Abstract
Geospatial information overload has become an issue in recent years. It is fuelled in part by the widespread availability of mobility data from a variety of sources, such as ubiquitous mobile computing devices, geographic positioning systems and traces from digital map interactions. The article describes a data analysis technique for extracting knowledge from mobility data. Data from mouse movements over digital maps were analysed for their spatial-temporal content to reveal user behavior. Although the trajectories are from mouse movements in Human-Computer Interaction domain, they can also serve as a proxy for physical trajectories in the real world. The article presents the methodology to reduce information overload and convert raw trajectory data into useful knowledge. This geographicknowledgediscoveryprocesswasrealisedusing Secondo, a highly specialised open source tool that allows developingspecific spatio-temporalqueriestoanalysetrajectories. The results indicate that Secondo can be intelligently exploited for identifying specific movement patterns and behavior and ultimately extractknowledgewhichcanbeusedinpersonalisedwebmaps,spatial recommender systems, event detection and crime monitoring tasks.
