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Real-time data exploitation supported by model- and event-driven architecture to enhance situation awareness, application to crisis management

Fertier, Audrey and Montarnal, Aurélie and Barthe, Anne-Marie and Truptil, Sébastien and Bénaben, Frédérick Real-time data exploitation supported by model- and event-driven architecture to enhance situation awareness, application to crisis management. (2019) Enterprise Information Systems, 14 (6). 769-796. ISSN 1751-7575

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Official URL: https://doi.org/10.1080/17517575.2019.1691268

Abstract

An effective crisis response requires up-to-date information. The crisis cell must reach for new, external, data sources. However, new data lead to new issues: their volume, veracity, variety or velocity cannot be managed by humans only, especially under high stress and time pressure. This paper proposes (i) a framework to enhance situation awareness while managing the 5Vs of Big Data, (ii) general principles to be followed and (iii) a new architecture implementing the proposed framework. The latter merges event-driven and model-driven architectures. It has been tested on a realistic flood scenario set up by official French services.

Item Type:Article
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Ecole nationale supérieure des Mines d'Albi-Carmaux - IMT Mines Albi (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
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Funders:
Agence Nationale pour la Recherche (ANR)
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Deposited On:19 Jan 2021 15:47

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