The FAIR Principles are a set of guiding principles for making data findable, accessible, interoperable and reusable1.
Findable: Metadata and data should be easy to find for both humans and computers. For the automatic discovery of datasets and services, it is essential that metadata is machine-readable.
Accessible: Once the required data has been found/discovered, the user needs to know how the data can be accessed. This information may include details including authorisation and authentication.
Interoperable: As data often needs to integrate with other data, it is essential that data should be able to interoperate with applications or workflows for analysis, storage, and processing.
Reusable: The main aim of FAIR is to optimise the reuse of data. To make this achievable, metadata and data should be described well, so that they can be replicated and/or utilised in different settings.
1 Wilkinson, M. D. et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018. doi:10.1038/sdata.2016.18
