IARPA launches Mercury Challenge

 IARPA

IARPA

In an effort to provide early warning capabilities, the Department of Defense’s Integrated Crisis Early Warning System (ICEWS) and IARPA’s Open Source Indicators (OSI) programs want to leverage novel statistical and machine learning techniques using publicly available data sources to forecast societal such as civil unrest and disease outbreaks with a high degree of accuracy.

Participants are encouraged to develop and test innovative forecasting methods that ingest and process publicly available data sources to predict Military Activity, Non-violent Civil Unrest, and Infectious Disease in specific places of interest.

Participant forecasts will be scored across a three-month rolling window. Every month, IAPRA will score those participants who have sent forecasts for three consecutive months. Scoring will be based on four metrics including forecast lead time, location accuracy, date accuracy, and facet actor/event-type matching.

 

CHALLENGE DOCUMENTS

 

Technologists, data scientists, and machine learning engineers who are skilled at breaking down complex data are encouraged to join. Individuals ranging from private industry and academia are all eligible to participate and win prizes. The Mercury Challenge Team believes success in this challenge can prove to be a strong addition to any data science practitioner’s portfolio.