This is the third year that the Institute of Data Science hosted the WiDS Maastricht Datathon to inspire women to learn more about data science and to create a supportive environment for women to connect with others in their community. This year the WiDS Maastricht Datathon will be held completely ONLINE, so you can join the event wherever you are in the world!

Everyone is welcome to participate in the WiDS Maastricht Datathon: Students, faculty, civil/public servants or anyone coming from the private sector. We encourage everyone to join regardless of their level of knowledge in data science! 

The WiDS Maastricht Datathon is open to individuals or teams of up to 4 participants, at least half of each team must be individuals identifying themselves as women!

WiDS Datathon Global
The WiDS Datathon is a Stanford University initiative preceding the Women in Data Science Conference (WiDS), to be held on Monday 7 March 2022. WiDS Conference Maastricht will follow on Tuesday 8 March.

WiDS aims at inspiring and educating data scientists worldwide, regardless of gender, and supporting women in the field. The WiDS Datathon builds upon these same objectives by enabling a diverse team to work together in a data-related challenge. 

Stanford University as the initiator will release a data challenge on the Kaggle platform. You can join the WiDS Datathon 2022 as an individual or with a team to tackle this data challenge competing with other teams from all over the world. Aligned with WIDS missions, we mandate at least 50% women in each participating team to encourage more women to learn data science and create a supportive environment for them.

The WiDS Datathon 2022 will address an important way to mitigate the effects of climate change with a focus on energy efficiency. Climate change is a globally relevant, urgent, and multi-faceted issue heavily impacted by energy policy and infrastructure. Addressing climate change involves mitigation (i.e. mitigating greenhouse gas emissions) and adaptation (i.e. preparing for unavoidable consequences). Mitigation of GHG emissions requires changes to electricity systems, transportation, buildings, industry, and land use. 

The WiDS Datathon 2022 dataset was created in collaboration with Climate Change AI (CCAI) and Lawrence Berkeley National Laboratory (Berkeley Lab). WiDS Datathon participants will analyze regional differences in building energy efficiency, and build models to predict building energy consumption, an important first step in understanding how to maximize energy efficiency. Accurate predictions of energy consumption can help policymakers target retrofitting efforts to maximize emissions reductions.