Collection and Use of Digital Mobility Data, Challenges in Their Anonymization, and Alternative Strategies

Digital mobility data, which consist of geolocation or movement information, pose a dual challenge: they require protection under measures like the General Data Protection Regulation (GDPR) due to their personal nature, yet they hold significant value for applications such as traffic planning, smart mobility services, and retail strategies, among others. This overview article explores the conflict between the need for privacy and the potential benefits of utilizing mobility data. It provides a comprehensive overview of data collection from smartphones, mobile networks, and connected vehicles, and outlines anonymization methods: data cropping, data generalization, and data perturbation; as well as pseudonymization. The presentation of mobility data use shows that anonymization measures are often insufficient. Although anonymization is applied, two major challenges remain: first, due to their dense collection points, mobility data are highly vulnerable when being intersected with secondary datasets. Second, unique time and spatial patterns make mobility data easily backtraceable to individuals. We conclude by proposing alternative strategies, such as cryptographic pseudonymization, data sharing platforms, and data trustees, as technical and institutional solutions for privacy-preserving mobility data approaches.