Dataset Freshness Check Runbook and Results

This workspace was used to run agentic freshness checks across dataset repositories under datasets/.

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What Was Done

• Ran an agentic workflow for each one of the repos
• For each repo, the checker:
  • reads repo metadata (README, datapackage, scripts),
  • extracts candidate upstream source URLs,
  • probes/fetches upstream endpoints,
  • computes latest local date from local data files,
  • compares local vs inferred upstream recency,
  • appends a row to freshness-report.csv.

Output Files

• Consolidated report: freshness-report.csv

CSV Schema

freshness-report.csv follows this structure:

repo_name,readme_location,datapackage_location,scripts_location,description,latest_local_date,latest_upstream_date,is_stale,staleness_reason,status

Notes and Caveats

• Checks are source-driven (not based on last git update date).
• Some datasets are flagged stale because upstream endpoints are inaccessible (401/403/404, redirects, or network timeouts).
• Some rows have empty latest_upstream_date when upstream recency could not be inferred from reachable payloads.