Designing for Impact in Civic Data Science
summary
Open data portals publish raw feeds—Analyze Boston exposes 160 datasets updating daily via CSV and an API with scripts that push every four hours—yet most projects stall without a clear theory of change, sustained maintainers, or end-user buy‑in. Concrete successes include a predictive crash model for six cities (insightlane.org), a Chicago E coli forecasting model, Syracuse’s snowplow tracker, and a San Diego poverty map. Successful projects define inputs and transformation, validate outputs, secure partner adoption, and arrange paid long‑term support.
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chapters (8)
- 0:00Introduction
- 1:09Civic data science basics
- 8:51Analyze Boston overview
- 14:02Civic data challenges
- 17:13Designing for impact
- 22:03Building partnerships
- 25:09Final advice
- 28:41Q&A
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