Treemob: Expressive Mobility Data Representation Through Tree-Based Structures

This paper explores expressive representations of personal mobility data, focusing on both informational and user-centered design aspects. The goal is to enable users to access, understand, and gain awareness of their mobility behaviours, assuming that expressiveness is not inherently linked to system complexity. We propose a novel methodology for representing and analyzing mobility data using tree-shaped structures. Additionally, we introduce Treemob, a suite of Python-based tools designed to facilitate mobility analysis. The experiments conducted provide a foundation for further research, offering a flexible framework for exploiting different issues and contexts.