Our approach to the FAIR Data Principles

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Written by

Sophie Bryant

Posted on

September 28, 2021

The FAIR Data Principles stand for findability, accessibility, interoperability, and reusability of data for both humans and machines. Here we highlight a few ways CCDC supports the FAIR Data Principles.

What are the FAIR Data Principles?

The FAIR Guiding Principles for scientific data management and stewardship were published in Nature's Scientific Data in 2016.


  • (Meta)data are assigned a globally unique and persistent identifier.
  • Data are described with rich metadata (defined by the first "R" requirement below).
  • Metadata clearly and explicitly include the identifier of the data they describe.
  • (Meta)data are registered or indexed in a searchable resource.


  • (Meta)data are retrievable by their identifier using a standardized communications protocol.
  • The protocol is open, free, and universally implementable.
  • The protocol allows for an authentication and authorization procedure, where necessary.
  • Metadata are accessible, even when the data are no longer available.


  • (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation.
  • (Meta)data use vocabularies that follow FAIR principles.
  • (Meta)data include qualified references to other (meta)data.


  • (Meta)data are richly described with a plurality of accurate and relevant attributes.
  • (Meta)data are released with a clear and accessible data usage licence.
  • (Meta)data are associated with detailed provenance.
  • (Meta)data meet domain-relevant community standards.

At CCDC, the FAIR Data Principles help guide our data decisions, and we're committed to:

  • Ensuring machines can reliably understand crystallographic experiments, data, and knowledge by using standard formats and vocabularies.
  • Adopting persistent identifiers to identify datasets and their contributors.
  • Leveraging standard identifiers such as InChI to link datasets to a range of chemistry resources.
  • Ensuring metadata is harvestable by machines to enable interoperability with other information resources.
  • Providing searchable resources that enable the discovery of data through interfaces designed for both humans and their machines.

Learn more

Visit our FAIR Data Principles webpage.

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