Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud

The FAIR Data Principles propose that all scholarly output should be Findable, Accessible, Interoperable, and Reusable. As a set of guiding principles, expressing only the kinds of behaviours that researchers should expect from contemporary data resources, how the FAIR principles should manifest in...

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Published inInformation services & use Vol. 37; no. 1; pp. 49 - 56
Main Authors Mons, Barend, Neylon, Cameron, Velterop, Jan, Dumontier, Michel, da Silva Santos, Luiz Olavo Bonino, Wilkinson, Mark D.
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.02.2017
Sage Publications Ltd
Subjects
Guidelines
Open data
Science
standards
interoperability
FAIR Data
Open Science
data integration
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Summary:The FAIR Data Principles propose that all scholarly output should be Findable, Accessible, Interoperable, and Reusable. As a set of guiding principles, expressing only the kinds of behaviours that researchers should expect from contemporary data resources, how the FAIR principles should manifest in reality was largely open to interpretation. As support for the Principles has spread, so has the breadth of these interpretations. In observing this creeping spread of interpretation, several of the original authors felt it was now appropriate to revisit the Principles, to clarify both what FAIRness is, and is not.
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ISSN:0167-5265
1875-8789
DOI:10.3233/ISU-170824