Descripción
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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. | |
Internacional
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Si |
JCR del ISI
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Si |
Título de la revista
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Scientific Data |
ISSN
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2052-4463 |
Factor de impacto JCR
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5,305 |
Información de impacto
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Datos JCR del año 2017 |
Volumen
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DOI
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10.1038/s41597-019-0184-5 |
Número de revista
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Desde la página
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SD 6 |
Hasta la página
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AN 174 |
Mes
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SIN MES |
Ranking
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