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FAIR (Findable, Accessible, Interoperable, Reusable)

FAIR (Findable, Accessible, Interoperable, Reusable)

In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data. The authors intended to provide guidelines to improve the findability, accessibility, interoperability, and reuse of digital assets.

All edits by  Gil Gildner 

Edits on 9 May 2019
Gil Gildner
Gil Gildner approved a suggestion from Golden's AI on 9 May 2019 10:11 am
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Article

The ideas within the FAIR Guiding Principles reflect, combine, build upon and extend previous work by both the Concept Web Alliance (https://conceptweblog.wordpress.com/) partners, who focused on machine-actionability and harmonization of data structuresdata structures and semantics, and by the scientific and scholarly organizations that developed the Joint Declaration of Data Citation Principles (JDDCP29), who focused on primary scholarly data being made citable, discoverable and available for reuse, so as to be capable of supporting more rigorous scholarship. An attempt to define the similarities and overlaps between the FAIR Principles and the JDDCP is provided at (https://www.force11.org/node/6062). The FAIR Principles are also complementary to the 'Data Seal of Approval' (DSA) (http://datasealofapproval.org/media/filer_public/2013/09/27/guidelines_2014-2015.pdf) in that they share the general aim to render data re-usable for users other than those who originally generated them. While the DSA focuses primarily on the responsibilities and conduct of data producers and repositories, FAIR focuses primarily on the data itself. Clearly, the broader community of stakeholders is coalescing around a set of common, dovetailed visions spanning all facets of the scholarly data publishing ecosystem.

Gil Gildner
Gil Gildner approved a suggestion from Golden's AI on 9 May 2019 10:11 am
Edits made to:
Article (+19/-19 characters)

Article

Good data stewardship is the key to knowledge discovery and innovation. To generate value for a research community beyond the initial researchers, funding agencies are increasingly setting requirements for proper data stewardship of research data. Beyond proper collection, annotation, and archival, data stewardship includes the 'long-term care' of research data, with the goal that they can be found and re-used in downstream studies. To facilitate good data stewardship, a broad community of international stakeholders have developed the FAIR Data principles. The FAIR principles have been embraced by both the European CommissionEuropean Commission and the G20. The first formal publication of the FAIR Principles further describes the rationale behind them.

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