Graphs are used extensively to facilitate the communication and comprehension of quantitative information, perhaps because they seem to exploit natural properties of our visual system such as the ability to process large amounts of information in parallel. Rather than a holistic pattern recognition process, however, research has found that graph comprehension is a complex, interactive process akin to text comprehension. Viewers form a mental model of the quantitative information displayed in the graph through serial, iterative cycles of identifying and relating the graphic patterns to associated variables. Furthermore, graph comprehension is not only constrained by bottom-up perceptual features of the graphical display, but is also influenced by top-down factors such as the viewer’s expectations about, or familiarity with, the graph’s content. Finally, individual differences in graph comprehension skill interact with top-down and bottom-up influences such that highly skilled graph viewers are less influenced by both the bottom up visual characteristics, and the top-down semantic content.