FAIR data is data which meets the FAIR principles of findability, accessibility, interoperability, and reusability (FAIR).[1][2] The acronym and principles were defined in a March 2016 paper in the journal Scientific Data by a consortium of scientists and organizations.[1]
The FAIR principles emphasize machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in the volume, complexity, and rate of production of data.[3]
The abbreviation FAIR/O data is sometimes used to indicate that the dataset or database in question complies with the FAIR principles and also carries an explicit data‑capable open license.
- ^ a b Mark D. Wilkinson; Michel Dumontier; IJsbrand Jan Aalbersberg; et al. (15 March 2016). "The FAIR Guiding Principles for scientific data management and stewardship". Scientific Data. 3 (1): 160018. doi:10.1038/SDATA.2016.18. ISSN 2052-4463. PMC 4792175. PMID 26978244. Wikidata Q27942822.
- ^ Annika Jacobsen; Ricardo de Miranda Azevedo; Nick Juty; et al. (31 January 2020). "FAIR Principles: Interpretations and Implementation Considerations". Data Intelligence: 10–29. doi:10.1162/DINT_R_00024. ISSN 2641-435X. Wikidata Q76394974.
- ^ "FAIR Principles". GO FAIR. Retrieved 2020-02-16.
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