Abstract
The Emergency Response Operations Management (EROM) Literature Sample is a collection of 644 papers winnowed from over 5,000 related articles through application of a binary classification tree, collecting the state-of-the-art in decision models of emergencies in progress. References are scraped from each of these 644 publications, to create a dataset describing a total of 14,821 papers linked by 23,175 citation relationships, the analysis of which is presented in, “Modeling Emergency Response Operations: A Theory Building Survey” in Computers and Operations Research[1]. Bibliographic research communities are identified within the data set by framing the task of network partitioning as a cluster ensemble problem from machine learning [2]. This data may be used in several ways, including as an extended reference section for [1], as all 644 papers studied could not be individually cited there. Other examples of potential reuse are further study of a particular research cluster, comparative study of the structural characteristics of this bibliographic network with literature in other fields, and as a test-bed for the further development of robust clustering algorithms.
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