Lesson 951 of 2116
Citing Research Software Properly: From Stata to PyTorch to That Custom Pipeline
Software citation has lagged behind data citation, but journals and funders now expect it. AI can generate proper citations for software packages, custom code, and computing environments — every time.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2software citation
- 3FORCE11
- 4Zenodo DOI
Concept cluster
Terms to connect while reading
Section 1
The premise
Proper software citation is a reproducibility imperative; AI can generate the citations consistently when the underlying metadata exists.
What AI does well here
- Generate citations for software packages following FORCE11 software citation principles (creators, title, version, publisher, identifier)
- Recommend version-specific identifiers (Zenodo DOIs, GitHub release tags)
- Draft computing environment statements (OS, language version, package versions)
- Produce a reproducibility appendix listing every software dependency with version
What AI cannot do
- Substitute for actually capturing the version information at the time of analysis
- Generate DOIs for software that hasn't been deposited
- Replace the discipline-specific citation styles (which vary)
Key terms in this lesson
End-of-lesson quiz
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