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:
1) 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.
2) A model for using bibliometric techniques to guide broadly applicable interventions similar to the Toolbox.
3) 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.
Analysis and visualization of the dynamics of research groups in terms of projects and co-authored publications. A case study of library and information science in Argentina :
« Objective: The present study offers a novel methodological contribution to the study of the configuration and dynamics of research groups, through a comparative perspective of the projects funded (inputs) and publication co-authorships (output).
Method: A combination of bibliometric techniques and social network analysis was applied to a case study: the Departmento de Bibliotecología (DHUBI), Universidad Nacional de La Plata, Argentina, for the period 2000-2009. The results were interpreted statistically and staff members of the department, were interviewed.
Results: The method makes it possible to distinguish groups, identify their members and reflect group make-up through an analytical strategy that involves the categorization of actors and the interdisciplinary and national or international projection of the networks that they configure. The integration of these two aspects (input and output) at different points in time over the analyzed period leads to inferences about group profiles and the roles of actors.
Conclusions: The methodology presented is conducive to micro-level interpretations in a given area of study, regarding individual researchers or research groups. Because the comparative input-output analysis broadens the base of information and makes it possible to follow up, over time, individual and group trends, it may prove very useful for the management, promotion and evaluation of science. »
Google Scholar Metrics: an unreliable tool for assessing scientific journals :
« We introduce Google Scholar Metrics (GSM), a new bibliometric product of Google that aims at providing the H-index for scientific journals and other information sources. We conduct a critical review of GSM showing its main characteristics and possibilities as a tool for scientific evaluation. We discuss its coverage along with the inclusion of repositories, bibliographic control, and its options for browsing and searching. We conclude that, despite Google Scholar’s value as a source for scien- tific assessment, GSM is an immature product with many shortcomings, and therefore we advise against its use for evalu- ation purposes. However, the improvement of these shortcomings would place GSM as a serious competitor to the other existing products for evaluating scientific journals. »
Beyond citations: Scholars’ visibility on the social Web :
« Traditionally, scholarly impact and visibility have been measured by counting publications and citations in the scholarly literature. However, increasingly scholars are also visible on the Web, establishing presences in a growing variety of social ecosystems. But how wide and established is this presence, and how do measures of social Web impact relate to their more traditional counterparts? To answer this, we sampled 57 presenters from the 2010 Leiden STI Conference, gathering publication and citations counts as well as data from the presenters’ Web « footprints. » We found Web presence widespread and diverse: 84% of scholars had homepages, 70% were on LinkedIn, 23% had public Google Scholar profiles, and 16% were on Twitter. For sampled scholars’ publications, social reference manager bookmarks were compared to Scopus and Web of Science citations; we found that Mendeley covers more than 80% of sampled articles, and that Mendeley bookmarks are significantly correlated (r=.45) to Scopus citation counts. »
Le classement de Leiden: environnement scientifique et configuration :
« Le classement de Leiden s’impose aujourd’hui comme une alternative pertinente et valable vis-à-vis de celui de Shanghai. De nombreux indicateurs font intervenir les caractéristiques propres aux champs disciplinaires et des calculs fondés sur le principe de distribution. Il est conçu par le centre CWTS de l’université néerlandaise de Leiden. »
« The Leiden Ranking is considered today as quite a pertinent and valuable alternative vs. the Shanghai Ranking. A significant number of indicators involve for instance Fields Citation Scores and data distribution. It is conceived by the CWTS of the University of Leiden – The Netherlands. »
This study gives an overview of the process of clustering scientific disciplines using hybrid methods, detecting and labelling emerging topics and analysing the results using bibliometrics methods.
The hybrid clustering techniques are based on biblographic coupling and text-mining and ‘core documents’, and cross-citation links are used to identify emerging fields.
The collaboration network of those countries that proved to be most active in the underlying disciplines, in combination with a set of standard indicators, form the groundwork for the bibliometric analysis of the detected emerging research topics.