Event highlight

Hertie School and Data Science Lab hold first Data4Good Festival

The event brings students together from across Europe to work on solutions to pressing societal issues.

A hackathon, data science workshops, and networking opportunities – all this was part of the Data4Good Festival hosted by the Hertie School and its Data Science Lab from 19 to 21 April. The event, sponsored by the Dieter Schwarz Foundation, brought together 150 students representing 50 European universities to foster creativity, collaboration, and innovative solutions to pressing societal issues using data-driven approaches.

Hackathon for the Common Good

The highlight of the Data4Good Festival was the Hackathon for the Common Good. Thirty-six teams of students competed to come up with data-based solutions to address challenges in urban innovation and migration, proposed by Technologiestiftung/CityLAB Berlin and the International Organisation for Migration. The aim of the competition was to establish a platform for young undergraduate talents to engage in a friendly and inspiring hands-on competition that promotes active learning in the field of data science and facilitates connections with their peers from partner institutions.

A jury consisting of Asya Magazinnik (Professor of Social Data Science), Simon Munzert (Professor of Data Science and Public Policy and Director of the Data Science Lab), and Niklas Kossow (Technologiestiftung Berlin) awarded prizes in three categories: 

  • Technical excellence: The first-place award went to the team ETHical from ETH Zurich, which included Simon Storf, Adam Suma, Alexander Brady, Igor Torshin, and Ajit Mistry. Their project created an interactive analysis dashboard that showcases pollution concentration across Berlin, highlighting problematic areas and utilising scraped Wikipedia articles with large language models to offer explanation and potential solutions to reduce emissions. A demo of the project can be viewed here.
  • Social impact: The first-place award went to DataWave Bodensee from the University of Constance, which included Niklas Kessler, Marina Hauger, Friederike Körte, Philipp Traber, and Martin Tran. Their project created an AI-driven media monitoring tool that gathers and automatically summarises online news sources on potential missing migrant incidents using large language models.
  • Data storytelling: The first-place award went to Forward College Haxtrordinaries from Forward College, which included Louisa Horras, Isaac Velez, Nicolette Setty, Giulia Rosa, and Victoria Lorenza Northe. Their presentation featured a data-based story of the harsh journey that many migrants have to endure to reach their destination, spotlighting the many different types of risks and potential solutions that can help to mitigate them.

Workshops and social events for networking

In addition to the main hackathon, the event also included specialised data science workshops in which data experts and practitioners in the field provided insights into data science workflow and the latest trends, best practices and technologies. The talks included a tutorial on interactive visual analytics with Tableau (Darinka Markovic, Interworks), lessons from working with the public sector (Gesa Johannsen, Polyteia), a practical application of network analysis (Dr Daniel Saldivia Gonzatti, WZB), and training on finetuning GPT models (Moritz Laurer, HuggingFace). 

The festival also served as a platform for participants to connect with like-minded peers, and mentors with social activities and games to help make lasting connections.

“The Data4Good Festival was a great opportunity for students and recent graduates to network and hone their skills to come up with data-based solutions to real-world problems,” says Simon Munzert. “We look forward to hosting the event next year!”

Visit our webpage to find out more about the Data4Good Festival and watch our recap video below.


  • Simon Munzert, Professor of Data Science and Public Policy | Director, Data Science Lab
  • Huy Ngoc Dang, Manager of Data Science Lab & Programme Coordinator of Master of Data Science for Public Policy