Challenges of Spatio-Temporal Trajectory Data Use: Focus Group Findings from the 1st International Summer School on Data Science for Mobility

Abstract

The fast development of wireless location acquisition technologies has led to a significant increase in the availability of mobility data, specifically spatio-temporal trajectory data, which includes information about the movements (locations) of objects over time. This data has proven valuable for a wide range of applications, including predicting travel patterns, discovering routes, analyzing social interactions, and managing resources in urban environments. However, using trajectory datasets can also be challenging, particularly in different countries. This article aims to explore the challenges of using trajectory datasets, specifically using focus group discussions. Focus groups are a qualitative method of gaining a deeper understanding of a particular topic and have not been previously used to examine the challenges related to trajectory datasets. The information gathered through these discussions is augmented by a review of existing literature for a comprehensive understanding of data challenges.