Thoughts on mobility data and privacy.

In 2021 I started working on my dissertation about privacy-preserving analytics of human mobility data. With this blog, I want to share interesting insights and useful implementations concerning mobility data and its privacy that I encounter along the way. I’m always happy about feedback, comments, or questions!

Recent blog posts

DP Mobility Report: A Python package for quick explorations and mobility data reports with privacy guarantees

Exploratory data analysis is an essential step in any data science project, as it allows us to understand the data and identify patterns, trends, and anomalies. However, exploratory analyses can often be time-consuming and repetitive. While there are existing packages for performing exploratory analyses on tabular data, e.g., ydata_profiling (formerly known as pandas_profiling) for Python,…

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Publication: Towards mobility reports with user-level privacy

Mobility data, even aggregated statistics, can usually not be shared without privacy concerns. Within this publication, my co-authors Saskia Nuñez von Voigt, Helena Mihaljević, and Florian Tschorsch and I aim to provide a report that compiles typical analyses of urban human mobility and provides privacy guarantees so that it can be shared freely. [Download paper]…

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