Yan, ZhixianSpremic, LazarChakraborty, DipanjanParent, ChristineSpaccapietra, StefanoAberer, Karl2010-11-042010-11-042010-11-04201010.1145/1869790.1869879https://infoscience.epfl.ch/handle/20.500.14299/56669With the prevalence of GPS-embedded mobile devices, enormous amounts of mobility data are being collected in the form of trajectory - a stream of (x,y,t) points. Such trajectories are of heterogeneous entities - vehicles, people, animals, parcels etc. Most applications primarily analyze raw trajectory data and extract geometric patterns. Real-life applications however, need a far more comprehensive, semantic representation of trajectories. This paper demonstrates the automatic construction and visualization capabilities of SeMiTri - a system we built that exploits 3rd party information sources containing geographic information, to semantically enrich trajectories. The construction stack encapsulates several spatio-temporal data integration and mining techniques to automatically compute and annotate all meaningful parts of heterogeneous trajectories. The visualization interface exhibits different levels of data abstraction, from low-level raw trajectories (i.e. the initial GPS trace) to high-level semantic trajectories (i.e. the sequence of interesting places where moving objects have passed and/or stayed).semantic trajectoriesNCCR-MICSNCCR-MICS/ESDMtext::conference output::conference proceedings::conference paper