Istituto di Scienza e Tecnologie dell'Informazione     
Fileto R., Cleto M., Renso C., Pelekis N., Klein D., Theodoridis Y. The Baquara2 knowledge-based framework for semantic enrichment and analysis of movement data. In: Data & knowledge engineering, vol. 98 pp. 104 - 122. Elsevier, 2015.
The analysis of movements frequently requires more than just spatio-temporal data. Thus, despite recent progresses in trajectory handling, there is still a gap between movement data and formal semantics. This gap hinders movement analyses benefiting from available knowledge, with well-defined and widely agreed semantics. This article describes the Baquara2 framework to help narrow this gap by exploiting knowledge bases to semantically enrich and analyze movement data. It provides an ontological model for structuring and abstracting movement data in a multilevel hierarchy of progressively detailed movement segments that generalize concepts such as trajectories, stops, and moves. Baquara2 also includes a general customizable process to annotate movement data with concepts and objects described in ontologies and Linked Open Data (LOD) collections. The resulting semantic annotations enable queries for movement analyses based on application and domain specific knowledge. The proposed framework has been used in experiments to semantically enrich movement data collected from social media with geo-referenced LOD. The obtained results enable powerful queries that illustrate Baquara2 capabilities.
URL: http://www.sciencedirect.com/science/article/pii/S0169023X15000555
DOI: 10.1016/j.datak.2015.07.010
Subject Trajectories of moving objects
Social media
Linked open data
Semantic enrichment
Movement data analysis

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