# awesomedata/awesome-public-datasets

A topic-centric list of HQ open datasets.

Repository: https://github.com/awesomedata/awesome-public-datasets
Canonical: https://ross.abutalabs.com/products/awesome-public-datasets
Homepage: https://awesomedataworld.slack.com
License: MIT
License Family: permissive
Topics: opendata, aaron-swartz, awesome-public-datasets, datasets
Last push: 2026-08-26T21:15:40+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 8, longevity 100
- inputs: {"age_days": 4304, "days_push": 7, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 78657, forks 11813 (observed 2026-08-28T04:12:21.683031+00:00)

## What it is
A topic-centric, curated list of high-quality free and open public datasets, organized by domain (agriculture, finance, health, etc.). It is maintained as an awesome-list and auto-generated from a core metadata repository.

## Use cases
- find open datasets for machine learning projects
- locate public data sources for a data science portfolio
- download sample data to practice data analysis
- find benchmark datasets for research
- source training data for a new model
- discover domain-specific open data for a report

## When to choose
- you need a curated starting point for finding public datasets across many topics
- you want free, community-vetted data sources for learning or prototyping

## When to avoid
- you need a guaranteed-clean, ready-to-use dataset rather than links to external sources
- you require datasets with licensing or SLA guarantees, since some listed sources are not free

## Facets
- artifact type: dataset
- maturity: active
- function: data-science, machine-learning, developer-tools
- domain: data-science, big-data, machine-learning, awesome-lists
- platform: cross-platform
- tags: awesome-list, open-data, curated-list, public-datasets

## Member repositories
- awesomedata/awesome-public-datasets (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:21.683031+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:14:11.301139+00:00, confidence not recorded.
  - readme: https://github.com/awesomedata/awesome-public-datasets (fetched 2026-08-28T04:12:21.683031+00:00, sha 664bc6f1b254)
- Data as of 2026-08-30T08:39:29.467469+00:00.