Redundant Encoding in Data Visualizations: Assessing Perceptual Accuracy and Speed
Russell Chun · Visual Communication Quarterly · 2017
While a number of studies in data visualization have investigated perceptual accuracies of visual encoding types, far less is known on the often-assumed benefits of redundant encoding, where multiple visual properties represent the same data. In this study, we conduct experiments to measure the perceptual accuracy and speed of redundant encodings of value on position, length, angle, and area. Our results demonstrate that the redundant addition of value to more accurate encoding types neither enhances nor detracts from perceptual judgments. We conclude that the neutrality of redundant value encoding can serve an important role in a designer's decision making and add visual interest to an infographic without impeding accuracy or speed.