Journal
SCIENTIFIC DATA
Volume 6, Issue -, Pages -Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/s41597-019-0184-5
Keywords
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Categories
Funding
- Isaac Peral/Marie Curie cofund
- Universidad Politecnica de Madrid, Ministerio de Economia y Competitividad [TIN2014-55993-RM]
- European Joint Programme on Rare Diseases [H2020-EU 825575]
- UK BBSRC Council [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, 3OT3TR002027-01S1, 1OT3OD025464-01]
- Wellcome Trust [212930/Z/18/Z, 208381/A/17/Z]
- NWO [400.17.605, 628.011.011]
- ELIXIR
- UPM Isaac Peral/Marie Curie cofund
- Dutch Techcenter for Life Sciences DP
- Dutch Ministry of Education, Culture and Science (Ministerie van Onderwijs, Cultuur en Wetenschap)
- Netherlands Organisation for Scientific Research (Nederlandse Organisatie voor Wetenschappelijk Onderzoek)
- Dutch TechCenter for Life Sciences
- UK Research Council [BB/L024101/1, BB/L005069/1]
- BBSRC [BB/L005069/1, BB/L005069/2, BB/E025080/1, BB/L005050/1, BB/J020265/1, BB/P025943/1, BB/L024101/1] Funding Source: UKRI
- Wellcome Trust [212930/Z/18/Z, 208381/A/17/Z] Funding Source: Wellcome Trust
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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.
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