A new semantic trajectory ontology model for modelling and reasoning on movement data

Recently several types of research have been suggested in the last few years for modelling and analyzing raw movement data, but they mainly concentrate on studying the geometric view of raw trajectory data and do not consider the semantic facet of moving objects. Therefore, the major challenge in trajectory data modelling and reasoning is the definition of techniques to enrich raw movement data semantically. In this work, we investigate a new semantic trajectory ontology model for modelling moving objects by considering several semantic features and also reasoning on them. The model can be applied to the inference of different activity types. The reasoning mechanism is used to achieve further semantic enrichment that puts together different levels of information of the domain. The performance of the approach was tested and evaluated using a dataset, which was acquired by a user over a year in the City of Calgary