Users interact with visual analytic systems to act upon cognitive processes as part of making sense of their information. What can we glean from the interactions that users perform during analysis? If successful, this project will develop an understanding of, or science of, interaction to systematically re-cast user interaction into mixed-initiative systems.

Approach

We base this work on the user interaction paradigm called Semantic Interaction, which suggests a connection between the embodiment of the process through the user interaction and the cognitive discourse users have with the information. As a result, capturing that tacit knowledge associated with the user interaction in a mathematically structured form can lead to a more fluid cognitive process of discovery and thus faster and more meaningful insights.

Benefit

Establishing a fundamental understanding for how a user’s reasoning processes are explicated via the user interactions he or she performs can help create more effective mixed-initiative systems. The shift in focus in design of these systems could be realized by maintaining a higher semantic level or state of the user.

Instead of requiring a translation between the cognitive processes and the interactions with the system’s models to act on their intuition and domain expertise, users can maintain a higher level of thought about their task.