Eine verschwommene Ansicht vieler Menschen, die über einen Zebrastreifen laufen.
© Be_Me, Pixabay

Note on the project!

This project is finished.

  • Theme New Technologies
  • Theme Field Tests

freemove

The freemove project is used for transdisciplinary research into movement data in awareness of privacy issues for sustainable urban mobility.


Target group
Science and research, public administration
Topic
New Technologies, Field Tests
Running time
May 2021 – June 2024

Privacy-Centered Urban Mobility Data

In the next three years, the aim of the project is to develop a scientifically sound framework that specifies the requirements for a fair, useful, secure and comprehensible provision of movement data for public and private users.

freemove is a transdisciplinary project for research into mobility data funded by the Federal Ministry of Education and Research. The research group combines the skills of university and practical partners in the areas of machine learning, digital self-determination, human-centered computing and information security.

On the scientific side, the project team is provided by the departments of the Berlin School of Economics and Technology, the Free University of Berlin, the Technical University of Berlin and the Berlin University of the Arts. The practice-oriented partners of the German Aerospace Center and the Technologiestiftung Berlin expand this scientific perspective with a focus on questions of implementation and stakeholder involvement.

The freemove project ended in June 2024. We would like to thank all contributors, workshop participants and helpers! The project page will remain online, as will the tools created. We continue to welcome feedback and answer your questions at info@technologiestiftung-berlin.de.

Project results

In addition to scientific publications, the consortium has also generated a number of results in the form of usable tools as part of the project.

  1. Step-by-step guide to anonymizing movement data while respecting its context in the form of a website
  2. Python package for privacy-preserving analysis of motion data with differential privacy guarantees
  3. Interactive website to explain privacy risks in the area of mobility data


We look forward to their numerous use and dissemination, and to feedback!

In corporation with:

Funded by: