A study of integrating perceptual guidelines from psychophysical experiments into an automated “visualization assistant.” Perceptual rules are converted into evaluation engines that critique a visualization and offer hints on how to improve it. Viewers answer a set of simple, application-independent queries about their dataset and analysis tasks. This is used in combination with the evaluation engines and mixed-initiative search algorithms from artificial intelligence to identify and improve promising visualization designs.

• Visual perception and mixed-initiative interaction for visualization design
• ViA: A perceptual visualization assistant
• ChipViz: Visualizing memory chip test data