52022SC0432

(1)

‘The Commission shall adopt implementing acts laying down a list of specific high-value datasets belonging to the categories set out in Annex I and held by public sector bodies and public undertakings among the documents to which this Directive applies.’

(2)

https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=uriserv:OJ.L_.2019.172.01.0056.01.ENG

(3)

More information about the Open Data Directive: https://ec.europa.eu/digital-single-market/en/european-legislation-reuse-public-sector-information

(4)

The implementing act must be adopted in accordance with the examination procedure provided in Article 5 of Regulation (EU) No 182/2011.

(5)

The European Data Portal classifies re-users into broad groups of data aggregators, developers and enrichers, see: European Data Portal, Analytical Report 9: The Economic Benefits of Open Data, 2017.

(6)

https://ec.europa.eu/digital-single-market/en/open-data

(7)

The same approach has been adopted in the US with regard to data held by the federal administration (including high value weather or satellite data) which has also been reused by EU companies.

(8)

E.g. Google initially acquired the necessary data for its Google Maps service from Navteq (now Here) and is said to be spending over $1 billion a year on generating accurate maps and routing data (see: https://tech.eu/features/4947/nokia-here-bidding-war-location-based-services/ ).

(9)

Modifying the original data to make it suitable for a given use case. Open Data may reduce this burden by promoting common standards, formats and licences.

(10)

Institute for Public Policy Research, ‘Creating a Digital Commons’, 2020, https://www.ippr.org/research/publications/creating-a-digital-commons

(11)

https://ec.europa.eu/info/strategy/priorities-2019-2024/europe-fit-digital-age/european-data-strategy_en

(12)

Commission Communication ‘A European Strategy for Data’ of 19 February 2020, COM/2020/66 final.

(13)

https://ec.europa.eu/research/openscience/index.cfm

(14)

Shaping Europe's Digital Future, 9 June 2020.

(15)

The Common European Data Spaces are a concept introduced by the Commission’s 2020 Data Strategy. They can be defined as a mix of data infrastructure, data governance rules and community building whose aim is to enhance data sharing within economic sectors in the EU. The governance layer of the Data Spaces will benefit from legislation currently under preparation (Regulation on European Data Governance) while financial support to the creation of data spaces in e.g. mobility, health or agricultural sectors will be provided by the Digital Europe Programme.

(16)

Commission Communication ‘Europe’s moment: Repair and Prepare for the Next Generation’ of 27 May 2020, SWD(2020)98final.

(17)

COM(2019) 640 final.

(18)

Three out of six domains indicated in Annex I of the Open Data Directive.

(19)

https://inspire.ec.europa.eu/sites/default/files/inspire2020_greendataspace_green_deal_data_space.pdf

(20)

https://ec.europa.eu/digital-single-market/en/destination-earth-destine

(21)

EU-27 general government expenditure stood at 46.7 % of EU GDP in 2018.

(22)

https://www.europeandataportal.eu/en/highlights/ai-and-open-data-crucial-combination

(23)

https://www.oecd.org/going-digital/enhancing-access-to-and-sharing-of-data-276aaca8-en.htm

(24)

https://op.europa.eu/en/publication-detail/-/publication/45328d2e-4834-11e8-be1d-01aa75ed71a1/language-en

(25)

https://www.europeandataportal.eu/sites/default/files/the-economic-impact-of-open-data.pdf

(26)

The Economic Impact of Open Data, 2020, European Data Portal, www.europeandataportal.eu

(27)

Open data employees are people in both the public and the private sector that are generating, providing, aggregating, re-using, and enriching open data.

(28)

COM(2020) 103 final.

(29)

European Commission (2020a). The European data market monitoring tool, D2.9 Final Study Report.

(30)

European Commission, Entrepreneurship and Small and medium-sized enterprises (SMEs) .

(31)

https://www.europeandataportal.eu/en/impact-studies/use-cases

(32)

Summary report of the public consultation on the European strategy for data, 24 July 2020, https://ec.europa.eu/digital-single-market/en/news/summary-report-public-consultation-european-strategy-data

(33)

See Article 1(1): this Directive establishes a set of minimum rules governing the re-use and the practical arrangements for facilitating the re-use of (…).

(34)

Public sector bodies include the state, regional or local authorities and bodies governed by public law whereas public undertakings can be characterised as publicly controlled companies providing services in utility sectors (legal definitions in Art. 2 of the Directive).

