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.
Ali Tahir. (2017) Using Open Source Tools for Spatial Temporal Querying and Knowledge Discovery from Moving Object Data, NUST Journal of Engineering Sciences , Volume 10, Issue 2.