Diversity and network coherence as indicators of interdisciplinarity: Case studies in bionanoscience

TL;DR

This paper introduces a framework using diversity and coherence metrics to evaluate interdisciplinarity in scientific research, demonstrated through case studies in bionanoscience.

Contribution

It develops novel bibliometric indicators for diversity and coherence, providing a comprehensive approach to measure interdisciplinarity.

Findings

Diversity indicates the breadth of a publication's knowledge base.

Network coherence reflects the structural consistency of related publications.

Combined metrics reveal different aspects of interdisciplinarity.

Abstract

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.