(35)

Examples of such data may include sensitive personal data, national security data, confidential statistical data, etc.

(36)

COM/2020/767 final.

(37)

SWD(2018) 145.

(38)

Full list of INSPIRE Themes: https://inspire.ec.europa.eu/Themes/Data%20Specifications/2892

(39)

European Commission (2020, forthcoming). Support Study to this Impact Assessment, SMART 2019/0025, prepared by Deloitte.

(40)

The expected impact of ITS Directive and related delegated acts on the availability of data in the transport field should exceed that of a hypothetical inclusion in the list of High Value Datasets because the application of ITS Directive 2010/40/EU is not limited to data held by public sector bodies and public undertakings.

(41)

Business to Government.

(42)

https://apifriends.com/digital-strategy/unleash-your-ai-with-apis/

(43)

The Economic Impact of Open Data, European Data Portal, 2020.

(44)

Agriculture, Financial services and insurance, Health; Education, Wholesale retail and trade, Real estate activities.

(45)

Selected examples of data re-use across all sectors are showcased by the European Data Portal: https://www.europeandataportal.eu/en/impact-studies/use-cases

(46)

See: Annex 2.

(47)

SWD(2018) 145.

(48)

SWD(2018) 127 final.

(49)

In addition to legislation, the EU’s Open Data Policy addresses the full range of problems in PSI re-use across Europe. These touch upon the issues of data skills, digitisation of the public sector or collaboration between the public and private sectors.

(50)

Evaluation Report SWD (2018) 145 observed that ‘the improvements in the reusability scores are driven by increased adoption of Application Programming Interfaces (APIs) and the improving availability of machine-readable datasets’.

(51)

https://ec.europa.eu/digital-single-market/en/news/summary-report-public-consultation-european-strategy-data

(52)

https://www.mulesoft.com/press-center/customer-experience-research-2019

(53)

Application Programming Interfaces in Governments: Why, What and How, JRC research for policy report, 2020.

(54)

https://www.data.gov/developers/blog/primer-machine-readability-online-documents-and-data

(55)

Barriers in working with Open Data, EDP analytical report No 5, 2020.

(56)

This can be referred to as ‘data source interoperability’, see: Publishing Data for Maximum Reuse, Pieter Colpaert, 2018, https://phd.pietercolpaert.be/#toc

(57)

Combination of several datasets within a larger dataset.

(58)

Annex 2 of this Impact Assessment.

(59)

https://ec.europa.eu/digital-single-market/en/news/consultation-guidelines-recommended-standard-licences-datasets-and-charging-re-use-public

(60)

Commission notice — Guidelines on recommended standard licences, datasets and charging for the reuse of documents, OJ C 240, 24.7.2014.

(61)

European Commission (2020, forthcoming). Support Study to this Impact Assessment, SMART 2019/0025, prepared by Deloitte.

(62)

https://www.istat.it/it/note-legali

(63)

https://data.norge.no/nlod/en/2.0/ or https://www.etalab.gouv.fr/licence-ouverte-open-licence

(64)

http://data.riksdagen.se/In-English/

(65)

As suggested by Recital 16 of the Open Data Directive.

(66)

See: Socio-legal Barriers to Data Reuse, National Library of Medicine, 2019, https://nlmdirector.nlm.nih.gov/2019/06/11/socio-legal-barriers-to-data-reuse or LAPSI License Interoperability Report, 2013, https://ec.europa.eu/digital-single-market/en/news/lapsi-license-interoperability-report

(67)

Not least because the adoption of CC or CC-compatible licences will allow for the seamless merging of European Commission’s and Member States’ data into EU wide data services and products.

(68)

The practice of charging is often linked to the funding mechanism in which public sector bodies are not fully financed by the budget.

(69)

The Directive even allows for specific HVDs held by public undertaking sto be charged for in caes where their free availability would lead to a distortion of competition in the relevant markets.

(70)

The recast Directive makes it clear that any application of charges beyond marginal costs can only happen in exceptional cases (Recital 36) and under strict transparency requirements.

(71)

As evidenced in the Support Study.

