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.
All
Environment
Public transportation
Society
Soft mobility
Traffic
Soft Mobility
(Literally) paving the way towards safer cities

Challenge provided by CycleAI

Environment
Air quality prediction in busy streets

Challenge provided by UNStudio

Society
Attracting the population to green spaces in metropolitan areas

Challenge provided by PSE

Environment
Avencas Marine Protected Area: Predict the future of the local ecosystem and its species

Challenge provided by Cascais Municipality

Public Transportation
Churn model for public transportation

Challenge provided by PSE

Public Transportation
Determining the main mobility flows in Lisbon based on mobile device data

Challenge provided by LxDataLab

Society
Energy communities inclusive of residents vulnerable to energy poverty

Challenge provided by Ghent Municipality

Environment
Identification of dark ecological corridors

Challenge provided by Bristol City Council

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

Challenge provided by Urbananalytica

Traffic
Identifying road segments with potential safety hazards

Challenge provided by PSE

Society
Improving the quality of life by reducing city noise levels

Challenge provided by the City of Torino

Soft Mobility
Missing Links - Closing the circuit in existing cycle networks

Challenge provided by U-Shift

Public Transportation
Model of integrated transport for senior citizens

Challenge provided by PSE

Public Transportation
Optimization of public transport routes during road interruptions

Challenge provided by Cascais Municipality

Soft Mobility
Optimization of soft-mobility drop-off points

Challenge provided by the City of Porto and Associação Porto Digital

Society
Optimization of the outdoor advertising within cities

Challenge provided by PSE

Traffic
Patterns and predictive modeling of traffic accidents

Challenge provided by UrbanAnalytica

Environment
Predict waste production for its reduction

Challenge provided by UrbanAI

Society
Predicting a safety score for women in Costa Rica

Challenge provided by Urbanalytica

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

Environment
Avencas Marine Protected Area: Predict the future of the local ecosystem and its species

Challenge provided by Cascais Municipality

Environment
Predicting air quality for outdoor activities

Challenge provided by Cascais Municipality

Environment
Air quality prediction in busy streets

Challenge provided by UNStudio

Environment
Predict waste production for its reduction

Challenge provided by UrbanAI

Environment
Identification of dark ecological corridors

Challenge provided by Bristol City Council

Public Transportation
Determining the main mobility flows in Lisbon based on mobile device data

Challenge provided by LxDataLab

Public Transportation
Optimization of public transport routes during road interruptions

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

Public Transportation
Churn model for public transportation

Challenge provided by PSE

Public Transportation
Model of integrated transport for senior citizens

Challenge provided by PSE

Society
Energy communities inclusive of residents vulnerable to energy poverty

Challenge provided by Ghent Municipality

Society
Improving the quality of life by reducing city noise levels

Challenge provided by the City of Torino

Society
Optimization of the outdoor advertising within cities

Challenge provided by PSE

Society
Attracting the population to green spaces in metropolitan areas

Challenge provided by PSE

Society
Predicting a safety score for women in Costa Rica

Challenge provided by Urbanalytica

Soft Mobility
Predicting the demand for shared bicycles

Challenge provided by Valle de Aburrá

Soft Mobility
Missing Links - Closing the circuit in existing cycle networks

Challenge provided by U-Shift

Soft Mobility
(Literally) paving the way towards safer cities

Challenge provided by CycleAI

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

Challenge provided by the City of Porto and Associação Porto Digital

Traffic
Patterns and predictive modeling of traffic accidents

Challenge provided by UrbanAnalytica

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

Challenge provided by Urbananalytica

Traffic
Identifying road segments with potential safety hazards

Challenge provided by PSE

World Data League - a competition for data scientists
hello@worlddataleague.com
PUBLICATIONS