A Classification of Visual Representations

hy du we often prefer glancing at a graph to studying a table of numbers? What might be a better graphic than either a graph or table for seeing how a biological process unfolds with time? To begin to answer these kinds of questions we examine the cognitive structure of graphics and report a structural classification of visual representadnns. McCormick, DeFami, and Brown [16] define visualization as " the study of mechanisms in computers and in humans which allow them in concert to perceive , use, and communicate visual information. " Thus, visualization includes the study of both image synthesis and image understanding. Given this broad focus, it is not surprising that visualization spans many academic disciplines, scientific fields, and multiple domains of inquiry. However, if visualization is to continue to advance as an interdisciplinary science, it must become more than a grab bag of techniques for displaying data. Our research focuses on classifying visual information. Classification lies at the heart of every scientific field. Classifications structure domains of systematic inquiry and provide concepu for developing theories to identify anomalies and to predict future research needs. Extant lawonomies of graphs and images can be characterized as either iimc-tional or structural. Functional taxonomies focus on the intended use and purpose of the graphic material. For example, consider the functional classification developed by Macdonald-Ross [ 141. One of the main categories is lechniurl dim pm used for maintaining, operating, and troubleshooting complex equip ment. Other examples of functional classifications can be found in Tufte [ZI. A functional classification does not reflect the physical structure of images, nor is it intended to correspond to an underlfing representation in memory 111. In contrast, structural categories are well learned and are derived from exem-plar learning. They focus on the form of the image rather than its content. Rankin [18] and Bertin [Z] developed such structural categories of graphs. Rankin used the number of dimensions and graph forms to determine his clas