Layered ontology-based multi-sourced information integration for situation awareness

Abstract

Data and information produced in network-centric environments are large and heterogeneous. As a solution to this challenge, ontology-based situation awareness (SA) is gaining attention because ontologies can contribute to the integration of heterogeneous data and information produced from different sources and can enhance knowledge formalization. In this study, we propose a novel method for enhancing ontology-based SA by integrating ontology and linked open data (LOD) called a multi-layered SA ontology and the relations between events in the layer. In addition, we described the characteristics and roles of each layer. Finally, we developed a framework to perform SA rapidly and accurately by acquiring and integrating information from the ontology and LOD based on the multi-layered SA ontology. We conducted three experiments to verify the effectiveness of the proposed framework. The results show that the performance of the SA of our framework is comparable to that of domain experts.