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Author Hendrik Stange; Sylvia Steenhoek; Sebastian Bothe; François Schnitzler
Title Insight-driven Crisis Information ? Preparing for the Unexpected using Big Data Type Conference Article
Year 2015 Publication ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2015
Volume Issue Pages
Keywords Big data; crisis information; incident detection; Reality Monitoring; uncertainty
Abstract National information and situation centers are faced with rising information needs and the question of how to prepare for unexpected situations. One promising development is the access to vastly growing data produced by distributed sensors and a socially networked society. Current emergency information systems are limited in the amount of complex data they can process and interpret in real-time and provide only partially integrated prediction and alarming capabilities. In this paper we present a novel approach to build a new type of automated and scalable information systems that intelligently make use of massive streams of structured and unstructured data and incorporate human feedback for automated incident detection and learning. Big data technologies, uncertainty handling and privacy-by-design are employed to match end-user system requirements. We share first experiences analyzing data from the centennial flood in Germany 2013.
Address
Corporate Author Thesis
Publisher University of Agder (UiA) Place of Publication Kristiansand, Norway Editor L. Palen; M. Buscher; T. Comes; A. Hughes
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9788271177881 Medium
Track Planning, Foresight and Risk Analysis Expedition Conference ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management
Notes Approved yes
Call Number Serial 1309
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