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

  • André Calero Valdez
  • Anne Kathrin Schaar
  • Martina Ziefle
  • Andreas Holzinger
  • Sabina Jeschke
  • Christian Brecher
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7669)

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 [1]. 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 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • André Calero Valdez
    • 1
  • Anne Kathrin Schaar
    • 1
  • Martina Ziefle
    • 1
  • Andreas Holzinger
    • 2
  • Sabina Jeschke
    • 3
  • Christian Brecher
    • 4
  1. 1.Human-Computer Interaction CenterRWTH Aachen UniversityAachenGermany
  2. 2.Institute for Medical Informatics, Statistics and DocumentationMedical University GrazAustria
  3. 3.Institute of Information Management in Mechanical Engineering (IMA), Center for Learning and Knowledge Management (ZLW), Assoc. Institute for, Management Cybernetics e.V. (IfU)RWTH Aachen UniversityAachenGermany
  4. 4.Laboratory for Machine Tools and Production EngineeringRWTH Aachen UniversityAachenGermany

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