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

被引：22

作者：

Gowanlock, Michael ^{[1
]}

Gazan, Rich ^{[1
]}

机构：

[1] Univ Hawaii, Dept Informat & Comp Sci, NASA Astrobiol Inst, Lib & Informat Sci Program, Honolulu, HI 96822 USA

来源：

SCIENTOMETRICS | 2013年 / 94卷 / 01期

基金：

美国国家航空航天局;

关键词：

Astrobiology; Bibliometrics; Information bottleneck method; Interdisciplinary science; Machine learning; Text mining; SCIENCE; CITATION;

D O I：

10.1007/s11192-012-0765-y

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页码：133 / 161

页数：29