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Line Graph Perception

We need data visualizations that can scale as screens sizes & aspect ratios change with technological advances, as well as when data sets get more complex. In order to simplify and distill line graphs to their essential features, we need to understand how people understand line graphs. What kinds of features are perceived and remembered? What is the hierarchy of line graph features? Does any of this change as visualization size and aspect ratio changes?

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Redundant Encoding

The redundant use of multiple visual features (redundant encoding) is a common data visualization technique. However, there is surprisingly very little evidence that there is a benefit to adding such visual complexity. Here we tested whether selection performance is better for simultaneous selection of multiple dimensions (color and shape) that specify the same set, relative to selection of either dimension alone. That is, is conjunctive selection helpful, even when the extra dimension is redundant? [More details]