Movement understanding frequently requires further information and knowledge than what can be obtained from bare spatio-temporal traces. Despite recent progress in trajectory data management, there is still a gap between the spatio-temporal aspects and the semantics involved. This gap hinders trajectory analysis benefiting from growing collections of linked data, with well-defined and widely agreed semantics, already available on the Web. This article introduces Baquara, an ontology with rich constructs, associated with a system architecture and an approach to narrow this gap. The Baquara ontology functions as a conceptual framework for semantic enrichment of movement data with annotations based on linked data. The proposed architecture and approach reveal new possibilities for trajectory analysis, using database management systems and triple stores extended with spatial data and operators. The viability of the proposal and the expressiveness of the Baquara ontology and enabled queries are investigated in a case study using real sets of trajectories and linked data.
['Renato Fileto', 'Marcelo Krüger', 'Nikos Pelekis', 'Yannis Theodoridis', 'Chiara Renso']
Baquara: A Holistic Ontological Framework for Movement Analysis Using Linked Data