"There is an urgent need to improve the infrastructure supporting the reuse of scholarly data." Good data management is not a goal in itself, but a conduit leading to knowledge discovery, innovation and the reuse of the data. The current digital ecosystem prevents this, which is why the funding and publishing community is beginning to require data management and stewardship plans. "Beyond proper collection, annotation, and archival, data stewardship includes the notion of ‘long-term care’ of valuable digital assets" so they can be discovered and re-used for new investigations.
This article describes four foundational principles (FAIR) to guide data producers and publishers:
- Findability,
- assigned a globally unique and persistent identifier
- data are described with rich metadata
- metadata clearly include the identifier of the data it describes
- data are registered or indexed in a searchable resource
- Accessibility,
- 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,
- metadata are accessible, even when the data are no longer available
- Interoperability,
- data use a formal, accessible, shared, and broadly applicable language for knowledge representation
- data use vocabularies that follow FAIR principles
- data include qualified references to other (meta)data
- Reusability
- meta(data) are richly described
- (meta)data have a clear data usage license
- (meta)data have a detailed provenance
- (meta)data meet community standards
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