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Beyond the basemap of science: mapping multiple structures in research portfolios: evidence from Hungary

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  • Sándor Soós

    (Library of the Hungarian Academy of Sciences)

  • George Kampis

    (Lorand Eötvös University)

Abstract

As a novel tool for evaluating research competences of R&D actors, science overlay maps have recently been introduced in the scientometric literature, with associated measures for assessing the degree of diversification in research profiles. In this study, we continue the elaboration of this approach: based on science overlay maps (called here m-maps), a new type of map is introduced to reveal the competence structure of R&D institutions (i-maps). It is argued, that while m-maps represent the multidisciplinarity of research profiles, i-maps convey the extent of interdisciplinarity realized in them. Upon i-maps, a set of new measures are also proposed to quantify this feature. With these measures in hand, and also as a follow-up to our previous work, we apply these measures to a sample of Hungarian Research Institutions (HROs). Based on the obtained rankings, a principal component analysis is conducted to reveal main structural dimensions of researh portfolios (of HROs) covered by these measures. The position of HROs along these dimensions then allows us to draw a typology of organizations, according to various combinations of inter- and multidisciplinarity characteristic of their performance.

Suggested Citation

  • Sándor Soós & George Kampis, 2012. "Beyond the basemap of science: mapping multiple structures in research portfolios: evidence from Hungary," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 869-891, December.
    • Handle: RePEc:spr:scient:v:93:y:2012:i:3:d:10.1007_s11192-012-0713-x
    DOI: 10.1007/s11192-012-0713-x
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    References listed on IDEAS

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    1. Kevin W. Boyack, 2009. "Using detailed maps of science to identify potential collaborations," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(1), pages 27-44, April.
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    Cited by:

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    2. We Shim & Oh-jin Kwon & Yeong-ho Moon & Keun-hwan Kim, 2016. "Understanding the Dynamic Convergence Phenomenon from the Perspective of Diversity and Persistence: A Cross-Sector Comparative Analysis between the United States and South Korea," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-29, July.
    3. Michael Calver & Kate Bryant & Grant Wardell-Johnson, 2018. "Quantifying the internationality and multidisciplinarity of authors and journals using ecological statistics," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 731-748, May.
    4. Lawson, Cornelia & Soós,Sándor, 2014. "A Thematic Mobility Measure for Econometric Analysis," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 201402, University of Turin.
    5. Sándor Soós & Zsófia Vida & András Schubert, 2018. "Long-term trends in the multidisciplinarity of some typical natural and social sciences, and its implications on the SSH versus STM distinction," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 795-822, March.
    6. Sander Zwanenburg & Maryam Nakhoda & Peter Whigham, 2022. "Toward greater consistency and validity in measuring interdisciplinarity: a systematic and conceptual evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7769-7788, December.
    7. Vilker Zucolotto Pessin & Luciana Harue Yamane & Renato Ribeiro Siman, 2022. "Smart bibliometrics: an integrated method of science mapping and bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3695-3718, June.

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