How to make data FAIR

Open Science Training Handbook (1.0). https://book.fosteropenscience.eu/ (c) CC0 1.0 Universal - Open Science Training Handbook (1.0). https://book.fosteropenscience.eu/
 
 
In 2016, the "The FAIR Guiding Principles for scientific data management and stewardship" were published in Scientific Data. This article presented the FAIR principles, which provide a set of precise qualities that a research data publication should follow to make data Findable, Accessible, Interoperable, and Reusable.
 
In the framework of the development of Open Science, the European Commission requires all projects funded under the current Horizon Europe Programme and the previous Horizon 2020 Programme, except justified cases, to develop a data management plan and ensure open access to research data. Data should be deposited openly following the FAIR principles that describe how research results should be organised so that they are findable, accessible, interoperable and reusable.
 
Publishing data according to the FAIR principles allows to comply with the motto: «as open as possible, as closed as necessary».
 
How to make data FAIR
 

Findable: Metadata and data should be easy to find. In order to do this, it is recommended to assign a unique and persistent identifier to the data, describe it with rich metadata, and register the metadata in a searchable resource.

 
Accessible: It must be possible for both humans and machines to access the data, subject to specific conditions or restrictions where necessary. Use standardised communication protocols for retrieval of data and metadata through the identifier; use open and free protocols; allow authentication and authorisation procedures when data cannot be open; and ensure that metadata is accessible, even when data is no longer available.
 
Interoperable: Data and metadata must follow recognised formats and standards to allow their combination and exchange. Data are provided in known and widely used formats, and preferably open. The metadata provided follows recognised standards. Wherever possible, controlled vocabularies, keywords, thesauri or ontologies are used. References and links to other related data are included.
 
Reusable: Publish data and metadata with a clear and accessible licence on its use and reuse; associate it with provenance information and comply with relevant standards used by the community in that particular domain.
 
Verification tools:
 
 

Image source: Sonja Bezjak, April Clyburne-Sherin, Philipp Conzett, Pedro Fernandes, Edit Görögh, Kerstin Helbig, Bianca Kramer, Ignasi Labastida, Kyle Niemeyer, Fotis Psomopoulos, Tony Ross-Hellauer, René Schneider, Jon Tennant, Ellen Verbakel, Helene Brinken, & Lambert Heller. (2018). Open Science Training Handbook (1.0).