Using bibliometrics to support the facilitation of cross-disciplinary communication

• Published in: Journal of the American Society for Information Science and Technology Vol. 64; no. 9; pp. 1768 - 1779
• Main Authors: Williams, Christopher J., O'Rourke, Michael, Eigenbrode, Sanford D., O'Loughlin, Ian, Crowley, Stephen J.
• Format: Journal Article
• Language: English
• Published: New York, NY Blackwell Publishing Ltd 01.09.2013; Wiley; Wiley Periodicals Inc
• Subjects: Bibliometrics; Bibliometrics. Scientometrics; Bibliometrics. Scientometrics. Evaluation; Citation analysis; Collaboration; communication skills; Effectiveness studies; Exact sciences and technology; Information and communication sciences; Information science; Information science. Documentation; Interdisciplinary aspects; Interdisciplinary subjects; Library and information science. General aspects; Methods; multivariate analysis; Research Administration; Sciences and techniques of general use; Space; Statistical analysis; Workshops; Statistical analysis; Citation; Bibliometric analysis; Multivariate analysis; Bibliometrics
• ISSN: 1532-2882; 2330-1635; 1532-2890; 2330-1643
• DOI: 10.1002/asi.22874

Given the importance of cross‐disciplinary research (CDR), facilitating CDR effectiveness is a priority for many institutions and funding agencies. There are a number of CDR types, however, and the effectiveness of facilitation efforts will require sensitivity to that diversity. This article presents a method characterizing a spectrum of CDR designed to inform facilitation efforts that relies on bibliometric techniques and citation data. We illustrate its use by the Toolbox Project, an ongoing effort to enhance cross‐disciplinary communication in CDR teams through structured, philosophical dialogue about research assumptions in a workshop setting. Toolbox Project workshops have been conducted with more than 85 research teams, but the project's extensibility to an objectively characterized range of CDR collaborations has not been examined. To guide wider application of the Toolbox Project, we have developed a method that uses multivariate statistical analyses of transformed citation proportions from published manuscripts to identify candidate areas of CDR, and then overlays information from previous Toolbox participant groups on these areas to determine candidate areas for future application. The approach supplies 3 results of general interest: A way to employ small data sets and familiar statistical techniques to characterize CDR spectra as a guide to scholarship on CDR patterns and trends. A model for using bibliometric techniques to guide broadly applicable interventions similar to the Toolbox. A method for identifying the location of collaborative CDR teams on a map of scientific activity, of use to research administrators, research teams, and other efforts to enhance CDR projects.