FAIR stands for making research data: Findable, Accessible, Interoperable, and Reusable.
The FAIR principles were published in 2016 in the article FAIR Guiding Principles for Scientific Data Management and Stewardship. The principles were developed to support the discovery and reuse of research data.
Working on a DMP for a research call? Most calls only require a short DMP (e.g. 2 pages) for the first stage of call. Use the bullet points below to ensure that you cover all FAIR Principles in your DMP.
What repositories can you use for your data to meet DMP requirements? The Library recommends Zenodo as a repository for data, software etc. This platform is run by CERN and supported by the EU OpenAIRE project, but use is not restricted to EU projects only. You can choose between open, embargoed, or restricted access; Multiple Creative Commons and open-source licences are available; Each upload receives a DOI (Digital Object Identifier) for citation which is required to make your data adhere to FAIR Principles.
FAIR data principles are guiding principles on best practice to make the greatest use and reuse of data; they are a good framework to follow when creating a Data Management Plan (DMP).
Making research data FAIR will provide a range of benefits to researchers, research communities, and research organisations, including:
FAIRsharing: a curated, informative and educational resource on data and metadata standards, inter-related to databases and data policies.
Force11 - The FAIR Data Principles: a set of guiding principles to make data Findable, Accessible, Interoperable, and Re-usable.
How FAIR are your data? a checklist produced for use at the EUDAT summer school to discuss how FAIR the participant's research data were and what measures could be taken to improve FAIRness.
GO FAIR RDM Starter Kit: a starter kit for RDM, listing resources to help researchers get started to organize their data.