Semantic Aspects on Mobility Data

Abstract

The bang of mobility data (due to the evolution of positioning devices such as GPS-enabled smartphones and tablets, on-board navigation systems in vehicles, vessels and planes, smart chips embedded in animals, etc.) has an equal share in what is called the BIG DATA era that raises important issues for Moving Object Databases (MOD) and Trajectory Data Warehouses (TDW), which are responsible for the operational and analytical, respectively, processing of moving object trajectories. A reasonable question that arises, is whether we really need all this detailed (i.e., point-by-point) information in order to perform the above processing effectively (i.e., having advanced mobile-aware applications and services in mind)? Trying to address this question, during the recent years mobility data are accompanied by semantic information (such as diaries filled in manually by citizens for urban transportation research purposes). In a different scenario, semantic information may be inferred by methods taking into account contextual information from the underlying application scenario. Thus, the answer to the above question may be simple: extract and manage (the necessary) semantics from movement and provide services and applications that are built upon them. In this chapter, we first present the background knowledge that allows us to swift the paradigm from raw trajectories to their semantic counterpart, and, subsequently, we study several methods that support a step-by-step methodology towards the reconstruction of the semantically enriched trajectories. The previous reflect the majority of the approaches that have been pursued in the literature, which tackle the raised issues from a conceptual point of view. Then, we go one step further by providing a blueprint of a prototype framework for designing and building real-world semantic-aware MODs and TDWs. Finally, we discuss the semantic aspects of privacy as an orthogonal dimension to the aforementioned techniques.