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

Wilkinson, Mark Denis and Dumontier, Michel and Sansone, Susanna-Assunta and Da Silva Santos, Luiz Bonino and Prieto Godoy, Mario and Batista, Dominique and McQuilton, Peter and Kuhn, Tobias and Rocca-Serra, Philippe and Crosas, Mercè and Schultes, Erik (2019). Evaluating FAIR maturity through a scalable, automated, community-governed framework. "Scientific Data", v. 6 (n. 174); pp. 1-12. ISSN 2052-4463. https://doi.org/10.1038/s41597-019-0184-5.


Title: Evaluating FAIR maturity through a scalable, automated, community-governed framework
  • Wilkinson, Mark Denis
  • Dumontier, Michel
  • Sansone, Susanna-Assunta
  • Da Silva Santos, Luiz Bonino
  • Prieto Godoy, Mario
  • Batista, Dominique
  • McQuilton, Peter
  • Kuhn, Tobias
  • Rocca-Serra, Philippe
  • Crosas, Mercè
  • Schultes, Erik
Item Type: Article
Título de Revista/Publicación: Scientific Data
Date: September 2019
ISSN: 2052-4463
Volume: 6
Faculty: Centro de Investigación en Biotecnología y Genómica de Plantas (CBGP) (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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 communitydefined FAIR assessments. The components of the framework are: (1) Maturity Indicators – communityauthored 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.

Funding Projects

Government of SpainTIN2014-55993-RMUnspecifiedUnspecifiedUnspecified
Horizon 2020825575EJP RDUnspecifiedEuropean Joint Programme on Rare Diseases
Horizon 2020634107MULTIMOTUnspecifiedCapture, dissemination and analysis of multiscale cell migration data for biological and clinical applications (MULTIMOT)
Horizon 2020654241PhenoMeNalUnspecifiedPhenoMeNal: A comprehensive and standardised e-infrastructure for analysing medical metabolic phenotype data
Horizon 2020676559ELIXIR-EXCELERATEUnspecifiedELIXIR-EXCELERATE: Fast-track ELIXIR implementation and drive early user exploitation across the life-sciences
Horizon 2020824087EOSC-LifeUnspecifiedProviding an open collaborative space for digital biology in Europe

More information

Item ID: 56643
DC Identifier: https://oa.upm.es/56643/
OAI Identifier: oai:oa.upm.es:56643
DOI: 10.1038/s41597-019-0184-5
Official URL: https://www.nature.com/articles/s41597-019-0184-5
Deposited by: Memoria Investigacion
Deposited on: 11 Oct 2019 12:31
Last Modified: 11 Oct 2019 12:31
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