(72)

E.g. company data in Belgium: https://economie.fgov.be/en/themes/enterprises/crossroads-bank-enterprises/services-everyone/cbe-file-containing-all-public

(73)

E.g. weather data in Croatia: https://meteo.hr/proizvodi_e.php?section=proizvodi_usluge&param=services

(74)

E.g. cadastral data of the Austrian Surveying Service (BEV): https://www.bev.gv.at/portal/page?_pageid=713,3175363&_dad=portal&_schema=PORTAL#Anchor-37650

(75)

According to the evaluation report SWD 2018 145: ‘In the studies where specific types of data were analysed (e.g. meteorological, geographic and hydrographical data), it emerged that there is high price elasticity in these domains, that is to say that re-users are very sensitive and reactive to price’.

(76)

http://sdfe.dk/media/2917052/20170317-the-impact-of-the-open-geographical-data-management-summary-version-13-pwc-qrvkvdr.pdf

(77)

https://www.gov.uk/government/publications/companies-house-data-valuing-the-user-benefits

(78)

See for instance, The cost of Geospatial Open Data, Peter A. Johnson, Renee Sieber, Teresa Scassa, Monica Stephens, Pamela Robinson, Transaction in GIS, Wiley, January 2017, http://onlinelibrary.wiley.com/doi/10.1111/tgis.12283/full or See case studies on the Norwegian METNO case (meteorological data) and case study on the Dutch KNMI case (meteorological data), Study on the Pricing of Public Sector Information – POPSI Study, October 2011, Deloitte, https://ec.europa.eu/digital-single-market/en/news/pricing-public-sector-information-study-popsis-models-supply-and-charging-public-sector

(79)

Stakeholders interviews, European Commission (2020, forthcoming). Support Study to this Impact Assessment, SMART 2019/0025, prepared by Deloitte.

(80)

https://www.insee.fr/fr/statistiques/4238594?sommaire=4238635

(81)

https://opendataincubator.eu/wp-content/uploads/2016/01/ODINE-Final-report-by-IDC.pdf

(82)

About GMES and Data: Geese and Golden Eggs, G Sawyer, M de Vries, 2012, Figure 3-4 ‘Overview of increases in demand following lowered PSI reuse charges’.

(83)

The latest EDP’s Open Data Maturity Report deplores the persisting disparities among the EU Member States and sees the High Value Datasets as an important opportunity for consolidating Europe’s open data ecosystem.

(84)

Trojette Report sur l'ouverture des données, 2013, Cour des Comptes, Chapter 4.1 – ‘La fin du monopole public dans l’élaboration de certaines données de référence’.

(85)

Denmark, France and the Czech Republic have pioneered the approach of defining ‘reference data’ for fully open re-use.

(86)

COM(2020) 66 final.

(87)

Dates referring to the initial adoption of the Directive 2003/98/EU and its subsequent revisions.

(88)

https://ec.europa.eu/digital-single-market/en/news/synopsis-report-public-consultation-revision-directive-reuse-public-sector-information

(89)

SWD(2018) 145.

(90)

Summary report of the public consultation on the European strategy for data, 24 July 2020, https://ec.europa.eu/digital-single-market/en/news/summary-report-public-consultation-european-strategy-data

(91)

Report on high value datasets from European Institutions, PWC Services 2014.

(92)

Technical Annex to G8 Open Data Charter, Action 2: Release of High Value Data, https://www.gov.uk/government/publications/open-data-charter

(93)

Article 14(2) mentions four separate criteria that need to be met for data to qualify as HVDs.

(94)

https://ec.europa.eu/digital-single-market/en/news/synopsis-report-public-consultation-revision-directive-reuse-public-sector-information

(95)

SWD(2018) 127 final.

(96)

See: PASC [Public Administration Select Committee] (2014) Public Administration Committee - Tenth

Report. Statistics and Open Data: Harvesting unused knowledge, empowering citizens and improving public services http://www.publications.parliament.uk/pa/cm201314/cmselect/cmpubadm/564/56402.htm

(97)

For instance, Google has spent 29 billion dollars on its top 10 acquisitions, which include huge datasets held by Youtube, Waze or FitBit (https://www.cbinsights.com/research/google-biggest-acquisitions-infographic/)

(98)

One third of the start-ups involved in the ODINE incubator stated that not only their business would be negatively affected but that they would simply not exist without public data being open and free. See: Impact Assessment of ODINE programme. 2017, IDC.

(99)

See: position paper on AI and data by France Digitale , a grouping of 13420 start-ups, https://francedigitale.org/combat/digitaleu/

(100)

The charging exception may however become relevant in a case of future extension of the thematic range of the High Value Datasets via a delegated act, as foreseen in the Open Data Directive.

