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Enhancing Situation Awareness Using Semantic Web Technologies and Complex Event Processing

Author

Listed:
  • Havva Alizadeh Noughabi

    (University of Gonabad)

  • Mohsen Kahani

    (Ferdowsi University of Mashhad)

  • Alireza Shakibamanesh

    (Ferdowsi University of Mashhad)

Abstract

Data fusion techniques combine raw data of multiple sources and collect associated data to achieve more specific inferences than what could be attained with a single source. Situational awareness is one of the levels of the JDL, a matured information fusion model. The aim of situational awareness is to understand the developing relationships of interests between entities within a specific time and space. The present research shows how semantic web technologies, i.e. ontology and semantic reasoner, can be used to describe situations and increase awareness of the situation. As the situation awareness level receives data streams from numerous distributed sources, it is necessary to manage data streams by applying data stream processor engines such as Esper. In addition, in this research, complex event processing, a technique for achieving related situational in real-time, has been used, whose main aim is to generate actionable abstractions from event streams, automatically. The proposed approach combines Complex Event Processing and semantic web technologies to achieve better situational awareness. To show the functionality of the proposed approach in practice, some simple examples are discussed.

Suggested Citation

  • Havva Alizadeh Noughabi & Mohsen Kahani & Alireza Shakibamanesh, 2018. "Enhancing Situation Awareness Using Semantic Web Technologies and Complex Event Processing," Annals of Data Science, Springer, vol. 5(3), pages 487-496, September.
    • Handle: RePEc:spr:aodasc:v:5:y:2018:i:3:d:10.1007_s40745-018-0148-1
    DOI: 10.1007/s40745-018-0148-1
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    References listed on IDEAS

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    1. Ignatius Swart & Barry Irwin & Marthie M. Grobler, 2016. "Adaptation of the JDL Model for Multi-Sensor National Cyber Security Data Fusion," International Journal of Cyber Warfare and Terrorism (IJCWT), IGI Global, vol. 6(3), pages 17-30, July.
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    Cited by:

    1. Ashutosh, 2023. "Estimation of Domain Mean Using Conventional Synthetic Estimator with Two Auxiliary Characters," Annals of Data Science, Springer, vol. 10(1), pages 153-166, February.

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