Social Impact Hub

All World Data League solutions in a single place.
World Data League was an international competition that gathered the best data scientists to solve social impact challenges. When each edition of the competition ended, we wrote a public report summarizing the best challenges' insights and results. Now, you can find it all here.
Environment
Identification of dark ecological corridors

Challenge provided by Bristol City Council

Soft Mobility
Optimization of soft-mobility drop-off points

Challenge provided by the City of Porto and Associação Porto Digital

Environment
Predicting air quality for outdoor activities

Challenge provided by Cascais Municipality

Public Transportation
Predicting people's flow for public transport improvements

Challenge provided by the City of Porto and Associação Porto Digital

Soft Mobility
Predicting the demand for shared bicycles

Challenge provided by Valle de Aburrá

Traffic
Predicting traffic flow in a city using induction loop sensors

Challenge provided by the City of Porto and Associação Porto Digital

Soft Mobility
Predicting the demand for shared bicycles

Challenge provided by Valle de Aburrá

Soft Mobility
Optimization of soft-mobility drop-off points

Challenge provided by the City of Porto and Associação Porto Digital

Traffic
Predicting traffic flow in a city using induction loop sensors

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Traffic
Patterns and predictive modeling of traffic accidents

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Traffic
Identifying patterns, explanatory factors, and prediction of irregular parking

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Traffic
Identifying road segments with potential safety hazards

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