Enhancing Interdisciplinary Cooperation by Social Platforms: Assessing the Usefulness of Bibliometric Social Network Visualization in Large-Scale Research Clusters

André Calero Valdez, Anne-Kathrin Schaar, Martina Ziefle, Andreas Holzinger

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

In large-scale research projects active management of the cooperation process is necessary, e.g. to ensure systematic transfer of knowledge, alignment of research goals, or appropriate dissemination of research efforts. In a large scale research-cluster at the RWTH Aachen University a cybernetic management approach is applied. As a planned measure, publishing efforts (i.e. bibliometric data) will be visualized on a social software platform accessible by researchers and the steering committee. But do researchers agree with the chosen style of visualization of their publications? As part of a user centered design, this paper presents the results of an interview study with researchers (n=22) addressing the usefulness and applicability of this approach. As central findings arguments for using the publication visualization are identified such as enabling retrospective analysis, acquiring new information about the team, improvement in dissemination planning, but at the same time contrasted by arguments against this approach, such as missing information, a possibly negative influence on workflow of researchers, and the bad legibility of the visualization. Additionally requirements and suggested improvements are presented.
Original languageEnglish
Title of host publicationHuman Interface and the Management of Information. Information and Knowledge Design and Evaluation, Lecture Notes in Computer Science LNCS 8521
EditorsSakae Yamamoto
Place of PublicationHeidelberg, Berlin
PublisherSpringer
Pages298-309
Edition1
ISBN (Print)978-3-319-07730-7
DOIs
Publication statusPublished - 2014

Keywords

  • Data Visualization
  • Information Systems

ASJC Scopus subject areas

  • Computer Science(all)

Fields of Expertise

  • Information, Communication & Computing

Treatment code (Nähere Zuordnung)

  • Application
  • Experimental

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