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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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