioneering  approaches  to  data  governance  and  related 
standardisation and starting legislating on enhanced use of ‘sensitive’ public sector data, 
with  a  risk  of  regulatory  fragmentation  between  Member  States  and  sectors.  These 
differentiated  approaches  increase  the  transaction  costs  when  developing  new  data-
related products and services across the EU.   

(b) Would national action or the absence of the EU level action conflict with core 

objectives of the Treaty180 or significantly damage the interests of other Member 
States? 

Member States action naturally is departing from industrial interests present in a Member 
State. For example, Franco-German Gaia-X departed from interests of the manufacturing 
industry,  given  a  strong  presence  of  original  equipment  manufacturers  (OEMs)  in 
Germany  and  France.  Similarly,  the  Dutch  iShare  scheme  evolved  around  the  logistics 
industry  that  has  a  strong  presence  in  that  Member  State.  Data-sharing  initiatives  in 
agriculture  are  most  developed  in  France  (cf.  API-Agro  platform).  These  examples 
illustrate  that  a  European  approach  is  necessary  to  ensure  that  there  are  no  –  even 

180 European Union: The EU in brief.  

89 

 
                                                           
unintentional  –  advantages  for  industrial  players  in  any  single  Member  State,  but  the 
approach should serve the interests of businesses in  all Member States from  the outset. 
Disadvantages can arise, e.g. if industrial players in one Member State are predominantly 
suppliers  whereas  the  OEMs  are  typically  present  in  another  Member  State  (a  concern 
voiced by Danish industry). Disadvantages could also materialize in rules of participation 
on  the  governance  of  common  European  data  spaces,  standardisation  or  other  rules-
setting  on  data  sharing  in  such  data  spaces,  which  makes  cross-sector  data  use  more 
difficult.  Also,  data-sharing  initiatives  are  ultimately  necessary  in  all  industries.  Pace-
setting initiatives in some Member States may not focus on the needs of other industrial 
sectors that are more strongly present in other Member States. Pioneering of data-sharing 
initiatives,  governance  mechanisms  and  technical  platforms  or  architectures  through 
Member States alone risks therefore not to sufficiently factor in industrial interests in all 
countries.  Finally,  mechanisms  that  enhance  the  use  of  ‘sensitive’  public  sector  data  in 
individual  Member  States  should  neither  explicitly  nor  implicitly  favour  data  users  of 
that specific Member State.  

(c)  To what extent do Member States have the ability or possibility to enact 

appropriate measures? 

The  internal  market  is  an  area  in  which  Member  States  and  the  EU  have  shared 
competences.  In  the  absence  of  European  action  on  data  sharing,  individual  Member 
States  have  taken  action,  in  the  form  of  legislation  or  by  supporting  industry-driven 
initiatives.  As  described  above,  this  entails  risks  of  –  even  unintentionally  –  favouring 
their  own  industrial  players.  Actions  at  national  level  cannot  create  access  to  the  pan-
European databases that are necessary for big data analyses or machine learning. 

On  the  other  hand,  while  the  EU  has  a  competence  to  regulate  under  Article  114(1) 
TFEU where there is an actual or potential obstacle to any of the fundamental freedoms, 
this  proposal  does  not  prohibit  Member  States’  ability  to  enact  further  appropriate 
measures in the data economy. In particular, the proposal will leave considerable margin 
to  Member  States  on  the  ‘how’  of  the  implementation  of  the  rules,  notably  how  to 
provide enhanced access to public sector information which is subject to rights of others.  

(d) How does the problem and its causes (e.g. negative externalities, spill-over 
effects) vary across the national, regional and local levels of the EU? 

There  is  no  significant  variation  in  the  magnitude  of  the  problem  of  insufficient  data 
sharing and its underlying causes at national, regional or local level. However, evidence 
shows that data reusers in larger Member States benefit from larger (and therefore often 
more representative) datasets. EU-wide exchanges would allow more actors to use a large 
range of datasets for big data purposes (e.g. for research purposes). Also, certain Member 
States  (including  France,  Germany,  the  Netherlands,  Denmark  and  Finland)  have 

90 

 
developed national strategies or supported industry-driven initiatives on data sharing that 
will benefit players in these countries, but would not necessarily benefit other industries 
with  strong presence in  other Member States. This  could  lead to  further disparities and 
unequal distribution of benefits of digitisation within the EU.  

