The FAIR data principles aim to make research data Findable, Accessible, Interoperable and Reusable. You can read more about the FAIR principles in this Scientific Data article.
General principles, and already being adopted by the community
The principles have been developed, as a general guide to the "FAIRness of data" rather than as a specification through the FORCE11 (the Future Of Research Communication and E-scholarship) FAIR Data Publishing Group. As a sign of their adoption by the community, the principles were included in the July 2016 update of H2020 advice in their Guidelines on FAIR Data Management in Horizon 2020, The H2020 Guidelines also include a Data Management Plan (DMP) template that is compatible with the Principles.
The principles, in detail
The Principles are reproduced here, from this page:
To be Findable:
F1. (meta)data are assigned a globally unique and eternally persistent identifier.
F2. data are described with rich metadata.
F3. (meta)data are registered or indexed in a searchable resource.
F4. metadata specify the data identifier.
To be Accessible:
A1 (meta)data are retrievable by their identifier using a standardized communications protocol.
A1.1 the protocol is open, free, and universally implementable.
A1.2 the protocol allows for an authentication and authorization procedure, where necessary.
A2 metadata are accessible, even when the data are no longer available.
To be Interoperable:
I1. (meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
I2. (meta)data use vocabularies that follow FAIR principles.
I3. (meta)data include qualified references to other (meta)data.
To be Re-usable:
R1. meta(data) have a plurality of accurate and relevant attributes.
R1.1. (meta)data are released with a clear and accessible data usage license.
R1.2. (meta)data are associated with their provenance.
R1.3. (meta)data meet domain-relevant community standards.
What do you think?
Get in touch with your Research Data team to discuss the FAIR principles, or to get advice on a H2020 data management plan:
email us, phone: x4791, visit the Research Data support webpages and guide, or call in to the Library (4.10). We look forward to hearing from you!
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