# petewarden/dstk

A collection of the best open data sets and open-source tools for data science

Repository: https://github.com/petewarden/dstk
Canonical: https://ross.abutalabs.com/products/dstk
Homepage: http://www.datasciencetoolkit.org/
Language: Ruby
License Family: other
Last push: 2016-08-29T12:16:48+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 5658, "days_push": 3656, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license, no_readme
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1149, forks 182 (observed 2026-08-28T04:03:46.350972+00:00)

## What it is
A curated collection of the best open datasets and open-source tools for data science, associated with the Data Science Toolkit project. It serves as a reference index rather than a runnable library.

## Use cases
- find open datasets for a data science project
- discover open-source data science tools
- locate free geocoding and text analysis data
- get started with public data sources
- find resources for machine learning datasets

## When to choose
- you want a curated starting point for open data and data science tooling
- you need pointers to free datasets instead of building one

## When to avoid
- you need an actively maintained tool or library
- you need a supported software dependency with a license
- you need up-to-date data sources

## Facets
- artifact type: dataset
- maturity: abandoned
- function: data-science, developer-tools
- domain: data-science, awesome-lists
- platform: cross-platform
- tags: awesome-list, open-data, curated-resources, geospatial-data, algorithms

## Member repositories
- petewarden/dstk (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:46.350972+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 2026-08-30T06:33:46.587282+00:00, confidence not recorded.
  - homepage: http://www.datasciencetoolkit.org/ (fetched 2026-08-29T12:38:45.391052+00:00, sha 0e81bcb0e506)
- Data as of 2026-08-30T08:39:29.467469+00:00.