Evaluating FAIR maturity through a scalable, automated, community-governed framework

Mark D. Wilkinson, Michel Dumontier, Susanna Assunta Sansone, Luiz Olavo Bonino da Silva Santos, Mario Prieto, Dominique Batista, Peter McQuilton, Tobias Kuhn, Philippe Rocca-Serra, Mercѐ Crosas, Erik Schultes

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Transparent evaluations of FAIRness are increasingly required by a wide range of stakeholders, from scientists to publishers, funding agencies and policy makers. We propose a scalable, automatable framework to evaluate digital resources that encompasses measurable indicators, open source tools, and participation guidelines, which come together to accommodate domain relevant community-defined FAIR assessments. The components of the framework are: (1) Maturity Indicators - community-authored specifications that delimit a specific automatically-measurable FAIR behavior; (2) Compliance Tests - small Web apps that test digital resources against individual Maturity Indicators; and (3) the Evaluator, a Web application that registers, assembles, and applies community-relevant sets of Compliance Tests against a digital resource, and provides a detailed report about what a machine "sees" when it visits that resource. We discuss the technical and social considerations of FAIR assessments, and how this translates to our community-driven infrastructure. We then illustrate how the output of the Evaluator tool can serve as a roadmap to assist data stewards to incrementally and realistically improve the FAIRness of their resources.

Original languageEnglish
Article number174
Pages (from-to)1-12
Number of pages12
JournalScientific Data
Volume6
Issue number1
DOIs
Publication statusPublished - 20 Sept 2019

Funding

M.D.W. is funded by the Isaac Peral/Marie Curie cofund with the Universidad Politécnica de Madrid, Ministerio de Economía y Competitividad grant number TIN2014-55993-RM, and the European Joint Programme on Rare Diseases (H2020-EU 825575). Throughout phase 1 and 2 of the work, S.A.-S., P.MQ., D.M. and PRS have been funded by grants awarded to S.A.-S. from the UK BBSRC and Research Councils (BB/L024101/1; BB/L005069/1), EU (H2020-EU 634107; H2020-EU 654241; H2020-EU 676559; H2020-EU 824087), IMI (116060; 802750), NIH (U54 AI117925; 1U24AI117966-01; 1OT3OD025459-01; 1OT3OD025467-01, 1OT3OD025462-01), and from the Wellcome Trust (212930/Z/18/Z; 208381/A/17/Z). MD is supported by grants from NWO (400.17.605; 628.011.011), NIH (3OT3TR002027-01S1; 1OT3OD025467-01; 1OT3OD025464-01), and ELIXIR, the research infrastructure for life-science data. MP was supported by the UPM Isaac Peral/Marie Curie cofund, and funding from the Dutch Techcenter for Life Sciences DP. LOBS and ES are supported by the Dutch Ministry of Education, Culture and Science (Ministerie van Onderwijs, Cultuur en Wetenschap), Netherlands Organisation for Scientific Research (Nederlandse Organisatie voor Wetenschappelijk Onderzoek), and the Dutch TechCenter for Life Sciences. We thank the NBDC/DBCLS BioHackathon series where many of these MIs and their tests were designed, and we particularly wish to acknowledge the participation of the Dataverse team, especially Julian Gautier and Derek Murphy, at IQSS, Harvard, in addition to Todd Vision from Data Dryad.

FundersFunder number
Cultuur en Wetenschap
Dutch Techcenter for Life Sciences
Dutch Techcenter for Life Sciences DP
ELIXIR
Ministerie Van Onderwijs
National Institutes of Health1OT3OD025462-01, U54 AI117925, 1OT3OD025459-01, 1OT3OD025467-01
National Institute of Allergy and Infectious DiseasesU24AI117966
Wellcome Trust208381/A/17/Z, 212930/Z/18/Z
Biotechnology and Biological Sciences Research Council
Research Councils UK676559, H2020-EU 824087, H2020-EU 634107, H2020-EU 654241, BB/L024101/1, BB/L005069/1
Ministerie van Onderwijs, Cultuur en Wetenschap
Nederlandse Organisatie voor Wetenschappelijk Onderzoek1OT3OD025464-01, 628.011.011, 400.17.605, 3OT3TR002027-01S1
Ministerio de Economía y CompetitividadTIN2014-55993-RM, H2020-EU 825575
Universidad Politécnica de Madrid
Innovative Medicines Initiative802750, 116060

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