Developing situation-aware applications for disaster management with a distributed rule-based platform

João Moreira, Joao Moreira, Luis Ferreira Pires, Marten J. van Sinderen, P. Dockhorn Costa

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    Abstract

    In order to enhance interoperability and productivity in the develop-ment of situation-aware applications for disaster management, proper mecha-nisms and guidelines are required. They must address the lack of semantics in modelling emergency situations. In addition, the ever changing and unpredicta-ble nature of disaster scenarios present challenges for information processing and collaboration. This paper proposes a framework that combines the follow-ing elements: (i) a foundational ontology for temporal conceptualization; (ii) well-founded specifications of structural and behavioral models; (iii) a CEP en-gine based on a distributed rule-based platform for situation management; (iv) a model-driven approach. We illustrate the operation of the framework with a scenario for monitoring tuberculosis epidemy.
    Original languageUndefined
    Title of host publicationProceedings of the RuleML 2015 Challenge, Special Track on Rule-based Recommender Systems for the Web of Data, Special Industry Track, and RuleML 2015 Doctoral Consortium
    Place of PublicationAachen
    PublisherCEUR
    Pages-
    Number of pages6
    Publication statusPublished - 2015

    Publication series

    NameCEUR Workshop Proceedings
    PublisherCEUR-WS.org
    Volume1417
    ISSN (Print)1613-0073

    Keywords

    • SCS-Services
    • EWI-26313
    • Disaster Management
    • METIS-312726
    • Situation-aware application
    • IR-97411
    • Context-aware application
    • Rule-based platform

    Cite this

    Moreira, J., Moreira, J., Ferreira Pires, L., van Sinderen, M. J., & Dockhorn Costa, P. (2015). Developing situation-aware applications for disaster management with a distributed rule-based platform. In Proceedings of the RuleML 2015 Challenge, Special Track on Rule-based Recommender Systems for the Web of Data, Special Industry Track, and RuleML 2015 Doctoral Consortium (pp. -). (CEUR Workshop Proceedings; Vol. 1417). Aachen: CEUR.