Multi-Level and Multi-Source Visual Analytics of Evidence-Based Knowledge Diffusion Processes

Project Start Date: Jul 1, 2014
Research Areas: Analytics, Analytics - Visual Analytics
Funding: Member Funded
Project Tags: ,

Project Summary

The project aims to develop enabling and integrative techniques for multi-level and multi-source gap analytics across heterogeneous units of analysis. Building on the single-source gap analytics work in our CVDI Year 2 project, the project will support the entire workflow of gap analytics involving multiple sources. Prototypes will demonstrate the visual analytic workflow through key application cases such as translational and evidence-based medicine (esp. portfolios of clinical trials, medicine research, health informatics), user behavior in complex adaptive systems (e.g., interactive events initiated from users of a diversity level of experience, how do users’ interactive behaviors differ between different levels?), and predictive studies of trigger events and trajectories of systemic changes. The objectives are to:

1) develop computational solutions to visualize how information moves across multiple heterogeneous sources

2) develop prototypes of showcases in relation to translational medicine, predictive analysis of the diffusion of information, and user adaptive behavior at different levels of expertise.


Principal Investigator(s)