(e)  Is the problem widespread across the EU or limited to a few Member States? 

The problem of insufficient data sharing is widespread across the EU, however it affects 
Member  States  with  different  levels  of  intensity.  This  is  partly  linked  to  a  Member 
State’s level of digitisation and the state of its national data economy. Member States are 
increasingly  aware  of  the  growing  value  of  data  for  their  economic  and  societal 
development,  including  for  post  COVID-19  recovery  programmes.  They  are  launching 
initiatives of varied intensity, including legislation, that aim to resolve different  aspects 
of this problem. There are risks of doing this in potentially diverging ways, but also that 
economic disparities within the EU will deepen further as some Member States advance 
faster than others.  

(f)  Are Member States overstretched in achieving the objectives of the planned 

measure? 

Member States will need to target funding at developing the mechanisms and structures 
proposed  in  this  instrument.  As  Member  States  will  remain  in  control  of  the  extent  of 
their  novel  services  to  enhance  the  better  use  of  certain  public  sector  information,  no 
Member State should be stretched. In particular, the instrument does not prescribe the use 
of a particular technology or institutional form of the structures/bodies that need to be in 
place.  

Additionally,  EU  funding  will  be  available  to  Member  States  to  help  with  the 
implementation  of  this  and  other  EU  measures.  Overall,  the  economic  and  societal 
benefits obtained through this intervention would be significantly higher than the costs, 
as explained in Chapter 6. As well as economic and societal welfare gains, businesses (in 
particular  SMEs),  researchers  and  citizens  stand  to  benefit.  Acting  at  EU  level  would 
achieve greater impact in a more effective and efficient manner.  

(g) How do the views/preferred courses of action of national, regional and local 

authorities differ across the EU? 

Member States have been unanimous in asking for action to improve data sharing at the 
European level. The March 2019 European Council conclusions state that: “the EU needs 
to go further in developing a competitive, secure, inclusive and ethical digital economy 

91 

 
with world-class connectivity. Special emphasis should be placed on access to, sharing of 
and use of data, on data security and on AI, in an environment of trust”181. 

In the Council conclusions on ‘Shaping Europe’s digital future’ of 9 June 2020, Member 
States also unanimously called on the Commission to present concrete proposals on data 
governance  and  to  encourage  the  development  of  common  European  data  spaces  for 
strategic sectors of industry and domains of public interest182. On 9 July 2020, the Digital 
Single Market Strategic Group, composed of Member States’ representatives, discussed 
initial ideas for the legislative framework on the common European data spaces, based on 
the Inception Impact Assessment, and expressed strong support for the improvement of 
data governance at EU level. Views and actions differ in terms of industries that Member 
States focus on when supporting industry-driven data sharing and governance initiatives.  

The  public  sector  at  national,  regional  and  local  level  was  consulted  through  different 
actions  during  the  preparation  of  the  initiative  (workshops,  online  consultation).  Some 
Member States (notably  France,  Finland and Germany) have shared their experience in 
establishing specific bodies that offer technical mechanisms to create secure and privacy-
enhancing conditions for the reuse of data subject to the rights of others. This has proved 
to drive forward a sharing and reuse culture. In the online consultation, public authorities 
were clearly in favour of developing governance mechanisms to support standardisation 
activities for interoperability purposes. They considered that EU or national government 
bodies have a role to play in the prioritisation and coordination of standards. They also 
considered that they have a role to play in the clarification of the legal rules. Finally, they 
agreed that public authorities should make a broader range of sensitive data available for 
R&I purposes and for the public interest.  

2.4 Based on the answer to the questions below, can the objectives of the proposed 
action be better achieved at Union level by reason of scale or effects of that 
action (EU added value)? 

Considering  the  importance  of  economies  of  scale  for  the  development  of  data 
technologies and services, coordinated action at European level will bring higher value to 
the European economy and society than action by individual Member States. Chapter 6 
of the Impact Assessment shows the potential direct and indirect benefits of the initiative, 
such as greater access to data, costs savings, efficiency gains and economic and societal 
benefits.  

