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The Journal of Supercomputing
Erschienen in: The Journal of Supercomputing 9/2021

17.02.2021

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

verfasst von: Jongmo Kim, Junsik Kong, Mye Sohn, Gyudong Park

Erschienen in: The Journal of Supercomputing | Ausgabe 9/2021

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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.
Vorheriger Artikel Parallel programs execution optimization using behavior control in LuNA system
Nächster Artikel Efficient data management techniques based on hierarchical IoT privacy using block chains in cloud environments

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Metadaten
Titel
Layered ontology-based multi-sourced information integration for situation awareness
verfasst von
Jongmo Kim
Junsik Kong
Mye Sohn
Gyudong Park
Publikationsdatum
17.02.2021
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 9/2021
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-021-03629-3

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