(101)

Such as Creative Commons BY or Creative Commons 0, which allow for an unrestricted re-use, including for commercial purposes.

(102)

https://ec.europa.eu/jrc/en/news/commission-makes-it-even-easier-citizens-reuse-all-information-it-publishes-online

(103)

https://ec.europa.eu/eurostat/web/ess/about-us

(104)

Apart from the case of financial reports whose formats are defined by EU ESEF Regulation 2019/815.

(105)

For the sake of completeness, it should also be noted that the process for the adoption of the Act has also been pre-defined. The proposed list of high value datasets will have to be accepted by the Member States, by way of an examination procedure.

(106)

The Evaluation Report of the PSI Directive (SWD(2018) 145 final) when discussing its effectiveness, noted already that ‘an additional area of improvement would be to provide high value datasets published with common more harmonised data models in the same level of granularity or scale in each Member State’.

(107)

Article 14(1) of the Open Data Directive.

(108)

As shown in the annual Open Data Maturity Studies conducted by the European Data Portal.

(109)

Data landscape, The European Data Market Monitoring Tool see: http://datalandscape.eu/european-data-market-monitoring-tool-2018

(110)

The room for manoeuvre is quite restricted for the ‘mobility’ domain. Article 14(2) of the Directive calls on the Commission to ensure complementarity with existing legal acts, such as Directive 2010/40/EU ITS Directive). This is due to the fact that the said Directive (accompanied by a series of delegated regulations) mandates the opening up of a wide scope of static and dynamic mobility data held by both public and private entities – thus exceeding the minimum level of harmonisation in the Open Data Directive. Accordingly, the Impact Assessment takes into account the data which are not in scope of the ITS Directive and its delegated regulations.

(111)

The Directive gives the possibility to the Commission to also consider data held by public undertakings in several utility sectors for the purpose of identifying High Value Datasets. Given the thematic scope of the exercise, the intended objectives, the expected costs involved and the need to respect relevant sectoral law (notably the ITS Directive that covers also public undertakings) as well as clearly negative feedback from the public undertakings in the course of stakeholder consultations, no objective reasons were found to include public undertakings’ data in the scope at this stage.

(112)

See: Annex II.

(113)

For full explanation of the methodology, see Annex 4.

(114)

It should be noted that the intensitites of intervention are designed and then assessed independently and separately theme by theme. It is only after the impacts of the policy options in each theme are assessed that the choice of the most appropriate policy package for the entire instrument can be made in Chapter 8.

(115)

Maps are not included as self standing datasets, since they can be obtained by layering multiple High Value datasets (e.g. Administrative Units + Place Names + Road and Rail transport networks).

(116)

List of data sets developed by INSPIRE Maintenance and Implementation Group (MIG) and related to environmental reporting which should be made available by Member States through the European Spatial Data Infrastructure in a stepwise manner. Full description available here: https://webgate.ec.europa.eu/fpfis/wikis/display/InspireMIG/Action+2016.5%3A+Priority+list+of+datasets+for+e-Reporting

(117)

See: European Data Monitor tool for the differences in the growth of the data market depending on a range of factors such as data availability. http://datalandscape.eu/european-data-market-monitoring-tool

(118)

Commission Communication ‘Europe’s moment – Repair and Prepare for the Next Generation’’, COM(2020) 456 final.

(119)

https://ec.europa.eu/info/business-economy-euro/egovernment_en

(120)

https://e-justice.europa.eu/home.do?action=home

(121)

Annex to the Commission Communication ‘A European Strategy for Data, COM/2020/66 final.

(122)

SME Strategy for a sustainable and digital Europe, COM(2020) 103 final.

(123)

Data landscape, The European Data Market Monitoring Tool see: http://datalandscape.eu/european-data-market-monitoring-tool-2018 , N B the monitoring tool uses the “Value of the Data Market” as a proxy for the direct economic value.

(124)

This value already takes into account a correction linked to the Covid-19 impact on the overall EU economy.

(125)

The European Data Market Monitoring Tool (see: footnote 96 above).

(126)

Economic Impact of Open Data, European Data Portal, 2020.

(127)

Study to support the review of Directive 2003/98/EC on the re-use of public sector information, Deloitte, 2018.

(128)

http://www.asedie.es/assets/asedie---infomediary-sector-report-2020.pdf

(129)

Study on emerging issues of data ownership, interoperability, (re-)usability and access to data, and liability, Deloitte 2017.

