FAIR principles

Following the FAIR principles, research objects should be findable, accessible, interoperable re-usable. These principles form the basis of a trusted environment where researchers, innovators, companies, and citizens can publish, find, and re-use each other’s data and tools for research, innovation, and educational purposes. The FAIR principles refer to any digital object evolving from the research process, that is, quantitative as well as qualitative data, metadata or algorithms, tools, software and services.

The first step in (re)using data is to find them. Machine-readable metadata are essential for automatic discovery of datasets and services. This can be realized, for instance, by assigning digital research objects with persistent identifiers

To ensure long-term accessibility, data need to be archived in a way that they (or at least their metadata) are retrievable via standardised, universally implementable communication protocols. The exact conditions under which the data is accessible should be provided.

For (meta)data to integrate with other data and to interoperate with existing applications or workflows, it should be based on standardized vocabularies, ontologies, thesauri etc. that follow the FAIR principles.

The ultimate goal of FAIR is to optimise the reuse of data in future research endeavours. To achieve this, metadata and data should be well-described so that researchers can judge whether they can be replicated and/or combined in a certain setting.


GO FAIR is a global and open initiative in which individuals, institutions and organizations synchronize their “FAIRification” efforts to avoid silo formation, undue competition and fragmentation.