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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(Document in English)
PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 5MB |
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 |
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Audience (journal): | International peer-reviewed journal |
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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) |
Statistics: | download |
Deposited On: | 19 Jan 2021 15:47 |
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