Direct comparison
Data Citation Vs Software Citation: Key Differences & Comparison | CASRAI
Data citation and software citation both give credit for outputs beyond the article, but they follow different principles, identifiers, and metadata formats — and software citation must handle versions.
Side-by-side comparison
| Dimension | Data citation | Software citation |
|---|---|---|
| Principles document | FORCE11 Joint Declaration of Data Citation Principles | FORCE11 Software Citation Principles |
| Year | 2014 | 2016 |
| What is cited | A dataset | A piece of research software |
| Identifier | Commonly a DataCite DOI | Commonly a Zenodo DOI for a release |
| Metadata format | Dataset metadata on the repository / DataCite schema | CITATION.cff and CodeMeta metadata files |
| Version handling | Cite the version or subset used | Strong emphasis on the exact version cited |
| Where deposited | Data repositories (e.g. Zenodo, Dryad) | Code archives (e.g. Zenodo from a code platform) |
| Peer-review path | A data paper describing the dataset | A software paper describing the software |
| Credit mechanism | A citable, creditable record for data creators | A citable, creditable record for software authors |
Common questions
FAQ
Why does software citation stress versions so much?+
Software changes frequently, so a result may depend on the precise version used. The Software Citation Principles emphasise citing a specific, archived version — often a Zenodo DOI for a tagged release — so others can retrieve exactly the software behind a finding.
What are CITATION.cff and CodeMeta?+
They are machine-readable metadata formats for describing software. CITATION.cff is a simple file authors add to a code repository to specify how the software should be cited; CodeMeta is a broader schema for software metadata. Both help generate consistent, complete software citations.
Are the two sets of principles related?+
Yes — both come from the FORCE11 community and share the same goal of giving non-article outputs proper credit and a citable record. The data principles came first (2014) and the software principles (2016) adapted that thinking to software's particular needs, especially versioning.
Going deeper
