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Horizon 2020 Open Research Data Pilot, Jean-Claude Burgelman, DG RTD European Commission (8th OpenAIRE workshop)


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Presentation at the 8th OpenAIRE workshop - 4 April 2017

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Horizon 2020 Open Research Data Pilot, Jean-Claude Burgelman, DG RTD European Commission (8th OpenAIRE workshop)

  1. 1. From vision to action From open to FAIR data OpenAIRE workshop - Legal issues in Open Research Data April 4, Barcelona Jean-Claude Burgelman Daniel Spichtinger DG RTD European Commission
  2. 2. 10 years to become open FP7 OA Green or Gold+Green Pilot H2020 OA Green or Gold+Green obligation & ORD Pilot H2020 OA Green or Gold+Green obligation & ORD by default
  3. 3. "To increase the circulation and exploitation of knowledge, open access to scientific publications should be ensured. Furthermore, open access to research data resulting from publicly funded research under Horizon 2020 should be promoted, taking into account constraints pertaining to privacy, national security and intellectual property rights  Open access to scientific publications resulting from publicly funded research under Horizon 2020 shall be ensured [...].  Open access to research data resulting from publicly funded research under Horizon 2020 shall be promoted. [...]." Now: Regulation establishing H2020
  4. 4. ORD pilot extension: implementation Extension of limited Open Research Data (ORD) Pilot to all areas of Horizon 2020 whilst retaining its key characteristics: • Robust opt outs options for IPR, confidentiality/privacy and security reason as well as if OA runs against the main objective of the project • Targeted primarily towards data underlying publications (other data as specified in DMP) • a Data Management Plan (DMP) is obligatory for projects that do not opt-out • Costs for open access to research data fully eligible • Whether projects opt-out or not does not affect the evaluation General approach: as open as possible, as closed as needed
  5. 5. ORD Pilot: opt-out reasons among proposals Calls in core-areas:  65% stay in  Opt out 35% Other areas:  Voluntary opt in 14%
  6. 6. FAIR data management in Horizon 2020
  7. 7. Clarifying terminology… In the past our policy mainly addressed the 'accessibility' part of FAIR. • Started off with 'open access to research data' • Moved towards open (research) data with the ORD pilot (which also covered further aspects) • We are now seeing openness as one component of FAIR data and aim to address all of the FAIR aspects in Horizon 2020
  8. 8. A FAIR DMP has to adress that data are o 'Findable', i.e. discoverable with metadata, identifiable and locatable by means of a standard identification mechanism; o 'Accessible', i.e. always available and obtainable; o 'Interoperable', i.e. both syntactically parseable and semantically understandable, allowing data exchange and reuse between researchers, institutions, organisations or countries; and o 'Reusable', i.e. sufficiently described and shared with the least restrictive licences, allowing the widest reuse possible and the least cumbersome integration with other data sources.
  9. 9. FAIR Data Management DMP o Template DMP (Annex to Guidelines on FAIR Data Management)  Provided as a service, its use is currently optional o Standard DMP template is light and flexible  Set of questions + summary table o One DMP per project not per dataset  but mention if there are specific issues for a particular dataset) o DMP as a living document  Updated as part of periodic evaluation and/or at least at the end of the project for final reporting
  10. 10. Guidelines on FAIR Data Management • Available here on the Participant Portal!
  11. 11. Initial DMP experiences o Additional guidance on data management is needed for all groups of actors in research projects (researchers, peer reviewers and funder administrators ('project officers') including roles supporting researchers with data management tasks (data librarians or IT professionals working in data centres). o Aspects such as data preservation, IPR or standards are too often not well developed in the DMPs that have been submitted so far o Nevertheless research projects with excellent RDM performance are not rare. Some high quality DMPs from H2020 projects have already been published online, see o Source: REA 2016 assessment of H2020 Societal Challenge 6 projects.
  12. 12. FAIR data = the DNA of the EOSC
  13. 13. "Europe's final transition must be one from fragmented data sets to an integrated European Open Science Cloud. By 2020, we want all European researchers to be able to deposit, access and analyse European scientific data through a European Open Science Cloud." The Commissioner's vision on EOSC Speech by Commissioner Carlos Moedas in Amsterdam, NL: “Open science: share and succeed”, 4 April 2016 = EOSC is about (FAIR) research data
  14. 14. Part of DSM strategy (19 April 2016), strong political support. o 'Game-changing policy', a 'vision'. o Commissioners Moedas & Oettinger o Supported by Pres. Juncker, VP Ansip, Ch. Merkel, LUX Presidency, NL Presidency, 2 sets of COMPET Council Conclusions, EP Report on DSM Act, EESC, … Communication 2016/178 : European Cloud Initiative
  15. 15. Governance Develop roadmap for governance and financing Create a global level playing field for research data sharing Widen user-base to public services, Industry and EU-13 (Open data) Infrastructure Action Plan for scientific data Interoperability (e.g. FAIR) Connect key EU RI (e.g. ESFRIs) Consolidate / federate data-infrastructures Content (open data) Make Open research data default in H2020 Foster scientific data sharing in MS Hardware Infrastructure (CNECT) High-Performance Computing Big-data storage High-speed connectivity Policy actions foreseen in the COM 2016 FAIR FAIR
  16. 16. What is next?
  17. 17. o EOSC Summit will include inputs from OSPP, HLEG EOSC, FAIR expert group, and EOSC Pilot– 12 June 2017 o 'Declaration of intent' and 'Coalition of the willing' will include parts on FAIR data – end of summer 2017 o Interim governance board of EOSC will need to have FAIR people on board o Action Plan for FAIR data Interoperability - Summer 2018 The next practical steps
  18. 18. Our common challenge?
  19. 19. Get more of these • 1.3 Billion EUR per year • Benefits identified by the European Bioinformatics Institute to users and their funders just by making scientific information freely available to the global life science community • This is equivalent to more than 20 times the direct operational cost of the Institute Source: Charles Beagrie Ltd. For EMBL-EBI
  20. 20. Define data dynamically to fit open science: - data - methods - algorithms - SW in one word: all that is needed (FAIR) to make science reproducible
  21. 21. We should not give in on scientific and independent QUALITY
  22. 22. So lets move FAIR from concept to operational reality that serves OPEN SCIENCE (and lets do that asap)