About D4GC
Why the Data 4 Good Challenge?
Data is one of the fundamentals of our society. We want to use this “oil of the digital era” to fuel new research on topics that can be used for ethical, non-profit oriented goals. We provide an interesting cocktail of crash courses provided by experienced tutors on topics that are useful, relevant, and accessible so that everyone can contribute to the project.
With the D4GC, our aim is to enrich students’ skillset with new experiences on how to analyse and process data in a meaningful manner. Furthermore we aspire to let participants work in an interdisciplinary way, such that they gain new insights from each other and learn to work in a more realistic environment.
By the numbers
Here's what we've accomplished together so far.
Previous Challenge Concepts
Opening the Black Box: Trustworthy AI for Surgical Skill Assessment, 2025
Precise and reliable skill evaluation in surgical training is essential. Yet today, many assessments remain manual, subjective, and difficult to scale. While machine learning models have opened the door to automated evaluation, their lack of transparency has slowed adoption in clinical practice.
In collaboration with Orsi Academy, the challenge aimed to bridge the gap between cutting-edge AI and clinical acceptance by developing explainable AI solutions that make surgical skill assessment both transparent and credible. Participants were tasked to design an explainable AI framework that sheds light on how automated techniques judge surgical skill.
Participants had access to a pre-trained skill classification model, along with anonymized video data and expert-annotated ratings of surgical performance to create interpretable methods.
Saving Food: Harnessing Data for a Sustainable Future, 2024
In today's world, addressing food waste is a necessity. Environmental and societal challenges call for innovative solutions to reduce food waste and redistribute surplus food to underserved communities.
In collaboration with Food Saving Leuven and Leuven Stad, students were challenged to develop a data-driven strategy to identify and address bottlenecks in the processes of the Food Saving Group, providing actionable solutions to optimize their food-saving initiatives.
Students had access to five years' worth of data on food pick-ups in Leuven, a comprehensive list of all restaurants, supermarkets, and bakeries in the area, as well as key metrics and indicators on demographics, environmental factors, and wealth distribution across Leuven.
Transforming Waste: A Data-Driven Revolution, 2023
In today’s world, effective waste management is no longer a choice it’s an imperative. We are faced with pressing environmental challenges that demand innovative solutions. This edition of D4GC, titled: “Transforming Waste: A Data-Driven Revolution”, invited the students to develop a waste management strategy that directly addresses the most critical issues today.
Students harnessed the power of data storytelling and creating waste management visualization tools. Students crafted a captivating story that delves into the challenges we face and the solutions we can implement.
Students had access to a range of valuable resources, including access to an API for an LLM-based Chatbot with access to an extensive knowledge base about recycling and waste management, data obtained from the Recycle Me App from Stad Leuven, Belgium’s recycling rules and regulations, recent blogs and articles focusing on upcycling trends, and an extensive array of indicators sourced from Belgium related to waste management. These valuable resources served as the foundation upon which students built their innovative strategy.
Urban Planning: Leuven City, 2022
Stad Leuven purchased 10 public benches to provide better infrastructure to seniors in Leuven. However, a lack of solid urban planning and covid outbreak intervened in the initiation of the bench installation.
During this challenge, students built their own data-driven urban planning to find proper locations to install the benches. The winning team’s solution was actually implemented by Leuven City.
They were provided with 4 datasets. Datasets 1 and 2 are the main datasets (Leuven demographic and location data) that you must utilize to come up with your solution. Datasets 3 and 4 (Traffic and Temperature) are publicly available and the D4GC web dashboard provided guidelines on how to utilize these data.
Adapting to climate change, 2021
During this challenge, the student’s target was to asses the risks that climate change poses under a certain scenario and figure out how we can adapt to them.
Students were provided with 5 datasets. Datasets 1 and 2 helped them in their analysis of climate change risk. Dataset 3 provided general economic and demographic data. Datasets 4 and 5 provided background information around the climate change issue that they could use to build their storyline.