FAIR Principles

The increasing volume and availability of online resources requires that research data be managed from inception in a way that allows for long-term or permanent preservation. By making research data accessible to the wider research community, we facilitate access to knowledge and improve the transparency of research. To this end, an international group of researchers, scientific publishers and data experts published the FAIR Principles for Research Data Management in 2016. The FAIR Guiding Principles for Scientific Data Management and Stewardship.

SangyaPundir, CC BY-SA 4.0, via Wikimedia Commons

FAIR is not a standard, but a list of principles that define FAIR research data as data that can be found (Findable), accessible (Accessible), interoperable (Interoperable) and reusable (ReusableIn addition to supporting the re-use of research data, the FAIR principles place particular emphasis on improving the machine findability, readability and usability of data. The principles highlight the fact that in the current digital ecosystem, people are increasingly dependent on computer support to cope with the increasing volume, complexity and speed of data creation. In this context, the machine usability of research data (i.e. the ability of computing systems to find, access, interact with and reuse data with little or no human intervention) highlighted by the FAIR Principles is crucial.


The FAIR Principles, which are described in more detail on the website Go FAIR, comprising the following points:

 Findability(Findability) 

  • (Meta)data is assigned a globally unique persistent identifier (PID, e.g. research data is described with rich metadata (at least creation date, title, authors, keywords, licence, funding, etc.). 
  • The metadata clearly and explicitly state the identifier of the research data they describe, e.g. DOI (Digital Object Identifier). 
  • (Meta)data are registered or indexed in a search resource (e.g. search engines, bibliographic collections, indexes). 

Accessibility(Accessibility) 

  • The (meta)data is accessible through the identifier via a standardised communication protocol that is open, free and universal (e.g. http). 
  • The communication protocol allows for authentication and authorisation procedures where necessary, which must be notified to the user (e.g. login with an institutional account or digital certificate). 
  • Metadata is available even when the research data itself is no longer available. 
  • Metadata is accessible even if the data cannot be open for legitimate reasons (e.g. protection of personal data). The term "open as far as possible and closed as far as necessary" has been coined for this principle ("as open as possible and as closed as necessary"). FAIR data is therefore not necessarily OPEN data. 

   Interoperability(Interoperability) 

  • (Meta)data are described in a formal, accessible, general and widely applicable language for representing knowledge. 
  • (Meta)data follow a controlled vocabulary that follows the FAIR principles, (e.g. Medical Subject Headings in medicine). 
  • (Meta)data contain qualified references (references or links) to other data and metadata. 

 Re-use(Reusability) 

  • The (meta)data are richly described and provide a multitude of detailed and relevant characteristics. 
  • The (meta)data is accompanied by a clear and accessible licence on the use of the research data, e.g. Creative Commons. 
  • (Meta)data gives details of the origin (provenance) of the research data. 


The data must be compatible with other datasets, applications or workflows for analysis, storage and processing (e.g. use of non-proprietary, open data formats is recommended). The metadata must meet the standards of the specific scientific domain and contain everything needed to understand and reuse the data (methodology, measurement variables and units, definitions, programming code, etc.). More on the preparation and use of metadata. data formatting and metadata for open sharing under the FAIR principles can be found on the DiRROS Data website. 

You can check how well your data meets the FAIR principles by using the websites or tools How to FAIR and FAIR Self Assessment Tool. 

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