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Knowledge Integration: Its Meaning and Measurement

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Book cover Springer Handbook of Science and Technology Indicators

Part of the book series: Springer Handbooks ((SHB))

Abstract

Interdisciplinary research depends on research traditions and fields originating from different research teams, different countries and regions. Its essence is knowledge integration. As a dynamic and interactive process it continuously pushes the structure of science to become a complex diverse system.

In this chapter, we provide a systematic review of interdisciplinary research. Starting from a definition of interdisciplinary research, its elements, and its role for scientific progress, we particularly focus on how to identify the activity of interdisciplinary research, how to measure it and point out the limitations of existing approaches. Stating that one can measure knowledge integration implies that this notion refers to a continuum, beginning from no integration (disciplinary research) to a large degree of integration (highly interdisciplinary).

Following Stirling, Rafols and Meyer we show that knowledge integration can be measured by two main factors: a diversity factor and a network coherence factor. The diversity factor itself consists of three aspects: variety (number of categories taken into account), evenness and similarity between categories. In accordance with the Jost–Leinster–Cobbold approach we prefer a so-called true diversity measure.

As an illustration, we provide a simple example of a study on interdisciplinarity in the field of synthetic biology, using the true diversity measure derived from the Rao–Stirling measure. Finally, we include some suggestions for future research.

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Acknowledgements

Lin Zhang acknowledges support from the National Natural Science Foundation of China Grant 71573085. Xiaojun Hu and Ronald Rousseau acknowledge support from the National Natural Science Foundation of China Grant 71573225. We further thank Loet Leydesdorff and Raf Guns for useful comments.

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Authors and Affiliations

  1. ECOOM, KU Leuven, Leuven, Belgium

    Ronald Rousseau

  2. School of Information Management, Wuhan University, Wuhan, China

    Lin Zhang

  3. School of Basic Medical Sciences, Zhejiang University, Hangzhou, China

    Xiaojun Hu

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  1. Ronald Rousseau
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  2. Lin Zhang
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  3. Xiaojun Hu
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Correspondence to Ronald Rousseau .

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Editors and Affiliations

  1. ECOOM and Faculty of Economics and Business, KU Leuven, Leuven, Belgium

    Wolfgang Glänzel

  2. Amsterdam, The Netherlands

    Henk F. Moed

  3. Competence Center Policy – Industry – Innovation, Fraunhofer Institute for Systems and Innovation Research ISI, Karlsruhe, Germany

    Ulrich Schmoch

  4. Faculty of Science and Engineering, University of Wolverhampton, Wolverhampton, UK

    Mike Thelwall

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Rousseau, R., Zhang, L., Hu, X. (2019). Knowledge Integration: Its Meaning and Measurement. In: Glänzel, W., Moed, H.F., Schmoch, U., Thelwall, M. (eds) Springer Handbook of Science and Technology Indicators. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-030-02511-3_3

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