(130)

Report on the implementation of the INSPIRE Directive, SWD(2016) 243 final/2.

(131)

Creative Commons 0 (public domain dedication) and Creative Commons BY (attribution) are the most commonly used open licences worldwide, including for content held by the public sector.

(132)

As voiced by the re-users of company data and business associations in the IIA consultation and during workshops.

(133)

https://www.geospatialworld.net/article/economic-value-of-geospatial-data-the-great-enabler/

(134)

For examples, see: https://www.gsa.europa.eu/GNSS4Crisis

(135)

Such as Finland, Denmark, Ireland (EU) or Norway (EEA).

(136)

https://www.copernicus.eu/en/services

(137)

European Commission (2020, forthcoming). Support Study to this Impact Assessment, SMART 2019/0025, prepared by Deloitte.

(138)

Ibid.

(139)

Ibid.

(140)

Does Marginal Cost Pricing of Public Sector Information Spur Firms Growth?, Heli Koski, The Research Institute of the Finnish Economy, 2011.

(141)

Ibid.

(142)

Barbara Huber, Alexander Kurnikowski, Stephanie Müller, Stefan Pozar, “The Economic and Political Dimension of Open Government Data in Austria,” Institute for Entrepreneurship & Innovation, WU Vienna University of Economics and Business, Spring 2013.

(143)

European Commission (2020, forthcoming). Support Study to this Impact Assessment, SMART 2019/0025, prepared by Deloitte.

(144)

E.g. in the framework of the International Open Data Charter or Open Government Partnership.

(145)

Pereira, G.V., Macadar, M.A., Luciano, E.M. et al. Delivering public value through open government data initiatives in a Smart City context. Inf Syst Front 19, 213–229 (2017).

(146)

Some countries have established conditionalities for companies receiving funding under COVID 19 specific recovery plan, including environmental actions and CO2 emission reduction.

(147)

https://blogs.worldbank.org/eastasiapacific/role-geospatial-information-confronting-covid-19-learning-korea

(148)

A wide range of economic benefits have already been attributed to an open re-use of data produced by the US National Oceanic and Atmospheric Administration (NOAA).https://www.oecd.org/sti/ieconomy/40066192.pdf

(149)

https://eponline.com/articles/2020/03/25/using-big-data-technology-for-environmental-protection.aspx

(150)

https://www.wri.org/aqueduct

(151)

https://data.jrc.ec.europa.eu/collection/floods

(152)

https://www.eea.europa.eu/archived/archived-content-water-topic/water-resources/floods

(153)

https://www.modstroem.dk/energiberegner/

(154)

www.greenhome,nl

(155)

www.sunenergia.com.en

(156)

European Data Portal, the Economic Impact of Open Data, 2020.

(157)

http://www.rbwm.gov.uk/web/news_10913_energy_reduction_sustainability_strategy.htm

(158)

UNECE, Recommendations for Promoting, Measuring and Communicating the Value of Official Statistics (New York and Geneva: United Nations, 2018).

(159)

As example: https://www.transparency.org/en/publications/open-data-and-the-fight-against-corruption-in-germany

(160)

https://www.researchgate.net/publication/323940830_Big_Data_for_Sustainable_Urban_Transport

(161)

https://www.tandfonline.com/doi/full/10.1080/09654313.2017.1294149

(162)

https://www.7wdata.be/open-data-institute/how-open-data-can-help-save-lives/

(163)

European Data Portal, the Economic Impact of Open Data, 2020.

(164)

European Commission (2020, forthcoming). Support Study to this Impact Assessment, SMART 2019/0025, prepared by Deloitte.

(165)

Weighted coefficient for the EU27 ICT-service sector, representing the ratio of enterprises per GVA/GDP. For the weighted coefficient it was assumed that an average firm in the EU27 ICT-sector has 6 employees, respectively a statistical ratio of ca. 2 enterprises per 1 million € GVA.

(166)

https://www.sme10x.com/10x-industry/how-open-data-can-help-startups-succeed

(167)

Assessment of the impact of the ODINE data incubator project, 2017.

(168)

A telling example is OpenDataSoft, a French open data start-up that since its creation has received multimillion funding from private investors and offers services to over 280 clients worldwide.

(169)

As testified by the improving DESI indicators: https://ec.europa.eu/digital-single-market/en/desi.

(170)

For instance, the Impact Assessment Support Study of 2018 associated the lowest costs for the public sector with the policy option of highest intensity (which was not retained).

