Ontology-based data sources' integration for maritime event recognition

Georgios M. Santipantakis, Konstantinos I. Kotis, G. Vouros
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引用次数: 2

Abstract

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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基于本体的数据源集成海事事件识别
最近发生在海上的环境灾难凸显了对有效的海上监视的需要。目前,海上导航技术可以自动提供船舶的实时数据,这些数据可以与其他历史数据一起进行综合处理,以检测复杂事件并支持决策。可以使用基于本体的数据访问(OBDA)框架来访问数据。数据的集成是至关重要的,但是数据的异构性和大量的数据使这一任务变得困难。在本文中,我们介绍了使用不同OBDA框架实现的两个系统,强调来自不同来源的数据的语义集成,以支持复杂事件识别。我们将分别讨论每个系统的特性以及从中获得的经验教训。
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