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The dynamics of interdisciplinary research fields: the case of river research

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Abstract

Interdisciplinarity results from dynamics at two levels. Firstly, research questions are approached using inputs from a variety of disciplinary fields. Secondly, the results of this multidisciplinary research feed back into the various research fields. This may either contribute to the further development of these fields, or may lead to disciplinary reconfiguration. If the latter is the case, a new interdisciplinary field may emerge. Following this perspective, the scientific landscape of river research and river science is mapped to assess to which current river research is a multi-disciplinary endeavor, and to which extent it results in a new emerging (inter)disciplinary field of river science. The paper suggests that this two level approach is a useful method to study interdisciplinary research and, more generally, disciplinary dynamics. With respect to river research, we show that it is mainly performed in several fields (limnology, fisheries & fish research, hydrology & water resources, and geomorphology) that hardly exchange knowledge. The different river research topics are multidisciplinary in nature, as they are shared by different fields. However, river science does not emerge as an interdisciplinary field, and often-mentioned new interdisciplinary fields such as hydroecology or hydromorphology are not (yet) visible. There is hardly any involvement of social within river research. Finally, the field of ecology occupies a central position within river research, whereas an expected engineering field is shown absent. This together may signal the acceptance of the ecosystem-based paradigm in river management, replacing the traditional engineering paradigm.

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Notes

  1. An instructive example of the resulting confusion is a study by Goldstone & Leydesdorff (2006) of cognitive science. Using betweenness centrality to measure the position of the journal Cognitive Science between computer science and cognitive psychology makes them conclude that the Cognitive Science functions as a broker between the two research fields, and that the knowledge flows between the two fields go through the journal Cognitive Science. However, the large majority of citations between the two fields are direct citations between journals in the two fields.

  2. It has been argued that in the current phase of scholarly publishing, the paper, more than the journals is the relevant unit. With direct (on line) access to articles, the journals would lose their central role in scholarly communication. If this would be the case, one would expect that journal citation networks are becoming less coherent over time. We tested this, and that does not seem to be the case. We will publish these results separately.

  3. The use of river* may lead to a bias towards large, non-wadeable river systems and may partly exclude literature on the wadeable parts of the river system more commonly associated with terms such as ‘streams’. To test, deploying ‘stream*’ as search terms resulted in a set documents that hardly overlapped (some 10 %) with the river* set. This is to a large extent because the term stream* has a much wider meaning. When restricting the stream* papers to the relevant subject areas (e.g., Environmental Sciences, Ecology, Water Resources, Marine Freshwater Biology, Oceanography, Biodiversity, Conservation, Physical Geography), the overlap increases to about 50 % of the papers.

  4. Though appearing in the factor analysis as a separate field we exclude Science Magazine, Nature and the Proceedings of the National Academies of Science from most of the further analysis of river science. These three journals have an explicit broad multi-disciplinary scope and are heavily cited by all fields, and that puts them together in a factor. However, they cannot be considered as representing a distinct research field.

  5. The nodes of the network are papers and the ties between papers are based on shared word-reference combinations: Title word A, B to N are combined with cited reference 1, 2 to x to form A1, A2, …. Ax, B1, B2, ….., Bx… Nx. Similarity between papers depends on the number of shared combinations.

  6. For a more detailed explanation of clustering algorithms in general, see Palla et al (2005). For a comparative analysis of Blondel et al’s algorithm versus others’ see Lancichinetti and Fortunato (2009).

  7. Please note that this is a two dimensional map of a multidimensional space. The projection influences the distances between the fields on the map.

  8. We used an automated search on the following search terms and derivatives (based on an inspection of the title words frequency distribution): agencies, cost, decision, development, economic, institution, learning, management, participant, place, planning, policy, public, social, socio, stakeholder, strategy, sustainability, user. The remaining topics were manually and visually checked.

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Acknowledgments

This study has been partly financed by the Interdepartmental Institute Science and Society of the Radboud University Nijmegen (grant W&S 2004-04), and by the Kennis voor Klimaat (Knowledge for Climate) program. Thanks to Mieke van Hemert for providing input when discussing the set up of the project, to André Somers for assistance with the SAINT Toolbox, to Jan Hendriks, Rob Leuven and two anonymous reviewers for providing valuable comments on earlier drafts.

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Authors and Affiliations

  1. Department of Environmental Science, Radboud University, Heyendaalseweg 135, 6525 AJ, Nijmegen, The Netherlands

    Pim Vugteveen & Rob Lenders

  2. Department of Organization Sciences & Network Institute, VU University Amsterdam, Buitenveldertselaan 3, 1081 HV, Amsterdam, The Netherlands

    Peter Van den Besselaar

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  1. Pim Vugteveen
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Correspondence to Peter Van den Besselaar.

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Vugteveen, P., Lenders, R. & Van den Besselaar, P. The dynamics of interdisciplinary research fields: the case of river research. Scientometrics 100, 73–96 (2014). https://doi.org/10.1007/s11192-014-1286-7

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