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Network dynamics to evaluate performance of an academic institution
Michael E Hughes1, John Peeler, John B Hogenesch
1Department of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, CT 06520, USA.
Science Translational Medicine
|October 15, 2010
Summary
Measuring scientific productivity using collaboration rates reveals significant growth in team science. The node degree metric showed a doubling of collaborations within the Institute for Translational Medicine and Therapeutics (ITMAT) over five years.
Area of Science:
- Biomedical research
- Translational medicine
- Scientific collaboration metrics
Background:
- Statistical performance assessments are common for individuals but not organizations.
- Team science is increasingly vital in biomedical research, necessitating new productivity measures.
- Assessing organizational productivity in science has lagged behind individual assessments.
Purpose of the Study:
- To measure changes in collaboration rates within a scientific organization.
- To evaluate the effectiveness of team science initiatives using a novel metric.
- To identify areas for improving inter-departmental and inter-institutional collaborations.
Main Methods:
- Utilized 'node degree over time' as a metric for collaboration rate.
- Analyzed publication and grant data over a five-year period.
- Focused on collaborations within the University of Pennsylvania's Institute for Translational Medicine and Therapeutics (ITMAT).
Main Results:
- Collaborative papers and grants within ITMAT approximately doubled over five years.
- Internal collaborations (within departments/institutions) were more frequent than external ones.
- The study quantified the growth in collaborative research activity.
Conclusions:
- The node degree metric effectively captures changes in scientific collaboration.
- ITMAT demonstrated significant growth in internal collaboration, indicating successful team science efforts.
- Opportunities exist to enhance collaborations between different institutions and departments.
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