Abstract

Disasters have long been a scourge for humanity. With the advances in technology (in terms of computing, communications, and the ability to process, and analyze big data), our ability to respond to disasters is at an inflection point. There is great optimism that big data tools can be leveraged to process large amounts of crisis-related data (in the form of user generated data in addition to traditional humanitarian data) to provide an insight into the fast-changing situation and help drive an effective disaster response. This article introduces the history and the future of big crisis data analytics, along with a discussion on its promise, enabling technologies, challenges, and pitfalls.

Details

Title
Crisis analytics: big data-driven crisis response
Author
Qadir Junaid 1 ; Anwaar, Ali 1 ; ur, Rasool Raihan 2 ; Zwitter Andrej 3 ; Sathiaseelan Arjuna 4 ; Crowcroft, Jon 4 

 Information Technology University (ITU), Electrical Engineering Department, Lahore, Pakistan (GRID:grid.497892.9) (ISNI:0000 0004 4691 9610) 
 King Faisal University, Hofuf, Kingdom of Saudi Arabia (GRID:grid.412140.2) (ISNI:0000000417559687) 
 University of Groningen, Groningen, Netherlands (GRID:grid.4830.f) (ISNI:0000000404071981) 
 University of Cambridge, Computer Laboratory, Cambridge, UK (GRID:grid.5335.0) (ISNI:0000000121885934) 
Publication year
2016
Publication date
Dec 2016
Publisher
Springer Nature B.V.
ISSN
23643412
e-ISSN
23643404
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2429904827
Copyright
© Qadir et al. 2016. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.