Recent environmental disasters in the sea, have highlighted the need for efficient maritime surveillance. Currently, maritime navigation technology automatically provides real time data from vessels, that together with other historical data can be processed in an integrated way to detect complex events and support decision making. Ontology-Based Data Access (OBDA) frameworks can be employed to access data towards this effort. Integration of data is critical, but the heterogeneity and the large amount of data make this a difficult task. In this paper we present two systems that we have implemented using different OBDA frameworks, emphasizing on the semantic integration of data from disparate sources to support complex event recognition. We discuss the features of each system separately and the lessons learned from this effort.
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