(171)

Impact Assessment Support Study, Deloitte, SMART 2017/0061, figure 42.

(172)

Examples of costs reductions due to increased efficiency have been discussed e.g. in the following study: https://www.w3.org/2013/share-psi/wiki/images/6/67/Impact_of_Open_Data_in_the_Public_Sector_Koski_2015.pdf

(173)

COM(2017) 134 final. Even if not specific for APIs, the EIF provides public administrations with a set of recommendations to improve governance of their interoperability activities, establish cross-organisational relationships and streamline processes supporting end-to-end digital services.

(174)

https://www.fiware.org/about-us/

(175)

Study to support the review of Directive 2003/98/EC on the re-use of public sector information, Deloitte, 2018, page 409.

(176)

Many of these costs are however not specific to the High Value Datasets but rather to any type of online dissemination of data by the company registers, already happening.

(177)

European Commission (2020, forthcoming). Support Study to this Impact Assessment, SMART 2019/0025, prepared by Deloitte.

(178)

Ibid, Section 3.1.1.

(179)

Ibid.

(180)

50 replies, gathered between 28 July 2020 and 25 August 2020.

(181)

European Commission (2020, forthcoming). Support Study to this Impact Assessment, SMART 2019/0025, prepared by Deloitte.

(182)

See: Annex 4.

(183)

The Directive is ‘without prejudice’ to EU and related national data protection provisions.

(184)

European Commission (2020, forthcoming). Support Study to this Impact Assessment, SMART 2019/0025, prepared by Deloitte.

(185)

https://opendataimpactmap.org/regions

(186)

These limitations stem from the requirements of article 14 of the Open Data Directive.

(187)

Given the adoption date and the expected timeline of the actual applicability of several provisions of the implementing act (e.g. on charging or APIs), impacts are measured as of 2024.

(188)

http://www.thegovlab.org/open-data-demand.html

(189)

https://www.europeandataportal.eu/en/impact-studies/open-data-maturity

(190)

https://ec.europa.eu/digital-single-market/en/news/public-sector-information-group-main-page

(191)

http://psialliance.info/

(192)

This is the maximum delay given by the OD Directive for the MS to discontinue all charges on HVDs.

(193)

https://op.europa.eu/en/publication-detail/-/publication/45328d2e-4834-11e8-be1d-01aa75ed71a1

(194)

https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/12271-European-Strategy-for-data/public-consultation

(195)

https://www.europeandataportal.eu/en/dashboard/2019

(196)

CapGemini Invent, 2020, https://www.europeandataportal.eu/en/impact-studies/open-data-impact

(197)

for which the datasets are relevant, in particular SMEs.

(198)

Committee on open data and the re-use of public sector information, Committee code: C51600.

(199)

The meeting reports are available in the Commission’s Comitology Register: https://ec.europa.eu/transparency/regcomitology/index.cfm

(200)

The meeting minutes are available on a dedicated Europa.eu page: https://ec.europa.eu/digital-single-market/en/news/public-sector-information-group-main-page

(201)

Outcome of the online consultation on the European strategy for data.

(202)

https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/12111-Implementing-act-on-a-list-of-High-Value-Datasets

(203)

https://www.kas.de/documents/259586/0/Summary+-+Final+Remarks.pdf

(204)

https://www.europeandataportal.eu/en/news/webinar-economic-impact-open-data-europe

(205)

https://www.europeandataportal.eu/en/highlights/inspire-2020-european-data-portal-web-session-high-value-datasets

(206)

https://www.europeandataportal.eu/en/news/european-data-portal-and-high-value-datasets

(207)

https://ec.europa.eu/digital-single-market/en/news/report-european-commissions-workshops-common-european-data-spaces

(208)

PLAN/2020/7446

(209)

Principles along which data should be findable, accessible, interoperable and reusable.

(210)

Documents provided by the members of the PSI Group of national experts.

(211)

See Official Journal of the European Union (2019) Directive (EU) 2019/1024 of the European Parliament and of the Council of 20 June 2019 on open data and the re-use of public sector information (recast), https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:32019L1024&from=EN

(212)

(213)

http://ec.europa.eu/smart-regulation/guidelines/toc_guide_en.htm

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http://ec.europa.eu/smart-regulation/guidelines/toc_tool_en.htm

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https://ec.europa.eu/info/sites/info/files/file_import/better-regulation-toolbox-63_en_0.pdf

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Due to a lack of data, costs and benefits have been quantified only to the extent possible. Costs and benefits have been assessed in a qualitative manner whenever quantitative data is lacking.

