Adaptive Visualization of Social Networks (ADVIS)

This proposal is to extend into Phase II our development of a new system for Adaptive Visualization of Social Networks (ADVIS). Recent years have seen a dramatic increase in the collection and study of social network data. Numerous social network visualizations have been developed to support user exploration and understanding of these data. However even in the few best systems, cognitive and design principles have been applied in ad hoc and non-systematic manner. The resulting visualization tools, while fine-tuned to a particular problem domain, cannot be adapted to changing user goals and priorities, data sets, and analyses. In our proposed approach, visualizations will instead be automatically generated in response to user-supplied tasks, based on a cognitive science framework that integrates"first principles"derived from the latest findings from perceptual and cognitive psychology, computer interface design, and cognitive systems engineering. The key innovation in our proposed system is an automated reasoning process that selects an optimal set of visualization techniques by explicitly considering the underlying cognitive premises of those techniques, and their interactions. As user goals, priorities, and data change, the system will continually create and re-create visualizations that are optimally tuned to most effectively support the user.