While  allowing  the  Member  States  to  take  further  action  in  this  area,  the  proposed 
instrument will ensure that future national and sectoral legislation flows from a number 
of  horizontal  principles  that  make  data  sharing  fit  for  cross-sectoral  and  EU-wide 
exchanges. It will ensure that all industry players benefit, irrespective of their situation in 

181 Council of the European Union Conclusions (22 March 2019).  
182 Council of the European Union Conclusions (9 June 2020). 

92 

 
                                                           
industrial supply chains. It will also ensure that all industrial sectors benefit, taking into 
account  the  respective  strengths  of  all  Member  States.  Furthermore,  the  proposed 
instrument brings clarity on what can be done with public sector data and by whom. 

(a)  Are there clear benefits from EU level action?  

The instrument would lead to demonstrable benefits compared to the lack of EU action or 
to other policy options,  as explained in Chapter 6 of the  Impact  Assessment.  It ensures 
that data sharing can happen across sectors and between Member States. These benefits 
are  achievable  only  at  the  EU  level  due  to  the  scale  of  the  internal  market  and  the 
economies of scale that harmonised initiatives bring to this.  

(b) Are there economies of scale? Can the objectives be met more efficiently at EU 

level (larger benefits per unit cost)? Will the functioning of the internal market be 
improved? 

The  measures  will  improve  the  functioning  of  the  Single  Market  for  Data  and 
consequently  of  the  Single  Market  as  a  whole.  Products  and  services  in  the  future  will 
benefit at various stages (strategic investment decisions on novel products and services, 
product  design,  product  processing,  product  surveillance  and  design  feedback  loops) 
from  big  data  analysis,  use  of  sensor  (IoT)  data  and  machine  learning.  For  certain 
products  or  services,  access  to  large  volumes  of  data  are  important.  These  are  hard  to 
obtain in small or medium-sized Member States alone. Also, it should become easier for 
firms  to  adapt  products  or  services  developed  in  one  Member  State  to  the  market  of 
another Member State. 

(c)  What are the benefits in replacing different national policies and rules with a 

more homogenous policy approach? 

A more harmonised way of data sharing across Member States and sectors would present 
benefits  for  industrial  sectors  and  players  across  the  value  chain,  irrespective  of  their 
relative  strength  or  presence  in  individual  Member  States.  Also,  only  a  concerted 
European approach can present an alternative to the current business models around data 
dominated by Big Tech platforms and cloud computing hyperscalers. The initiative will 
reduce  fragmentation  in  the  legal  and  policy  governance  frameworks  for  data  sharing 
(including  the  absence  of  them),  which  currently  stands  in  the  way  of  creating  the 
common  European  data  spaces  and  a  data  economy  that  is  transparent,  effective  and 
accountable.  In  the  different  consultation  actions  conducted  to  prepare  the  initiative, 
stakeholders  strongly  supported  EU  measures  to  create  a  harmonised  and  clear  set  of 
rules on data sharing, as presented in the Annex 2 of the Impact Assessment.  

(d) Do the benefits of EU-level action outweigh the loss of competence of the 

93 

 
Member States and the local and regional authorities (beyond the costs and 
benefits of acting at national, regional and local levels)? 

The  proposed  initiative does  not  lead  to  a loss  of  competence  in  the  Member  States.  It 
will  ‘Europeanise’  the  support  to  industry-driven  initiatives  such  as  Gaia-X  and  ensure 
that benefits of such initiatives accrue throughout the EU. The proposed initiative intends 
to clarify different rules and practices across the EU, which currently make it difficult for 
companies to develop pan-European data-based services and products. It allows Member 
States  and  sectors  to  complement  and  reinforce  the  data  economy  with  initiatives  that 
respond to their specificities.  

(e)  Will there be improved legal clarity for those having to implement the 

legislation? 

Yes,  the  proposed  instrument  will  ensure  that  future  national  and  sectoral  legislation 
flows from a number of horizontal principles that make data sharing fit for cross-sectoral 
and EU-wide exchanges.  

