VESPa: A Pattern-based Visual Query Language for Event Sequences

Movement data can often be enriched with additional information that enables analysts to ask new questions, for instance about POIs visited and meetings that imply interactions between persons. Information on spatiotemporal events such as visits or meetings can be especially valuable for digital forensics, marketing analysis, and urban planning. Most existing query languages for movement data, however, do not take that additional information into account. We address this gap by proposing VESPa, a pattern-based graphical query language to express, check, and refine hypotheses about spatio-temporal event sequences. Using VESPa, the analyst can sketch abstract assumptions and use the pattern to query the data for matches. The applicability of our approach is demonstrated in two case studies with different datasets. We also report on a small user study in which several construction and comprehension tasks were successfully solved in an interactive implementation