Abstract

The FAIR Data Principles propose that all scholarly output should be Findable, Accessible, Interoperable, and Reusable.As a set of guiding principles, expressing only the kinds of behaviours that researchers should expect from contemporary data resources, how the FAIR principles should manifest in reality was largely open to interpretation.As support for the Principles has spread, so has the breadth of these interpretations.In observing this creeping spread of interpretation, several of the original authors felt it was now appropriate to revisit the Principles, to clarify both what FAIRness is, and is not.