The authors William Cleveland and Robert McGill have suggested a strong scientific foundation based theory to base graphical methods on. Graphical perception is one of the main principle that forms the base of the approach suggested by the authors. I completely agree with the fact that the effectiveness of the visualization of data after analysis lies in the quantitative information any user can gain by visually decoding the graphic. Maximizing this quantitative information gain should be the ultimate objective. I realized the importance of the need to have a strong basis from this paper. I feel the strong conceptual framework of the experiment and of course the subsequent experiment design and conclusions made it so successful. Even today, graphical perception is always considered a key factor in designing visualizations. In the wake of new types of visualizations like tree maps, I found this interesting paper based on a study conducted by two members of the Stanford Vis Group. With a somewhat similar experiment design, they are trying to assess the effectiveness of Amazon's Mechanical Turk to be used for graphical experiements.
Link to a brief description and the paper: http://vis.stanford.edu/papers/crowdsourcing-graphical-perception
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