Knowledge Integration and Diffusion: Measures and Mapping of Diversity and Coherence

Ràfols, Ismael

doi:10.1007/978-3-319-10377-8_8

Cited by 44 publications

(51 citation statements)

References 57 publications

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“…The main contribution comes from Rafols and colleagues (e.g. Rafols & Meyer, 2010, Rafols et al, 2012Rafols, 2014). A theoretical framework is needed in order to outline the dimensions of interdisciplinarity and relations between attributes.…”

Section: Attributes Of Interdisciplinary Researchmentioning

confidence: 99%

Consistency and validity of interdisciplinarity measures

Schneider

2020

Quantitative Science Studies

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Assessing interdisciplinarity is an important and challenging work in bibliometric studies. Previous studies tend to emphasize that the nature and concept of interdisciplinary is ambiguous and uncertain (e.g. Leydesdorff & Rafols 2010, Rafols & Meyer, 2010, Sugimoto & Weingart, 2014. As a consequence, various different measures of interdisciplinarity have been proposed. However, few studies have examined the relations between these measures. In this context, this paper aims to systematically review these interdisciplinarity measures, and explore their inherent relations. We examine these measures in relation to the Web of Science (WoS) journal subject categories (SCs), and also an interdisciplinary research center at Aarhus University. In line with the conclusion of Digital Science (2016), our results reveal that the current situation of interdisciplinarity measurement in science studies is confusing and unsatisfying. We obtained surprisingly dissimilar results with measures that supposedly should measure similar features. We suggest that interdisciplinarity as a measurement construct should be used and interpreted with caution in future research evaluation and research policies.

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Section: Attributes Of Interdisciplinary Researchmentioning

confidence: 99%

Consistency and validity of interdisciplinarity measures

Schneider

2020

Quantitative Science Studies

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“…It is equivalent to the empirical approach of measuring "Integration" devised in support of evaluation efforts for the US National Academies Keck Futures Initiative (Porter, Roessner, & Heberger, 2008). Rafols (2014) treats various measures of diversity and coherence. Of note are recent efforts to measure variety, balance, and disparity separately (Wang, Thijs, & Glänzel, 2014;Yegros-Yegros et al, 2010;Yegros-Yegros, Rafols, & d'Este, 2015).…”

Section: Research Papermentioning

confidence: 99%

Measuring and Visualizing Research Collaboration and Productivity

Garner

Porter

Leidolf

et al. 2018

Journal of Data and Information Science

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Purpose This paper presents findings of a quasi-experimental assessment to gauge the research productivity and degree of interdisciplinarity of research center outputs. Of special interest, we share an enriched visualization of research co-authoring patterns. Design/methodology/approach We compile publications by 45 researchers in each of 1) the iUTAH project, which we consider here to be analogous to a “research center,” 2) CG1— a comparison group of participants in two other Utah environmental research centers, and 3) CG2—a comparison group of Utah university environmental researchers not associated with a research center. We draw bibliometric data from Web of Science and from Google Scholar. We gather publications for a period before iUTAH had been established (2010–2012) and a period after (2014–2016). We compare these research outputs in terms of publications and citations thereto. We also measure interdisciplinarity using Integration scoring and generate science overlay maps to locate the research publications across disciplines. Findings We find that participation in the iUTAH project appears to increase research outputs (publications in the After period) and increase research citation rates relative to the comparison group researchers (although CG1 research remains most cited, as it was in the Before period). Most notably, participation in iUTAH markedly increases co-authoring among researchers—in general; and for junior, as well as senior, faculty; for men and women: across organizations; and across disciplines. Research limitations The quasi-experimental design necessarily generates suggestive, not definitively causal, findings because of the imperfect controls. Practical implications This study demonstrates a viable approach for research assessment of a center or program for which random assignment of control groups is not possible. It illustrates use of bibliometric indicators to inform R&D program management. Originality/value New visualizations of researcher collaboration provide compelling comparisons of the extent and nature of social networking among target cohorts.

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“…Also, as illustrated in the right side of Figure 2, coherence can increase when the number of relations increases (density), when the relations become stronger (intensity), or when they link more different categories (disparity) (Rafols 2014). Stirling (1998) and Rafols (2014).…”

Section: Operationalization Of Breadth and Integrationmentioning

confidence: 99%

“…Likewise, any measure of coherence makes an implicit choice of the relative weight of density, intensity, and disparity. Following Stirling (2007), we have proposed generalized heuristics and measures for exploring diversity and coherence as shown in Table 2 and discussed in Rafols (2014).…”

Section: Intensity Of Relations Between Categories I and J: Iijmentioning

confidence: 99%

Interdisciplinarity in Research Evaluation

Huutoniemi

Ràfols

2017

The Oxford Handbook of Interdisciplinarity

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The evaluation of interdisciplinary research is complicated by ambiguity about what interdisciplinarity is and what it should be. The question is topical, as evaluation plays an important role in how science is being shaped and changed today. The chapter performs a meta-analysis of the concept of interdisciplinarity in research evaluation, and gives an epistemic account of what would be involved in such evaluations. First, it discusses the various ways interdisciplinarity can add value to the disciplinary organization of academia and their respective implications for research evaluation. Second, it provides tools for mapping and measuring these value-added properties and illustrates what kind of evidence they can convey to research evaluations. The combined examination of values and indicators enables a more differentiated understanding of what exactly to look at when evaluating interdisciplinary research—and more generally, how to design research evaluations from an interdisciplinary point of view.

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Knowledge Integration and Diffusion: Measures and Mapping of Diversity and Coherence

Cited by 44 publications

References 57 publications

Consistency and validity of interdisciplinarity measures

Consistency and validity of interdisciplinarity measures

Measuring and Visualizing Research Collaboration and Productivity

Interdisciplinarity in Research Evaluation

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