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Emerging Perspectives in Big Data Warehousing
Mobility data became an important paradigm for computing performed in various areas. Mobility data is considered as a core revealing the trace of mobile objects displacements. While each area presents a different optic of trajectory, they aim to support mobility data with domain knowledge. Semantic annotations may offer a common model for trajectories. Ontology design patterns seem to be promising solutions to define such trajectory related pattern. They appear more suitable for the annotation of multiperspective data than the only use of ontologies. The trajectory ontology design pattern will be used as a semantic layer for trajectory data warehouses for the sake of analyzing instantaneous behaviors conducted by mobile entities. In this chapter, the authors propose a semantic approach for the semantic modeling of trajectory and trajectory data warehouses based on a trajectory ontology design pattern. They validate the proposal through real case studies dealing with behavior analysi...
The enormous evolution of positioning technologies and remote sensors is leading to big amounts of disparate mobility data. Collected mobility data generates the need of modelling of such behaviour and the understanding of them which gave the rise of different models achieved either by classical conceptual modelling or by those based on ontology. Modelling and analysing trajectory data are still challenging because of the heterogeneity of trajectory data models and the complexity of establishing choices about domain's consensual knowledge. To fulfil this objective, we propose a generic ontology that explains the semantics of these data and we define a trajectory data warehouse conceptual model based on the shared ontology in order to analyse trajectory data going from users' short transactions to complex queries involving decision makers. The shared ontology that we propose is an OWL-DL formalism that covers common structures encountered in trajectories.We illustrate our work with a real case study.
2008 •
In this paper we present a methodology for the semantic enrichment of trajectories. The objective of this process is to provide a semantic interpretation of a trajectory in term of behaviour. This has been achieved by enhancing raw trajectories with semantic information about moves and stops and by exploiting some domain knowledge encoded in an ontology. Furthermore, the reasoning mechanisms provided by the OWL ontology formalism have been exploited to accomplish a further semantic enrichment step that puts together the different levels of knowledge of the domain. A final example application shows the added power of the enrichment process in characterizing people behaviour.
Proceedings of the 17th International Workshop on Data Warehousing and OLAP - DOLAP '14
A Semantic Model for Movement Data Warehouses2014 •
ACM Computing Surveys
Semantic trajectories modeling and analysis2013 •
Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application. This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This survey provides the definitions of the basic concepts about mobility data, an analysis of the issues in mobility data management, and a survey of the approaches and techniques for: (i) constructing trajectories from movement tracks, (ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and (iii) using data mining to analyze semantic trajectories and extract knowledge about their characteristics, in particular the behavioral patterns of the moving objec...
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