FAIR data


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This is a proposed new standard glossary term. See this post for background on this review track. To comment on the term below either click the blue “Reply” button at the bottom or select a passage of text in the term and click the “Quote” pop-up to create a comment about that section only.

Short Definition: Data that conforms to the FAIR data principles which suggest that research data should be Findable, Accessible, Interoperable and Reusable.

Extended Definition: Data that conforms to the FAIR data principles which suggest that research data should be Findable, Accessible, Interoperable and Reusable. The concept of FAIR data builds on previous attempts to define a set of attributes that add to the value of research data and build collectively the the usability of data by other researchers and by machines. Most notable among these is the definition of Intelligent Openness coined for the Royal Society report Science as an Open Enterprise (Royal Society, 2012: https://royalsociety.org/policy/projects/science[public[enterprise/Report/) and then adopted by the G7 Science Ministers’ Statement and the 2013 iteration of the European Commission’s Research Data Policy for the Horizon 2020 Programme (discoverable, accessible, assessable, intelligible, useable, and … interoperable) (European Commission 2013, Guidelines on Data Management in Horizon 2020: http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020[hi[oa[data[mgt_en.pdf. The FAIR data principles add a set of sub-definitions that identify those things that are required to make data susceptible to mass processing by machines.

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Sources: https://www.force11.org/group/fairgroup/fairprinciples

Term Lead: Simon Hodson


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