Assessing researcher interdisciplinarity: A case study of the University of Hawaii NASA Astrobiology Institute

Michael Gowanlock, Rich Gazan

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

In this study, we combine bibliometric techniques with a machine learning algorithm, the sequential information bottleneck, to assess the interdisciplinarity of research produced by the University of Hawaii NASA Astrobiology Institute (UHNAI). In particular, we cluster abstract data to evaluate Thomson Reuters Web of Knowledge subject categories as descriptive labels for astrobiology documents, assess individual researcher interdisciplinarity, and determine where collaboration opportunities might occur. We find that the majority of the UHNAI team is engaged in interdisciplinary research, and suggest that our method could be applied to additional NASA Astrobiology Institute teams in particular, or other interdisciplinary research teams more broadly, to identify and facilitate collaboration opportunities.

Original languageEnglish (US)
Pages (from-to)133-161
Number of pages29
JournalScientometrics
Volume94
Issue number1
DOIs
StatePublished - Jan 2013
Externally publishedYes

Keywords

  • Astrobiology
  • Bibliometrics
  • Information bottleneck method
  • Interdisciplinary science
  • Machine learning
  • Text mining

ASJC Scopus subject areas

  • Social Sciences(all)
  • Computer Science Applications
  • Library and Information Sciences

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