Classifying modeling and simulation as a scientific discipline
Published in Scientometrics, 2016
The body of knowledge related to modeling and simulation (M&S) comes from a variety of constituents: (1) practitioners and users, (2) tool developers and (3) theorists and methodologists. Previous work has shown that categorizing M&S as a concentration in an existing, broader disciple is inadequate because it does not provide a uniform basis for research and education across all institutions. This article presents an approach for the classification of M&S as a scientific discipline and a framework for ensuing analysis. The novelty of the approach lies in its application of machine learning classification to documents containing unstructured text (e.g. publications, funding solicitations) from a variety of established and emerging disciplines related to modeling and simulation.
Recommended citation: Gore, Ross; Diallo, Saikou; Padilla, Jose. (2016). "Classifying modeling and simulation as a scientific discipline". Scientometrics. 109, 615-628.
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