Using Mixed Node Publication Network Graphs for Analyzing Success in Interdisciplinary Teams

André Calero Valdez (), Anne Kathrin Schaar, Martina Ziefle, Andreas Holzinger, Sabina Jeschke and Christian Brecher
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André Calero Valdez: RWTH Aachen University, Human Computer Interaction Center
Anne Kathrin Schaar: RWTH Aachen University, Human Computer Interaction Center
Martina Ziefle: RWTH Aachen University, Human Computer Interaction Center
Andreas Holzinger: Medical University Graz, Institute for Medical Information, Statistics and Documentation
Sabina Jeschke: RWTH Aachen University, IMA/ZLW & IfU
Christian Brecher: RWTH Aachen University, Werkzeugmaschinenlabor (WZL)

A chapter in Automation, Communication and Cybernetics in Science and Engineering 2013/2014, 2014, pp 737-749 from Springer

Abstract: Abstract Large-scale research problems (e.g. health and aging, eonomics and production in high-wage countries) are typically complex, needing competencies and research input of different disciplines (Ziefle et al., E-Health, Assistive Technologies and Applications for Assisted Living: Challenges and Solutions, pp. 76–93, 2011). Hence, cooperative working in mixed teams is a common research procedure to meet multi-faceted research problems. Though, interdisciplinarity is – socially and scientifically – a challenge, not only in steering cooperation quality, but also in evaluating the interdisciplinary performance. In this paper we demonstrate how using mixed-node publication network graphs can be used in order to get insights into social structures of research groups. Explicating the published element of cooperation in a network graph reveals more than simple co-authorship graphs. The validity of the approach was tested on the 3-year publication outcome of an interdisciplinary research group. The approach was highly useful not only in demonstrating network properties like propinquity and homophily, but also in proposing a performance metric of interdisciplinarity. Furthermore we suggest applying the approach to a large research cluster as a method of self-management and enriching the graph with sociometric data to improve intelligibility of the graph.

Keywords: Publication Network Analysis; Sociometry; Interdisciplinarity; Research Cluster Assessment; Bibliometry; Visualization (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-08816-7_57

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DOI: 10.1007/978-3-319-08816-7_57

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