Findable: data should be easy to find and identify, possibly located in trusted discipline repositories.
Accessible: data should have open access whenever possible and be available through stardardised protocols.
Interoperable: well formatted data that uses discipline conventions and vocabularies, for both the data itself and the metadata used to describe it.
Reusable: data should be accompanied by enough information on how it was collected or processed, as to guarantee its quality and hence make it usable by other. It should have a license that allows and facilitates reuse.
In 2016, the ‘FAIR Guiding Principles for scientific data management and stewardship’ were published in Scientific Data. They are now widely adopted.
For more information on FAIR principles and how to apply them you can check the GO-FAIR initiative website. The ARDC website also has extensive resources on FAIR data, including a training and this assessment tool.
FAIR vignette from Open Science Training Handbook License: CC 0