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Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature

Interdisciplinary scientific research (IDR) extends and challenges the study of science on a number of fronts, including creating output science and engineering (S&E) indicators. This literature review began with a narrow search for quantitative measures of the output of IDR that could contribut...

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Bibliographic Details
Published in:Journal of informetrics 2011, Vol.5 (1), p.14-26
Main Authors: Wagner, Caroline S., Roessner, J. David, Bobb, Kamau, Klein, Julie Thompson, Boyack, Kevin W., Keyton, Joann, Rafols, Ismael, Börner, Katy
Format: Article
Language:English
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Summary:Interdisciplinary scientific research (IDR) extends and challenges the study of science on a number of fronts, including creating output science and engineering (S&E) indicators. This literature review began with a narrow search for quantitative measures of the output of IDR that could contribute to indicators, but the authors expanded the scope of the review as it became clear that differing definitions, assessment tools, evaluation processes, and measures all shed light on different aspects of IDR. Key among these broader aspects is (a) the importance of incorporating the concept of knowledge integration, and (b) recognizing that integration can occur within a single mind as well as among a team. Existing output measures alone cannot adequately capture this process. Among the quantitative measures considered, bibliometrics (co-authorships, co-inventors, collaborations, references, citations and co-citations) are the most developed, but leave considerable gaps in understanding of the social dynamics that lead to knowledge integration. Emerging measures in network dynamics (particularly betweenness centrality and diversity), and entropy are promising as indicators, but their use requires sophisticated interpretations. Combinations of quantitative measures and qualitative assessments being applied within evaluation studies appear to reveal IDR processes but carry burdens of expense, intrusion, and lack of reproducibility year-upon-year. This review is a first step toward providing a more holistic view of measuring IDR, although research and development is needed before metrics can adequately reflect the actual phenomenon of IDR.
ISSN:1751-1577
1875-5879
DOI:10.1016/j.joi.2010.06.004