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Insight-driven Crisis Information ? Preparing for the Unexpected using Big Data
Hendrik Stange
author
Sylvia Steenhoek
author
Sebastian Bothe
author
François Schnitzler
author
2015
University of Agder (UiA)
Kristiansand, Norway
English
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.
Big data
crisis information
incident detection
Reality Monitoring
uncertainty
exported from refbase (http://idl.iscram.org/show.php?record=1309), last updated on Mon, 09 Nov 2015 13:11:52 +0100
text
http://idl.iscram.org/files/hendrikstange/2015/1309_HendrikStange_etal2015.pdf
HendrikStange_etal2015
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management
ISCRAM 2015
L. Palen
editor
M. Buscher
editor
T. Comes
editor
A. Hughes
editor
ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management
2015
University of Agder (UiA)
Kristiansand, Norway
conference publication
9788271177881
2411-3387
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