Crime Forecasting Challenge : Data Science Contest

The Real-Time Crime Forecasting Challenge seeks to harness the advances in data science to address the challenges of crime and justice. It encourages data scientists across all scientific disciplines to foster innovation in forecasting methods. The goal is to develop algorithms that advance place-based crime forecasting through the use of data from one police jurisdiction.

aims to:

  1. Encourage “nontraditional” crime forecasting researchers to compete against more “traditional” crime forecasting researchers.
  2. Compare available crime forecasting methods.
  3. Improve place-based crime forecasting.

Accordingly, the Challenge will have three categories of contestants: students; individuals/small businesses; and large businesses

This Challenge will be based on the locations listed in calls-for-service (CFS) records provided by the Portland Police Bureau (PPB) for the period of March 1, 2012 through February 28, 2017


  1. Overview
  2. How to Enter
  3. Important Dates
  4. Judges
  5. Judging Criteria
  6. Prizes
  7. Other Rules and Conditions
  8. Prize Disbursement and Challenge Winners
  9. Contact Information
  10. Data for Download




Author: Ajay Ohri

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