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Automated graphical generation systems should be able to design effective presentations for heterogeneous (quantitative and qualitative) information in static or interactive environments. When building such a system, it is important to thoroughly understand the presentation-related characteristics of domain-specific information. We define a data-analysis taxonomy that can be used to characterize heterogeneous information. In addition to capturing the presentation-related properties of data, our characterization takes into account the user's information-seeking goals and visual-interpretation preferences. We use automatically-generated examples from two different application domains to demonstrate the coverage of the proposed taxonomy and its utility for selecting effective graphical techniques.
Zhou et al. (Tue,) studied this question.
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