F. A . I . R The opinions expressed in this presentation are my - - PowerPoint PPT Presentation
Barend Mons Biosemantics Group LUMC and EMC LS integrator Netherlands eScience Center Chair of DTL-data Head of ELIXIR node NL EC member of Open PHACTS Chair of High Level Expert Group EOSC F. A . I . R The opinions expressed in this
Biosemantics Group LUMC and EMC LS integrator Netherlands eScience Center Chair of DTL-data Head of ELIXIR node NL EC member of Open PHACTS Chair of High Level Expert Group EOSC
The opinions expressed in this presentation are my personal opinions and do not necessarily reflect the draft report of the High Level Expert Group for the European Open Science Cloud.
F.A.I.R
Cloud
https://ec.europa.eu/research/participants/portal/desktop/en/opportunities/h2020/topics/2054-infradev-04-2016.html
P r e s s C
f e r e n c e t
a y
First GO-FAIR lab in DTL (Health-RI) (2016-17) Stated aim to create GO-FAIR labs in other domains (2017-20) First (sister) GO-FAIR lab in SD (NIH/NHS/NSF) (2016) Second (sister) FOIL in Sao Paulo (Scielo)(2016) Third (sister) GO-FAIR lab in Arusha (2017) Stated aim to create GO- FAIR labs in other MS
(DE, SWE, UK, FI, CZ) 2017
Data loss is real and significant, while data growth is staggering
Nature news, 19 December 2013
capacity is doubling every 18 months and this rate is steady
doubling every 6-8 months
to continue for this decade
‘Oops, that link was the laptop of my PhD student’
Science1.0
90% of world's data generated over last two years
(http://www.sciencedaily.com/releases/2013/05/130522085217.htm)
US$28B/year (50%) spent on preclinical research is not reproducible
Freedman et al. http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002165
Only 12% of NIH funded datasets are demonstrably deposited in recognized repositories. So: approximately 200,000 to 235,000 invisible datasets cannot be effectively reused
Read et al. http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0132735
What about US? (as in us, MS)?
9
something to refer to http://www.nature.com/articles/sdata201618
Cloud
Cloud
Science (July-December 2014);
January 2016);
+ PC meetings, EAG meetings, e-IRG meetings, concertation meetings, info days, conferences, events, ...
Cloud
Trusted access to services & systems Re-use of shared data Across disciplinary, social and geographical borders Federated environment, across Member States
Cloud
Minimal international guidance and governance Maximum freedom to implement. Globally interoperable and accessible Globally embedded in a ‘Commons’
Cloud
Human expertise Core resources Standards, Best Practices Underpinning technical infrastructures A web of Data and Services
Cloud
Open Science Open Innovation Systematic and professional data management Long term data stewardship
Cloud
The majority of the challenges are social rather than technical Not just the size of data, but in particular complex data and analytics across domains. Shortage of data experts globally and in the European Union Archaic system of rewards and funding of science and innovation ‘Valley of death’ between (e-)infrastructure providers and domain specialists. Short funding cycles of core research infrastructures are not fit for purpose Fragmentation between domains causes repetitive and isolated solutions Distributed data sets increasingly do not move (size & privacy reasons) Centralised HPC is insufficient to support distributed meta-analysis and learning. However, the major components for a first generation EOSC are largely ‘there’ But ‘lost in fragmentation’ and spread over 28 Member States.
Cloud
Cloud
New modes [4] of scholarly communication Modern reward and recognition practices [3] need to support data sharing and re-use Innovative, fit for purpose funding schemes for sustainable underpinning infrastructures Core data experts [7] need to be trained and their career perspective significantly improved Cross-disciplinary collaboration-specific measures for review, funding and infrastructure Support for the transition from scientific insights towards societal innovation [8] The EOSC needs to be developed as an eco-system of infrastructures [2] Key Performance Indicators should be developed for the EOSC [2] The EOSC should enable automation of data processing: machine actionability [1]is key. FAIR principles [1, 6] (http://www.nature.com/articles/sdata201618)
Research Integrity [6]
Cloud
P1: Take immediate, affirmative action in close concert with Member States P2: Close discussions about the ‘perceived need’ P3: Build on existing capacity and expertise where possible P4: Frame the EOSC as supporting Internet based protocols & applications
Cloud
G1: Aim at the lightest possible, internationally effective governance G2: Guidance only where guidance is due G3: Define Rules of Engagement for formal participation in the EOSC G4: Federate the Gems across Member States
Cloud
I1: Turn this report into an EC approved document to guide EOSC initiative I2: Develop, Endorse and implement a Rules of Engagement scheme I3: Fund a concentrated effort to locate and develop Data Expertise in Europe I4: Install a highly innovative guided funding scheme for the preparatory phase I5: Make adequate data stewardship mandatory for all research proposals I6: Install an executive team to deal with international coherence of the EOSC I7: Install an executive team to deal with the preparatory phase of the EOSC
EOSC: 7 Immediate actions based on feed back
Cloud
II1: Publish the report (final draft available) II2: Develop, Pilot and implement a Rules of Engagement scheme II3: Detail the transition and sustainability model (and pilot it) II4: Train the data experts to bridge between ‘e-INFRA’ and ‘ESFRI’ II5: Assist data stewardship planning and exec. tools for all researchers II6 Develop the plan for what ‘minimal essential governance’ means in practice II7 Federate Interoperability standards and best practices (key RDA-role)
executive group(s) deliverables
II2 II2 II3 II3 II3 II3 II3 II3 II4 II4 II4 II5 II5 II5 II5 II6 II7 II7 RDA II7 FDG’s II3 Impactstory ORCID, FORCE 11
Approves DS Plan before submission of grant core resource EOSC
In DS plan
Review panel (DS = Tickbox) FUNDER Cloud Coin Authority Monthly invoice to Cloud Coin Authority? endorsed Repository Data Publisher HPA service
Applications & e-Infra providers Other Peoples’ Data
FAIR exchange
FAIR Research Data FAIR Workflows
FOILS