Citing data gives proper credit to the data creators and acknowledges their contribution.
Just like journal articles, datasets should be cited formally to recognize the researchers who created them and to help others reliably locate and reuse the data.
What should a data citation include:
Data citation uses the same core elements as traditional references:
- Author(s)/Creator(s)
- Title of Dataset
- Publication Year
- Repository or Publisher
- Version or Edition (if applicable)
- Persistent Identifier (DOI, handle, URL)
These elements ensure anyone can accurately locate the exact dataset cited, even years later.
UBC Library on how to cite data
Citing data properly ensures that data creators receive credit, supports the reproducibility of research, and allows others to locate and reuse the data accurately.
Get Cited
- Deposit your data in a repository like UBC Dataverse Collection (Borealis) or FRDR (for really large datasets) to receive a DOI and a built-in data citation.
- Include the citation in publications and presentations, ensuring readers know how to find your dataset.
- Track your dataset’s impact via citations and repository download metrics, demonstrating the value of your work.
- Connect datasets to your profile on platforms like ORCID, Google Scholar, or ImpactStory by adding the DOI to your work and activating an ORCID token (e.g. example ORCID<>Datacite connection)
 Data access statements
Many journals and funders now require a Data Access Statement in publications, which should include:
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Where the data is deposited (e.g., UBC Dataverse, FRDR)
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Persistent identifiers (DOIs), when possible
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Any constraints on access (e.g., due to ethics or confidentiality)
Need help? Contact research.data@ubc.ca