Big Data and Emergency Management: A Scientometric Approach to Understanding an Interdisciplinary Domain

Authors: André Skupin*, San Diego State University
Topics: Hazards, Risks, and Disasters, Geographic Information Science and Systems
Keywords: emergency management, big data, network analysis, knowledge visualization, scientometrics, bibliometrics
Session Type: Paper
Day: 4/10/2018
Start / End Time: 10:00 AM / 11:40 AM
Room: Napoleon D1, Sheraton 3rd Floor
Presentation File: No File Uploaded

Funded by the Research Council of Norway (RCN) and the Norwegian Centre for International Cooperation in Education (SiU), the "Transnational Partnership for Excellent Research and Education in Big Data and Emergency Management" (BDEM) is a multi-year effort to share best practices and strengthen research and training cooperation among a core group of leading institutions in Norway, Japan, Hong Kong, and the United States. As a founding member of the BDEM consortium, the Center for Information Convergence and Strategy (CICS) at San Diego State University took on the initial challenge of characterizing the relationship between big data and emergency management. This is a difficult endeavor, since they spring from fundamentally different intellectual lineages and societal contexts. For example, there is innate tension between the technological capabilities and well-meaning ambitions of BD experts and the real-world needs and constraints of EM practitioners.

The paper presents results of a detailed scientometric analysis of the BDEM domain. A corpus of more than 10,000 publications was transformed into several co-occurrence networks, followed by computation of network centrality measures, pruning of network links and eventual visualization. This analysis leads to the delineation of major structures in scientific discourse within and among the BD and EM communities, identifying backbone structures, key linkages, and temporal trends. Making these structures explicit can help educators in curriculum design and allow multidisciplinary teams to improve methodological and epistemological clarity.

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