CollaborationViz: interactive visual exploration of biomedical research collaboration networks

Area of Science:

• Biomedical Informatics
• Network Science
• Data Visualization

Background:

• Social network analysis (SNA) is crucial for understanding interactions within research communities.
• Clinical Translational Science Award (CTSA) programs benefit from SNA for assessing research collaborations.
• Traditional network statistics can be challenging for non-experts to interpret.

Purpose of the Study:

• To develop and present meaningful network visualizations for analyzing research collaboration networks (RCNs).
• To facilitate visual analysis tasks, uncovering hidden network structures and dynamics.
• To introduce CollaborationViz, an open-source tool for interactive visualization of RCNs.

Main Methods:

• Employed multidimensional, visual aggregation of network dynamics for visualization design.
• Applied novel visualization techniques to explore RCNs at a CTSA institution.
• Developed CollaborationViz, an open-source visual analytical tool.

Main Results:

• Visualizations effectively uncover hidden network structures and dynamics.
• The techniques allow for comparison of investigators and groups, identifying critical factors in network evolution.
• CollaborationViz provides an intuitive interface for apprehending RCN dynamics.

Conclusions:

• Meaningful network visualizations enhance the understanding of complex research collaborations.
• Visual analytical tools like CollaborationViz are valuable for researchers and administrators in CTSA communities.
• Interactive visualization aids in the analysis and strategic direction of RCNs.