SetGo: Metadata Readiness for Scientific AI Datasets
Scientific datasets intended for AI use require both computational readiness for model training and metadata readiness for discovery, sharing, and reuse. The Readiness Engine for Data Integration (REDI) addresses computational readiness, but no corresponding tool evaluates whether a dataset's metadata are sufficiently complete, governed, and standards-compliant for publication and agent-based consumption. Existing FAIR assessors operate only on published repository records, and no single system covers FAIR compliance, licensing, provenance, governance, reproducibility, and catalog readiness together. We present SetGo, an open-source Python toolkit that assesses and repairs metadata readin...
| Authors | Sean R. Wilkinson, Polina Shpilker, Wesley Brewer |
|---|---|
| Primary category | cs.DL |
| Published | 10 July 2026 |
| Last updated at source | 10 July 2026 |
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