How to be FAIR
Open Science and increasingly Open Data revolve around the realisation and application of four basic principles which are known by the acronym of FAIR*, namely
| F | FINDABLE |
To be Findable any Data Object should be uniquely and persistently identifiable. |
| A | ACCESSIBLE | Data is Accessible in that it can be always obtained by machines and humans |
| I | INTEROPERABLE | Data Objects can be Interoperable only if: (Meta) data is machine-actionable |
| R | RE-USABLE | (Meta) data should be sufficiently well-described and rich that it can be automatically (or with minimal human effort) linked or integrated, like-with-like, with other data sources. Published Data Objects should refer to their sources with rich enough metadata and provenance to enable proper citation. |
These four principles were initially articulated in an article published by Mark Wilkinson and colleagues in March 2016 (see footnote 15 below) and have come to be accepted by the research and scientific communities as a way of understanding, making sense of and bringing co-ordination to all the material and scholarship which is increasingly described as ‘Open’.
We have listed a few web pages below which describe the FAIR principles in relation to Open Data in more detail and offer some self-help tools and guidance for ensuring that your data is FAIR.
FAIR Data Self-Assessment Tool (Australian National Data Service
FAIR Data Assessment Tool (using Survey Monkey)
FAIRShake : A System to Evaluate the FAIRness of Digital Objects
*Wilkinson, Mark D. The FAIR Guiding Principles for scientific data management and stewardship https://www.nature.com/articles/sdata201618