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A Stream Reasoning System for Maritime Monitoring.

, , , , , and . TIME, volume 120 of LIPIcs, page 20:1-20:17. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, (2018)

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Taming Big Maritime Data to Support Analytics., , , and . IF&GIS, page 15-27. Springer, (2017)Ontology-Based Data Integration for Event Recognition in the Maritime Domain., , and . WIMS, page 6:1-6:11. ACM, (2015)The datAcron Ontology for the Specification of Semantic Trajectories - Specification of Semantic Trajectories for Data Transformations Supporting Visual Analytics., , , , , , , , and . J. Data Semantics, 8 (4): 235-262 (2019)Semantics based Reconciliaton for Collaborative Ontology Evolution., and . KEOD, page 153-158. INSTICC Press, (2009)The E-SHIQ Contextual Logic Framework., and . AT, volume 918 of CEUR Workshop Proceedings, page 300-301. CEUR-WS.org, (2012)Distributed reasoning with coupled ontologies: the E-SHIQ representation framework., and . Knowl. Inf. Syst., 45 (2): 491-534 (2015)Accessing and reasoning with data from disparate data sources using modular ontologies and OBDA., , and . SEMANTiCS, page 41-48. ACM, (2015)Ontology-based data sources' integration for maritime event recognition., , and . IISA, page 1-6. IEEE, (2015)Increasing Maritime Situation Awareness via Trajectory Detection, Enrichment and Recognition of Events., , , , , , , , , and 8 other author(s). W2GIS, volume 10819 of Lecture Notes in Computer Science, page 130-140. Springer, (2018)The datAcron Ontology for Semantic Trajectories., , , , and . ESWC (Satellite Events), volume 10577 of Lecture Notes in Computer Science, page 26-30. Springer, (2017)