Furthermore,  it  will  bring  legal  clarity  on  what  can  be  done  with  certain  data  and  by 
whom.  Such  clarity  will  be  brought  on  three  levels:  First,  researchers  and  innovators 
seeking to use public sector data that can only be used under strict conditions will be able 
to  obtain  guidance  from  public  authorities  on  the  usability  and  conditions  of  data  use. 
Similarly, researchers and innovators that seek to use data voluntarily made available by 
individuals or companies for the public good will have access to schemes that give legal 
certainty  on  the  rights  to  use  such  data.  Finally,  for  B2B  and  C2B  transactions,  novel 
intermediaries will play  a functional  role in  ensuring compliance with  relevant  laws, in 
particular data protection and competition law. Regarding data altruism, an authorisation 
regime with mutual recognition among the Member States would ensure clarity through 
harmonisation  of  the  requirements  necessary  to  provide  these  kind  of  services.  Mutual 
recognition mechanisms will ensure that European data intermediaries can operate across 
EU countries. 

3.  Proportionality: How the EU should act 

3.1  Does the explanatory memorandum (and any impact assessment) 

accompanying the Commission’s proposal contain an adequate justification 
regarding the proportionality of the proposal and a statement allowing appraisal 
of the compliance of the proposal with the principle of proportionality? 

The  Explanatory  Memorandum  of  the  proposal,  as  well  as  the  Impact  Assessment 
(Chapter 3 – ‘Why should the EU act?’), contain dedicated sections on subsidiarity and 
added value, which also address the proportionality question. The sections of the Impact 

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Assessment that deal with the impacts of the policy options (Chapter 5) and the way the 
different actors are affected by the initiative (Annex 3) also demonstrate that the initiative 
is in line with the proportionality principle. 

The initiative is proportionate to the objectives sought. The Member States are the main 
stakeholders  that  will  be  required  by  the  legislation  to  put  in  place  the  necessary 
processes and structures  or bodies to address the problems. However, the initiative will 
leave  a  significant  amount  of  flexibility  for  implementation  at  national  and  sector-
specific levels, including through the European data spaces. Also, for B2B data sharing, 
the initiative essentially fosters the emergence of novel intermediaries.  

3.2 Based on the answers to the questions below and information available from any 

impact assessment, the explanatory memorandum or other sources, is the 
proposed action an appropriate way to achieve the intended objectives? 

The  proposed  legislation  will  induce  financial  and  administrative  costs  to  be  borne 
essentially by national authorities. However, the exploration of different options and their 
expected  costs  and  benefits  led  to  a  balanced  design  of  the  instrument.  It  will  leave 
enough flexibility for national  authorities to decide on the level  of financial investment 
and  possibilities  to  recover  such  costs  through  administrative  charges  or  to  take 
additional  measures,  while  offering  overall  coordination  at  EU  level  (e.g.  through  a 
European structure for coordinating the governance aspects of data sharing). 

(a)  Is the initiative limited to those aspects that Member States cannot achieve 

satisfactorily on their own, and where the Union can do better? 

The proposed initiative only focuses on areas where there is a demonstrable advantage in 
acting at EU level, and on problems identified and described in its Impact Assessment. It 
pursues  objectives  that  cannot  be  sufficiently  achieved  by  the  Member  States  acting 
alone, as described in section 2.3 above, due to the scale, speed and level of transnational 
coordination needed. 

(b) Is the form of Union action (choice of instrument) justified, as simple as possible, 
and coherent with the satisfactory achievement of, and ensuring compliance with 
the objectives pursued (e.g. choice between regulation, (framework) directive, 
recommendation, or alternative regulatory methods such as co-legislation, etc.)? 

In line with the Better Regulation Guidelines, a multi-criteria analysis carried out for the 
accompanying Impact Assessment has explored several options for each of the measures 
foreseen.  A  comparative  assessment  of  the  merits  of  each  option  also  included  its 
efficiency,  the  effectiveness,  the  coherence,  the  legal/political  feasibility  and  the 
proportionality  (Chapter  7).  The  option  of  coordination  at  EU  level  and  soft  measures 

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only  was  discarded  based  on  the  cost-benefit  analysis,  as  it  would  not  significantly 
change the situation as compared to the baseline scenario. Existing soft law measures in 
the  field  have  shown  that,  although  useful  in  providing  certain  clarity  and  giving  a 
general direction, they have been taken up with different intensities by actors in the data 
economy and Member States. 

