Abstract
This paper presents the design of an ontology for the representation of enriched semantic trajectories in the maritime domain. The ontology supports vessel trajectories, at different levels of detail, enriched with vessel characteristics, weather information and events, as well as topological and proximity relations to geographical areas of interest (such as ports and protected areas). The paper describes how raw data from diverse data sources are integrated in order to produce enriched semantic trajectories, represented as linked data in RDF, in compliance with the proposed ontology. Moreover, the added-value of the ontology is demonstrated by means of semantic queries that retrieve information about moving vessels and their trajectories using complex criteria. The linked data and our ontology are publicly available as five star linked open data, offering a valuable resource to the research community.
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Acknowledgment
This work was supported by the Horizon 2020 Framework Programme of the European Union under grant agreement No 957237 (project VesselAI).
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M. Santipantakis, G., Doulkeridis, C., A. Vouros, G. (2023). An Ontology for Representing and Querying Semantic Trajectories in the Maritime Domain. In: Abelló, A., Vassiliadis, P., Romero, O., Wrembel, R. (eds) Advances in Databases and Information Systems. ADBIS 2023. Lecture Notes in Computer Science, vol 13985. Springer, Cham. https://doi.org/10.1007/978-3-031-42914-9_16
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