The DFG-funded RUSHMORE project explores innovative methods for generating synthetic mobility data and supports research with FAIR-compliant data services.
Understanding mobility behaviour – such as traffic flows, cycling and public transport use – is a key challenge for scientists, urban planners and policymakers. However, valuable mobility data is often regionally and temporally limited. RUSHMORE (Resources for Human Mobility Research) aims to fill this data gap by generating synthetic data and developing transferable machine learning models. The goal is to provide a publicly accessible data service based on the FAIR principles (Findable, Accessible, Interoperable, Reusable).
The project started in February 2025 and will run until January 2028. Besides L3S, the University of Bonn, Heinrich-Heine-University Düsseldorf, and GESIS – Leibniz Institute for the Social Sciences are involved. The project is coordinated by Dr. Simon Gottschalk of L3S.
Click here to visit the project website.
