The FAIR Guiding Principles

Below are listed the FAIR Guiding Principles [1] as a reference for guiding FAIR implementation. They provide guidance when improving Findability, Accessibility, Interoperability and Reusability of digital resources. For machine-actionable reference, the principles are also defined in our ontology here.

See also the interpretation of the FAIR Guiding Principles by the GO FAIR community.

Findable

The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. Machine-readable metadata are essential for automatic discovery of datasets and services, so this is an essential component of the FAIRification process.

F1

(meta)data are assigned a globally unique and persistent identifier >> GO FAIR Foundation interpretation >>

F2

data are described with rich metadata (defined by R1 below)
>> GO FAIR Foundation interpretation >>

F3

metadata clearly and explicitly include the identifier of the data they describe
>> GO FAIR Foundation interpretation >>

F4

(meta)data are registered or indexed in a searchable resource
>> GO FAIR Foundation interpretation >>

Accessible

Once the user finds the required data, she/he/they need to know how they can be accessed, possibly including authentication and authorisation.

A1

(meta)data are retrievable by their identifier using a standardised communications protocol
>> GO FAIR Foundation interpretation >>

A1.1

the protocol is open, free, and universally implementable
>> GO FAIR Foundation interpretation >>

A1.2

the protocol allows for an authentication and authorisation procedure, where necessary
>> GO FAIR Foundation interpretation >>

A2

metadata are accessible, even when the data are no longer available
>> GO FAIR Foundation interpretation >>

Interoperable

The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing.

I1

(meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation
>> GO FAIR Foundation interpretation >>

I2

(meta)data use vocabularies that follow FAIR principles
>> GO FAIR Foundation interpretation >>

I3

(meta)data include qualified references to other (meta)data
>> GO FAIR Foundation interpretation >>

Reusable

The ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings.

R1

(meta)data are richly described with a plurality of accurate and relevant attributes
>> GO FAIR Foundation interpretation >>

R1.1

(meta)data are released with a clear and accessible data usage license
>> GO FAIR Foundation interpretation >>

R1.2

(meta)data are associated with detailed provenance
>> GO FAIR Foundation interpretation >>

R1.3

(meta)data meet domain-relevant community standards
>> GO FAIR Foundation interpretation >>

Anchor [1]

References

[1] The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 3, 160018 (2016). https://doi.org/10.1038/sdata.2016.18 Mark Wilkinson, Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, Arie Baak, Niklas Blomberg, Jan-Willem Boiten, Luiz Bonino da Silva Santos, Philip E. Bourne, Jildau Bouwman, Anthony J. Brookes, Tim Clark, Mercè Crosas, Ingrid Dillo, Olivier Dumon, Scott Edmunds, Chris T. Evelo, Richard Finkers, Alejandra Gonzalez-Beltran, Alasdair J.G. Gray, Paul Groth, Carole Goble, Jeffrey S. Grethe, Jaap Heringa, Peter A.C ’t Hoen, Rob Hooft, Tobias Kuhn, Ruben Kok, Joost Kok, Scott J. Lusher, Maryann E. Martone, Albert Mons, Abel L. Packer, Bengt Persson, Philippe Rocca-Serra, Marco Roos, Rene van Schaik, Susanna-Assunta Sansone, Erik Schultes, Thierry Sengstag, Ted Slater, George Strawn, Morris A. Swertz, Mark Thompson, Johan van der Lei, Erik van Mulligen, Jan Velterop, Andra Waagmeester, Peter Wittenburg, Katherine Wolstencroft, Jun Zhao & Barend Mons