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http://ec.europa.eu/smart-regulation/guidelines/toc_guide_en.htm

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See EC (2020), The economic impact of open data, pp. 18ff.

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Vickery 2011, Review of Recent Studies on PSI Re-Use and Relate Market Developments.

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Data landscape, The European Data Market Monitoring Tool see: http://datalandscape.eu/european-data-market-monitoring-tool-2018

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See e.g. European Commission, European Data Portal (2020), The Economic Impact of Open Data: Opportunities for value creation in Europe. Study conducted by Capgemini.

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With regard to the indirect effects included however, the employment coefficient of the ICT sector can only serve as a proxy.

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Eurostat 2020, Statistics Explained, Glossary: government revenue and expenditure. https://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:Government_revenue_and_expenditure

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It must be noted, however, that this total governmental revenue includes – as defined in the European System of Accounts 2010 – also the market output, output for own final use and payments for non-market production. As this definition is a rather broad concept and as the macroeconomic effect of the introduction of the Policy Packages depends on a lot yet unknown factors, market output, output for own final use and payments for non-market production cannot be predicted as precisely as the other variables of governmental revenues. Excluding the categories mentioned, the adjusted governmental revenues would lower to approximately 38% of GDP according to OECD estimates. OECD, 2020, Comparative Statistics: Governmental Revenue. https://stats.oecd.org/Index.aspx?DataSetCode=REV

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https://www.smartdatacollective.com/big-data-and-the-sme-prepare-to-succeed/

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https://www.forbes.com/sites/louiscolumbus/2017/10/08/small-businesses-are-the-real-mvps-of-analytics-and-bi-growth/#4af291526ca4

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Deloitte (2018), Study supporting the review of the PSI Directive.

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https://www.smartdatacollective.com/big-data-and-the-sme-prepare-to-succeed/

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Deloitte (2018). Realising the economic potential of machine-generated, non-personal data in the EU, Report for Vodafone Group.

OECD (2019). Enhancing Access to and Sharing of Data: Reconciling Risks and Benefits for Data Re-use across Societies, OECD Publishing, Paris.

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European Commission (2017). Synopsis report consultation on the ‘building a European data economy’ initiative.

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Soroka, A. et al. (2017) ‘Big Data Driven Customer Insights for SMEs in Redistributed Manufacturing’, Procedia CIRP, 63(1), pp. 692–697.

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Provost, F. and Fawcett, T. (2013) ‘Data Science and its Relationship to Big Data and Data-Driven Decision Making’, Big Data, 1(1), pp. 51–59.

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COM(2020) 103 final. An SME Strategy for a sustainable and digital Europe.

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Britzelmaier-B, Sterk-M, Graue-C: Big data in SMEs – findings of an empirical study. (2020) Global Business and Economics Review 22(1/2):115.

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Jin, X. et al. (2015) ‘Significance and Challenges of Big Data Research’, Big Data Research, 2(2), pp. 59–64.

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Boyd, D. and Crawford, K. (2012) ‘Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon’, Information Communication and Society, 15(5), pp. 662–679.

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Depeige, A. and Doyencourt, D. (2015) ‘Actionable Knowledge As A Service (AKAAS): Leveraging big data analytics in cloud computing environments’, Journal of Big Data, 2(1), pp. 1–16.

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Stakeholders interviews.

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Valuing the user benefits of companies house data, Report 2: Direct Users, BEIS Research Paper Number 2019/015.

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Impact Assessment study on the list of high-value datasets to be made available by the Member States under the PSI Directive, 2020.

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Jaana Mäkelä, Paula Ahonen-Rainio and Kirsi Virrantaus “Effects of open topographic datain Finland, A user study one and half years after the opening” Dept of Real Estate, Planning and Geoinformatics, Aalto School of Engineering, 2014.

(242)

Impact Assessment study on the list of high-value datasets to be made available by the Member States under the PSI Directive, 2020.

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http://www.qmap.it/index.php/en/products/

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https://sharedmobility.ai/2020/06/why-long-term-meteorological-data-is-a-key-factor-for-urban-mobility-services/

(245)

https://www.europeandataportal.eu/sites/default/files/use-cases/use_case_spain_-_dato_capital.pdf

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