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.
Visit our FAIR Data Principles webpage.
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