The dissertation discussed in this article [1] was written in the midst of an era of digitization. The world is becoming increasingly instrumented with sensors, monitoring, and other methods for generating data describing social, physical, and natural phenomena. Thus, data exist with the potential of being analyzed to uncover, or discover, the phenomena from which it was created. However, as the analytic models leveraged to analyze these data continue to increase in complexity and computational capability, how can visualizations and user interaction methodologies adapt and evolve to continue to foster discovery and sensemaking?
Revised: September 30, 2014 |
Published: July 1, 2014
Citation
Endert A. 2014.Semantic Interaction for Visual Analytics: Toward Coupling Cognition and Computation.IEEE Computer Graphics and Applications 34, no. 4:8-15.PNNL-SA-103241.doi:10.1109/MCG.2014.73