The  choice  of  a  regulation  as  the  form  of  the  legal  instrument  is  justified  by  the 
predominance of elements  that should  not leave margins to implementation such as the 
authorisation of data altruism mechanism, labelling of novel data intermediaries and the 
setup  of  coordination  structures  at  European  level.  The  direct  applicability  of  the 
Regulation  would  avoid  an  implementation  period  for  the  Member  States,  so  that  the 
establishment of the common European data spaces could start very soon, in line with the 
EU  Recovery  Plan.  At  the  same  time,  the  provisions  of  the  Regulation  are  not  overly 
prescriptive and leave room for different levels of Member State action for elements that 
do  not  undermine  the  objectives  of  the  initiative,  in  particular  the  organisation  of  the 
mechanisms supporting the reuse of ‘sensitive’ public sector data.  

(c)  Does the Union action leave as much scope for national decision as possible 

while achieving satisfactorily the objectives set? (e.g. is it possible to limit the 
European action to minimum standards or use a less stringent policy instrument 
or approach?) 

The proposed legislation will require that national authorities put in place mechanisms to 
support  the  reuse  of  ‘sensitive’  public  sector  data,  in  order  to  address  the  problems 
presented  in  the  Impact  Assessment.  However,  the  initiative  will  leave  Member  States 
some flexibility for implementation of such mechanisms.  

(d) Does the initiative create financial or administrative cost for the Union, national 
governments, regional or local authorities, economic operators or citizens? Are 
these costs commensurate with the objective to be achieved? 

The  proposed  legislation  will  create  financial  and  administrative  costs,  mainly  for  the 
Union  (creating  a  European  structure  for  the  governance  aspects  of  data  sharing)  and 
national  governments  (putting  the  structures  and  processes  in  place  for  the  reuse  of 
certain public sector data, the authorisation of data altruism schemes and the certification 
of  data  intermediaries).  However,  the  legislation  will  allow  for  those  costs  to  be 
recovered  directly  through  administrative  charges  from  the  beneficiaries.  Discretion  on 
this  matter  is  left  to  Member  States  with  ceilings  set  in  order  to  avoid  that  charges 
become prohibitive.  

The  initiative  will  also  benefit  public  sector  bodies  and  allow  them  to  deliver  a  better 
public service around public databases, as they will benefit from technological and legal 
expertise – also through EU-level coordination. With more private sector data available 

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for reuse, the public sector will also make more use of such data. This will lead to more 
evidence-based policy- and decision-making and, ultimately, to better and more efficient 
public services.  

Economic operators will be the main beneficiaries of the initiative. The reuse of public 
sector data subject to rights of others will be subject to administrative charges. However, 
it is expected that operators will only reuse such data (and pay the charges) if on balance 
they expect a positive economic outcome. Similarly, they are expected to incur costs in 
relation to the authorisation of data altruism schemes, however the benefits are expected 
to  outweigh  such  costs.  Similarly,  the  certification  costs  for  novel  data  intermediaries 
will translate into service fees for business users. It is expected that also here, businesses 
will only make recourse to such intermediaries if the reduction in friction and transaction 
costs  outweigh  those  costs.  Finally,  through  enhancing  interoperability  at  the  technical 
level  and  making  available  generic  enabling  standards,  the  initiative  will  lower 
transaction  costs  of  data  sharing  and  facilitate  EU-wide  and  cross-sector  data  sharing. 
The prioritisation of standards will in particular benefit SMEs. 

(e)  While respecting the Union law, have special circumstances applying in 

individual Member States been taken into account? 

In general, there are no such special circumstances. The issues in relation to data sharing 
are very similar across all Member States. The initiative will leave flexibility to Member 
States  when  implementing  the  legislation,  also  in  order  to  allow  recently  established 
national  initiatives  on  enhanced  reuse  of  public  sector  data  to  continue  to  exist  in  its 
present form. It will also build on existing initiatives to support industry-led approaches 
to data sharing such as Franco-German Gaia-X, Dutch iShare or Finnish Sitra/IHAN.  

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ANNEX 6: GOVERNANCE FRAMEWORK IN THIRD 
COUNTRIES 

Over  the  last  few  years,  several  countries  around  the  world  have  put  in  place  mechanisms  to 
boost their data economies by enhancing trust in data sharing. Some of the elements foreseen in 
this  initiative  take  inspiration  from  experiences  in  other  countries  in  the  field  of  data 
intermediaries and certification schemes for data intermediaries. 

