M. Arru, E. Negre, C. Rosenthal-Sabroux, M. Grundstein
{"title":"Towards a responsible early-warning system: Knowledge implications in decision support design","authors":"M. Arru, E. Negre, C. Rosenthal-Sabroux, M. Grundstein","doi":"10.1109/RCIS.2016.7549288","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":344289,"journal":{"name":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Tenth International Conference on Research Challenges in Information Science (RCIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RCIS.2016.7549288","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
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.