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What is FAIR data?

By Daniel Van Strien, on 9 October 2017

The FAIR data principles aim to provide a framework to ensure that research data can be effectively reused. The principles are outlined below alongside recommendations for practically achieving these principles.

Why FAIR data? 

The FAIR Data Principles were developed by a FORCE11 group and originally published in Nature Scientific Data in 2016. The authors argue that ‘Good data management is not a goal in itself, but rather is the key conduit leading to knowledge discovery and innovation, and to subsequent data and knowledge integration and reuse by the community after the data publication process.’

What are the fair data principles?

The FAIR principles outline four broad requirements for effectively sharing research data:

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.

How to make your data FAIR?

Researchers can help make their data FAIR by:

Researchers can help ensure that they can make their data available under the FAIR principles by planning early in the research process. Completing a Data Management Plan using a funder template or DMPOnline will make it easier to release data in the most effective manner at the end of a project.