The FAIR principles (Findability, Accessibility, Interoperability, Reusability) applicable to the scientific data were developed by Force11 and published by Wilkinson et al. in 2016 (The FAIR Guiding Principles for scientific data management and stewardship). The steps involved in FAIRification have been explained by GO FAIR.
These principles form a guide to good practice for the management and reuse of data and metadata by both machines and humans. However, they do not constitute a specification because they do not recommend any particular standard, technology or data format.
In addition, FAIR data are not necessarily “open” and may have different degrees of FAIRness and/or openness. LOD (based on semantic web standards) and FAIR (based on principles) should not be confused: see on this subject “Cloudy, increasingly FAIR; revisiting the FAIR Data guiding principles for the European Open Science Cloud” (2017)
The terminology (meta)data presented in Loterre meets all the FAIR principles. Indeed, they are:
They can also participate in the FAIRification of (meta)research data by promoting their semantic interoperability (through vocabulary or thesaurus concepts).
Loterre and the Inist terminologies that the platform hosts are reported in the FAIRSharing portal: https://fairsharing.org/collection/Loterre