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datasets: Croissant 1.1 + RAI metadata, versioned signed releases, citation - #96
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…tation - Every published dataset gets a croissant.json (MLCommons Croissant 1.1 with the Responsible AI vocabulary: limitations, biases, use cases, personal data, collection, social impact, maintenance), generated by data_validation/croissant/build_croissant.py. File checksums, record fields and dates come from the repository; the RAI text is per dataset in the generator. Record sets over each index/manifest CSV let ML tooling load the data directly. - CI: croissant files must be up to date, valid per mlcroissant, and load the same number of records as their CSVs. - datasets-release workflow: tagging datasets-v<version> (matching CITATION.cff) re-runs every check, builds per-dataset and all-datasets zips with SHA256SUMS, attests build provenance with Sigstore, and publishes a GitHub release. - CITATION.cff (datasets version 1.0.0) and .zenodo.json for citation and Zenodo DOI archiving. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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| "Skews toward open-source Python LLM frameworks and inference servers (agent frameworks are about half of " | ||
| "the entries), because CVE assignment concentrates there; closed SaaS assistants appear only through " | ||
| "public research disclosures.", |
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| "Sector coverage is uneven: cross-sector templates are the largest group, followed by financial " | ||
| "services and SaaS; several sectors have a single template.", |
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| "Reflects the attack styles of its source corpora (authority and urgency framing, morphological and " | ||
| "cross-lingual bypasses).", |
…set files LF CI regenerated different checksums because Windows working copies are CRLF. .gitattributes now pins dataset CSV/JSON (and reference CSVs) to LF on every platform, agentdataflow's index.csv is renormalized (its build_index.py writes CRLF), and build_croissant.py hashes LF-normalized bytes, which equal the stored blob. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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Summary
Items 12–13 of the data-validation review.
MLCommons Croissant 1.1 + Responsible AI metadata
croissant.json: vulnerability, exploit, riskassessment, agentdataflow, promptinj and rag. Incident (no entries yet) and crossframework (superseded) are skipped.data_validation/croissant/build_croissant.pygenerates them with the officialmlcroissantlibrary:dataLimitations,dataBiases,dataUseCases,personalSensitiveInformation,dataCollection/Type,dataSocialImpact,dataReleaseMaintenancePlan) is written per dataset in the generator, checked against the data's actual distributions. For example, the vulnerability dataset's skew toward agent frameworks and High/Critical severity, and the exploit dataset's ~70% ATLAS share.index.csvor manifest let ML tooling load the records directly. NeurIPS 2026 requires Croissant with RAI fields for dataset submissions.croissant, using the new optionalrequirements-croissant.txt:mlcroissant validate;Versioned, checksummed, signed releases
datasets-releaseworkflow, triggered by pushing adatasets-v<version>tag that matchesCITATION.cff. It:SHA256SUMS;actions/attest-build-provenance, pinned), verifiable withgh attestation verify;Citation and DOI
CITATION.cff: datasets version 1.0.0, CC-BY-SA-4.0. This enables GitHub's "Cite this repository" button..zenodo.jsonsupplies Zenodo's metadata. One manual step remains: an org owner has to enable this repository in Zenodo's GitHub integration (zenodo.org → GitHub). After that, eachdatasets-v*release is archived on Zenodo with a DOI.Docs
datasets/README.mdgains a "Metadata, releases and citation" section. The contribution steps now say to regenerateindex.csvandcroissant.jsonafter editing entries.Verification
CITATION.cffversion is semver).run_all_checks.py: 0 errors (croissant.jsonis excluded from the record checks).actionlintis clean.🤖 Generated with Claude Code