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URMC / Clinical & Translational Science Institute / Stories / November 2019 / Increasingly Interconnected: Mapping Research Collaborations at UR

Increasingly Interconnected: Mapping Research Collaborations at UR

collaboration data graphicFor nearly a decade, the UR CTSI has mapped research collaborations at the University of Rochester, its medical center (URMC), and other research institutions in the Clinical and Translational Science Awards (CTSA) Program using self-reported data from faculty members. According to that data, URMC researchers have become increasingly connected over time.

We are continuing that work now, and encourage faculty to take this ten-minute survey to tell us about their collaborations.

Responses to this year’s survey will help us understand how the research environment is evolving and where we could focus efforts to foster collaborative science and support emerging investigators and networks. Participating investigators, networks or groups, and centers or departments can request their results, which will be available in early 2020.

More About The Project

Every two years, the UR CTSI uses a survey tool to collect data from faculty on collaborations to perform social network analysis. This is a method of mapping and measuring the relationships and flows between people, groups or organizations. Social network analysis provides a visual and a mathematical analysis of human relationships, as well as insight into who are the key players within the network and who may benefit from additional network connections. 

For the medical center, the UR CTSI is analyzing:

  • Growth and changes within the research network over time
  • The composition of interdisciplinary and interdepartmental research teams
  • The impact of investigator gender and rank on collaborations

For more information about the method and previous outcomes of the survey, see the UR CTSI’s recent poster, which was presented at the March 2019 Translational Science meeting of the Association for Clinical and Translational Science (ACTS).


The project described here was supported by the University of Rochester CTSA award numbers UL1TR000042 and UL1TR002001 from the National Center for Advancing Translational Sciences of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Michael Hazard | 11/15/2019

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