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Towards a responsible Early-Warning System: knowledge implications in decision support design

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Date
2016
Dewey
Recherche opérationnelle
Sujet
Information and Knowledge Systems; Knowledge Integration; Early-Warning Systems; Decision Support; Fire Safety
DOI
http://dx.doi.org/10.1109/RCIS.2016.7549288
Conference name
10th International Conference on Research Challenges in Information Science (RCIS)
Conference date
06-2016
Conference city
Grenoble
Conference country
France
Book title
IEEE 10th International Conference on Research Challenges in Information Science (RCIS) - Proceedings
Publisher
IEEE Press
Year
2016
ISBN
978-1-4799-8711-5
URI
https://basepub.dauphine.fr/handle/123456789/15920
Collections
  • LAMSADE : Publications
Metadata
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Author
Arru, Maude
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Negre, Elsa
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Rosenthal-Sabroux, Camille
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Grundstein, Michel
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Type
Communication / Conférence
Item number of pages
12 p.
Abstract (EN)
Warnings can help prevent damage and harm if they are issued timely and provide information that help responders and population to adequately prepare for the disaster to come. Today, there are many indicator and sensor systems that are designed to reduce disaster risks, or issue early-warnings. In a socially and environmentally responsible word, we need effective Early-Warning Systems (EWS). EWS are Information and Knowledge Systems dedicated to protect people against disasters damages. Such systems are designed to integrate data, information and knowledge from various sources and actors who do not usually interact to issue early-warnings. This paper introduces knowledge implications in EWS decision support design in general, with a discussion on communication processes between data, information and knowledge. We propose a knowledge-oriented vision of EWS elements to examine existing systems and provide dynamic and flow-oriented models. In this perspective, we analyze knowledge integration processes in the design of the fire safety system of our University.

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