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Semantic Integration of Real-Time Heterogeneous Data Streams for Ocean-related Decision Making
Abstract and Figures
Information deluge is a continual issue in today's military environment, creating situations where data is sometimes underutilized or in more extreme cases, not utilized, for the decision-making process. In part, this is due to the continuous volume of incoming data that presently engulf the ashore and afloat operational community. However, better exploitation of these data streams can be realized through information science techniques that focus on the semantics of the incoming stream, to discover information-based alerts that generate knowledge that is only obtainable when considering the totality of the streams. In this paper, we present an agile data architecture for real-time data representation, integration, and querying over a multitude of data streams. These streams, which originate from heterogeneous and spatially distributed sensors from different IoT infrastructures and the public Web, are processed in real-time through the application of Semantic Web Technologies. The approach improves knowledge interoperability, and we apply the framework to the maritime vessel traffic domain to discover real-time traffic alerts by querying and reasoning across the numerous streams. The paper and the provided video demonstrate that the use of standards-based semantic technologies is an effective tool for the maritime big data integration and fusion tasks.
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