2009/01/10 by Ismael Ràfols, Martin Meyer, Rafols, Ismael +1 · 2 citations
Biochemistry, Genetics and Molecular Biology · Decision Sciences · #Bioinformatics and Genomic Networks #Data Analysis #FOS: Physical sciences #Interdisciplinary Research and Collaboration #Physics and Society (physics.soc-ph) #Statistics and Probability (physics.data-an) #scientometrics and bibliometrics research
paper · pdf · doi:10.48550/arxiv.0901.1380
openalex publication_date 2009/01/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The multidimensional character and inherent conflict with categorisation of interdisciplinarity makes its mapping and evaluation a challenging task. We propose a conceptual framework that aims to capture interdisciplinarity in the wider sense of knowledge integration, by exploring the concepts of diversity and coherence. Disciplinary diversity indicators are developed to describe the heterogeneity of a bibliometric set viewed from predefined categories, i.e. using a top-down approach that locates the set on the global map of science. Network coherence indicators are constructed to measure the intensity of similarity relations within a bibliometric set, i.e. using a bottom-up approach, which reveals the structural consistency of the publications network. We carry out case studies on individual articles in bionanoscience to illustrate how these two perspectives identify different aspects of interdisciplinarity: disciplinary diversity indicates the large-scale breadth of the knowledge base of a publication; network coherence reflects the novelty of its knowledge integration. We suggest that the combination of these two approaches may be useful for comparative studies of emergent scientific and technological fields, where new and controversial categorisations are accompanied by equally contested claims of novelty and interdisciplinarity.