Examples
Worked examples
- Is an instance
A researcher who spent six months cleaning and documenting a 50-GB dataset for Dryad deposit with a DataCite DOI
Counter-examples
Looks similar, but isn't
- Not an instance
Uploading an undocumented zip to a personal Dropbox is not an open-data contribution in the FAIR sense
Editorial commentary
Open-data contribution is the substantive work of preparing, documenting, depositing, and maintaining a research dataset in a FAIR-aligned open repository under a permissive licence — work that is distinct from, and often far more time-consuming than, the original data collection itself. Metadata curation, format conversion, README authoring, schema design, and ongoing maintenance after deposit are all part of this labour, historically close to invisible in credit systems built around paper authorship alone.
How it differs from related terms: Open-software contribution is the equivalent labour applied to code rather than data; a data validator checks a dataset’s quality and correctness rather than preparing it for deposit, though the same person frequently does both. This is credited through DataCite DOIs and formal data citations, and increasingly through CRediT-extension “Data curation” credit on papers that use the dataset, rather than solely through the deposit record itself.
An undocumented file dropped into a personal cloud folder is not an open-data contribution in the FAIR sense — the documentation, licensing, and long-term accessibility are what make the work reusable, and therefore creditable.
References
- Wilkinson et al., “The FAIR Guiding Principles,” Scientific Data (2016)
- FORCE11 Joint Declaration of Data Citation Principles (2014)
Also known as
Data curation contribution · Data stewardship contribution
Machine-readable encodings
Use in your systems
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