Diversity measures and network centralities as indicators of interdisciplinarity: Case studies in BionanoScience

Mapping and evaluating interdisciplinarity poses major challenges, due to its multidimensional character and its inherent conflict with categorisation methods. Here we develop indicators of interdisciplinarity as cognitive diversity that are not dependent on categorisation. To do so, we integrate in a conceptual framework measures of diversity used in ecology and economics, the measures of similarity predominant in bibliometrics and recently proposed indicators of interdisciplinarity based on social network analysis. We carry out two case studies in bionanoscience which illustrate how these indicators do capture the diversity of research topics engaged by an author or a publication, in contrast to category-based indicators that fail to do so. We suggest that these simple and ready-to-use indicators of cognitive diversity may be of potential importance in comparative studies of emergent scientific and technological fields, where claims of novelty and interdisciplinarity are rife but not always justified.