Japan: certification schemes for information banks  

The  Japanese  government  has  tried  to  increase  trust  towards  Japanese  ‘information  banks’  - 
systems  for  securely  accessing  personal  data  with  the  data  subject’s  consent183  -  by  releasing 
guidelines on the functions of certification schemes.  

Certification  is  based  on  government  guidelines184  compiled  in  June  2018  for  information 
banking  services  to  use  personal  information  while  protecting  the  privacy  of  individuals. 
Certification  remains  voluntary.  As  part  of  the  certification  process,  an  internal  auditing  body 
checks  what  is  done  with  the  personal  data.  Under  the  system,  information  banks  allow  client 
firms to tap into their databases only after obtaining consent from data-supplying individuals. In 
addition, the individuals can select the types of data to be used and grant specific firms access to 
their data.  

In July 2019, the Information Technology Federation of Japan certified FeliCa Pocket Marketing 
Inc. and Sumitomo Mitsui Trust Bank as information banks185.  

Endorsement  by  the  federation  is  not  compulsory  to  commercialise  personal  data,  but  it  does 
enhance the  credibility of companies as safe data providers. 

The Aeon Co. unit and the trust bank have started operations using personal data that they hold. 
FeliCa, which offers reward points and e-money unique to municipalities trying to reinvigorate 
their local economies, plans to provide its individual customers’ data to local retailers and small 
firms  to  help  them  set  up  business  strategies.  Sumitomo  Mitsui  Trust  aims  to  capitalise  on  its 
database in the healthcare field. 

Republic of Korea: data vouchers as intermediaries 

The  Korea  Data  Agency186  started  the  ‘data  voucher’  programme  to  promote  data-based 
innovative  businesses  and  the  surrounding  data  ecosystem.  Data  vouchers  can  be  used  to 
purchase  and  process  a  dataset  by  small  companies  that  have  difficulties  in  using  data,  and 
promoting the data and AI industries by expanding transactions of purchased and processed data. 

183 D. A. Consortium (2018). Pilot testing begins on an “information bank,” a new system for storing personal data, 
News Release. 
184 Ministry of Economy, Trade and Industry (2018). Release of the Guidelines of Certification Schemes Concerning 
Functions of Information Trust ver. 1.0. 
185 Jiji (2019). Japan grants certification for first time to 'information banks', The Japan Times. 
186 Korea Data Agency. 

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They play an intermediary role between the companies that hold the data and the companies that 
need the data. They are part of the Korean Government’s (Ministry of Science and ICT) initiative 
to  support  SMEs  in  accessing  data.  The  programme  is  popular,  with  on  average  1 000  data 
purchases and 640 data processing activities supported annually. Some 2 795 companies applied 
for the voucher programme last year187.  

On 11 May 2020, the South Korean Financial Services Commission (FSC) launched a financial 
data  exchange  programme  to  facilitate  data  transactions  between  buyers  and  sellers  from 
financial institutions, fintech firms, retailers and telcos. It will serve as a platform to match data 
providers  and  recipients  as  needed.  The  FSC  will  also  consider  introducing  a  data  voucher 
programme to help set appropriate data prices and support data purchases188. 

Australia: public sector designation of trusted data-sharing platform 

This example shows that governments can act as or create a trusted third party for data-sharing 
relationships. In 2017, the Australian government initiated the ‘Data Integration Partnership for 
Australia’  (DIPA)  as  an  investment  to  maximise  the  use  and  value  of  the  government’s  data 
assets189.  

DIPA is a whole-of-government collaboration including more than 20 Commonwealth agencies. 
It  improves  technical  data  infrastructure  and  data  integration  capabilities  across  the  Australian 
public service. The agencies make available important data assets such as in the health, education 
and social welfare sectors, allowing policymakers to gain insights that were not possible before. 
Sectoral  hubs  of  expertise,  independent  entities  that  are  funded  by  the  Commonwealth  and 
denominated Accredited Integrating Authorities, enable the integration of those longitudinal data 
assets. Individual privacy and the security of sensitive data are preserved, as DIPA only provides 
access  to  controlled,  de-identified,  and  confidentialised  data  for  policy  analysis  and  research 
purposes. 

187 Information provided by the EEAS Delegation to Seoul. 
188 Pulse (2020). Korea to launch financial data exchange in March. 
189 Australian Government, Department of the Prime Minister and Cabinet (2017). Data Integration Partnership for 
Australia. 

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