We took part in the 'Data Challenge: Mobile Phone Data' by BERD@NFDI

To foster our connections within the NFDI (Nationale Forschungsdateninfrastruktur) we took part in the “Data Challenge: Mobile Phone Data” by Berd@NFDI at Ludwig Maximilian Unviersity of Munich (LMU).

During this workshop we had the opportunity to discuss with practicioners from fields like economics and social sciences on how they use mobility data, and more explicitly mobile phone data to answer reasearch questions in their applciation domain. Interestingly, questions like privacy-restrictions and the evaluation of large datasets were the main concerns there and align exactly with issues identified in our research (Mokbel et al., 2024). Further, we especially contributed with discussing our idea on trajectory anonymization (compare (Walther et al., 2024)) and developed ideas for future coollaborations with other institutes.

Resources

1. Mokbel, M., Sakr, M., Xiong, L., Züfle, A., Almeida, J., Anderson, T., Aref, W., Andrienko, G., Andrienko, N., Cao, Y., Chawla, S., Cheng, R., Chrysanthis, P., Fei, X., Ghinita, G., Graser, A., Gunopulos, D., Jensen, C. S., KIM, J.-S., … Zimányi, E. (2024). Mobility Data Science: Perspectives and Challenges. ACM Trans. Spatial Algorithms Syst. https://doi.org/10.1145/3652158 [Online]
2. Walther, P., Luo, X., & Werner, M. (2024). TraBiMap: Reducing Privacy Concerns in Trajectory Analysis with Randomized Data Representations. 2nd ACM SIGSPATIAL International Workshop on Geo-Privacy and Data Utility for Smart Societies. https://doi.org/10.1145/3681768.3698496 [PDF] [Online]