Is the expertise of evaluation panels congruent with the research interests of the research groups: A quantitative approach based on barycenters. Issue 4 (October 2015)

• Record Type: Journal Article
• Authors: Rahman, A.I.M. Jakaria; Guns, Raf; Rousseau, Ronald; Engels, Tim C.E.
• Is Part Of: Journal of informetrics. Volume 9:Issue 4(2015:Oct.)
• Page Start: 704
• Page End: 721
• Publication Date: 2015-10
• Subjects: Research evaluation -- Expert panel -- Barycenter -- Overlay map -- Matching research expertise -- Similarity matrix; Library statistics -- Periodicals; Information science -- Statistical methods -- Periodicals; Bibliometrics -- Periodicals; Bibliothèques -- Statistiques -- Périodiques; Sciences de l'information -- Méthodes statistiques -- Périodiques; Bibliométrie -- Périodiques; 020.727
• DOI: 10.1016/j.joi.2015.07.009
• Languages: English
• ISSNs: 1751-1577

Abstract

Highlights: We present methods to measure overlap of expertise in research evaluation. An entity's expertise can be summarized as its barycenter in cognitive space. Barycenters can be calculated in two or more dimensions. The distance between barycenters is an indicator of cognitive distance and hence expertise overlap. The method is applied to two research evaluations at the University of Antwerp. Abstract: Discipline-specific research evaluation exercises are typically carried out by panels of peers, known as expert panels. To the best of our knowledge, no methods are available to measure overlap in expertise between an expert panel and the units under evaluation. This paper explores bibliometric approaches to determine this overlap, using two research evaluations of the departments of Chemistry (2009) and Physics (2010) of the University of Antwerp as a test case. We explore the usefulness of overlay mapping on a global map of science (with Web of Science subject categories) to gauge overlap of expertise and introduce a set of methods to determine an entity's barycenter according to its publication output. Barycenters can be calculated starting from a similarity matrix of subject categories (N dimensions) or from a visualization thereof (2 dimensions). We compare the results of the N -dimensional method with those of two 2-dimensional ones (Kamada–Kawai maps and VOS maps) and find that they yield very similar results. The distance between barycenters is used as an indicator of expertise overlap. The results reveal that there is some discrepancy between the panel's and the groups' publications in both the Chemistry and the Physics departments. The panels were not as diverse as the groups that were assessed. The match between the Chemistry panel and the Department was better than that between the Physics panel and the Department.