Measuring and Visualizing Research Collaboration and Productivity

被引:0
|
作者
Jon Garner [1 ]
Alan L.Porter [2 ]
Andreas Leidolf [3 ]
Michelle Baker [3 ,4 ]
机构
[1] Search Technology,Inc.  2. School of Public Policy, Georgia Institute of Technology  3. Ecology Center, Utah State University
[2] Department of Biology, Utah State University
基金
美国国家科学基金会;
关键词
Bibliometrics; Interdisciplinarity; Multidisciplinarity; Research evaluation; Research collaboration mapping; Science visualization; Scientometrics; Social network analysis;
D O I
暂无
中图分类号
G353.1 [情报资料的分析和研究];
学科分类号
摘要
Purpose: This paper presents findings of a quasi-experimental assessment to gauge the research productivity and degree of interdisciplinarity of research center outputs. Of special interest, we share an enriched visualization of research co-authoring patterns. Design/methodology/approach: We compile publications by 45 researchers in each of 1) the i UTAH project, which we consider here to be analogous to a "research center," 2) CG1— a comparison group of participants in two other Utah environmental research centers, and 3) CG2—a comparison group of Utah university environmental researchers not associated with a research center. We draw bibliometric data from Web of Science and from Google Scholar. We gather publications for a period before i UTAH had been established(2010–2012) and a period after(2014–2016). We compare these research outputs in terms of publications and citations thereto. We also measure interdisciplinarity using Integration scoring and generate science overlay maps to locate the research publications across disciplines.Findings: We find that participation in the i UTAH project appears to increase research outputs(publications in the After period) and increase research citation rates relative to the comparison group researchers(although CG1 research remains most cited, as it was in the Before period). Most notably, participation in i UTAH markedly increases co-authoring among researchers—in general; and for junior, as well as senior, faculty; for men and women: across organizations; and across disciplines.Research limitations: The quasi-experimental design necessarily generates suggestive, not definitively causal, findings because of the imperfect controls.Practical implications: This study demonstrates a viable approach for research assessment of a center or program for which random assignment of control groups is not possible. It illustrates use of bibliometric indicators to inform R&D program management.Originality/value: New visualizations of researcher collaboration provide compelling comparisons of the extent and nature of social networking among target cohorts.
引用
收藏
页码:54 / 81
页数:28
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