<abstract xmlns="http://www.w3.org/1999/xhtml"><sec id="j_jdis-2018-0004_s_007_w2aab3b7b4b1b6b1aab1c17b1Aa"><h3>Purpose</h3><p>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.</p></sec><sec id="j_jdis-2018-0004_s_008_w2aab3b7b4b1b6b1aab1c17b2Aa"><h3>Design/methodology/approach</h3><p>We compile publications by 45 researchers in each of 1) the iUTAH 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 iUTAH 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.</p></sec><sec id="j_jdis-2018-0004_s_009_w2aab3b7b4b1b6b1aab1c17b3Aa"><h3>Findings</h3><p>We find that participation in the iUTAH 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 iUTAH 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.</p></sec><sec id="j_jdis-2018-0004_s_010_w2aab3b7b4b1b6b1aab1c17b4Aa"><h3>Research limitations</h3><p>The quasi-experimental design necessarily generates suggestive, not definitively causal, findings because of the imperfect controls.</p></sec><sec id="j_jdis-2018-0004_s_011_w2aab3b7b4b1b6b1aab1c17b5Aa"><h3>Practical implications</h3><p>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&amp;D program management.</p></sec><sec id="j_jdis-2018-0004_s_012_w2aab3b7b4b1b6b1aab1c17b6Aa"><h3>Originality/value</h3><p>New visualizations of researcher collaboration provide compelling comparisons of the extent and nature of social networking among target cohorts.</p></sec></abstract>

PurposeThis 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/approachWe compile publications by 45 researchers in each of 1) the iUTAH 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 iUTAH 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.FindingsWe find that participation in the iUTAH 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 iUTAH 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 limitationsThe quasi-experimental design necessarily generates suggestive, not definitively causal, findings because of the imperfect controls.Practical implicationsThis 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/valueNew visualizations of researcher collaboration provide compelling comparisons of the extent and nature of social networking among target cohorts.

Measuring and Visualizing Research Collaboration and Productivity

Journal of Data and Information Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Measuring and Visualizing Research Collaboration and Productivity"}

PurposeThis paper presents findings of a quasi-experimental assessment to gauge the research productivity and degree of interdisciplinarity of research center...

Measuring and Visualizing Research Collaboration and Productivity

Article Category: Research Paper

Published Online: Mar 13, 2018

Page range: 54 - 81

Received: May 20, 2017

Accepted: Jul 21, 2017

DOI: https://doi.org/10.2478/jdis-2018-0004

Keywords
Bibliometrics, Interdisciplinarity, Multidisciplinarity, Research evaluation, Research collaboration mapping, Science visualization, Scientometrics, Social network analysis

© 2018 Walter de Gruyter GmbH, Berlin/Boston

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Measuring and Visualizing Research Collaboration and Productivity

Article Category: Research Paper

Published Online: Mar 13, 2018

Page range: 54 - 81

Received: May 20, 2017

Accepted: Jul 21, 2017

DOI: https://doi.org/10.2478/jdis-2018-0004

KeywordsBibliometrics, Interdisciplinarity, Multidisciplinarity, Research evaluation, Research collaboration mapping, Science visualization, Scientometrics, Social network analysis

© 2018 Walter de Gruyter GmbH, Berlin/Boston

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
Bibliometrics, Interdisciplinarity, Multidisciplinarity, Research evaluation, Research collaboration mapping, Science visualization, Scientometrics, Social network analysis