Findable, Accessible, Interoperable, Reusable – FAIR: an acronym that recently became inevitable for anyone involved in research data management, or in any of the initiatives relating to the European Open Science Cloud.
Digital scientific data, tools, workflows and services are becoming available at increased speed and unprecedented scale. Unfortunately, a large segment of these digital objects remains unnoticed, unaccessed or un-used beyond their producer team, limiting our abilities of extracting maximum benefit and knowledge from these research investments.
The FAIR principle was first introduced in a workshop held in Leiden in 2014, where a group of like-minded academic and private stakeholders met to discuss ways to overcome obstacles in data discovery and reuse.
FAIR consists of 15 elements that define the characteristics needed to enable reuse by third-parties. For example, to be Findable (F), data should:
Although the elements of the FAIR principles are related they are also independent and separable. The principles may be adhered to in any combination and incrementally, as providers’ publishing environments evolve to increasing degrees of ‘FAIRness’.
The FAIR principles precede implementation choices, and do not enforce or recommend any specific technology, standard, or implementation-solution. The principles are also not a standard or a specification. They establish a concise and measurable set that can act as a common denominator across institutes, across data and service providers and across disciplines. This means that they can be used as a guide to help data and tool owners to evaluate if their data, tools and services are findable, accessible, interoperable, and reusable.