Team Science at URMC: Using Social Network Analysis to Visualize Research Collaborations
In 2011, the University of Rochester Clinical and Translational Science Institute (CTSI) began a project to map the collaborative research environment at the University of Rochester Medical Center using self-reported data from faculty members. Additional data was collected in 2013 and 2015, and will be collected again starting on Tuesday, October 3. On Tuesday, all faculty members will receive an email containing a link to an online survey asking them to identify their current research collaborators at URMC by name. This data will help the CTSI understand how the research environment has evolved over time.
Network maps of collaborations among faculty at the University of Rochester Medical Center in 2013 and 2015.
Social network analysis, or “SNA”, is the mapping and measuring of relationships and flows between people, groups, organizations, and other connected information. The dots (nodes) in the network represent the individual people, while the links (edges) show relationships between the individuals. SNA provides both a visual and a mathematical analysis of human relationships, and provides insight into who the key players are within the network and who may benefit from additional network connections. For the medical center specifically, the CTSI is interested in analyzing:
- Growth and changes within the research network over time
- The composition of interdisciplinary and interdepartmental research teams
- The impact of office location (on-campus vs. off-campus) on collaborations
- The impact of gender on collaborations
The directors of the CTSI ask that all faculty members take a few minutes and complete the survey in order to provide your own piece of the research network puzzle. The more responses that are received, the more complete the research network picture will be. Thank you and we look forward to your participation!
For more information about the methodologies employed in the survey, read the CTSI’s initial publication about the project.
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 | 9/29/2017
