  One of the major challenges for evaluating the effectiveness of data
visualizations and visual analytics tools arises from the fact that different
users may be using these tools for different tasks. In this paper, we present a
simple example of how different tasks lead to different patterns of attention
to the same underlying data visualizations. We argue that the general approach
used in this experiment could be applied systematically to task and feature
taxonomies that have been developed by visualization researchers. Using eye
tracking to study the impact of common tasks on how humans attend to common
types of visualizations will support a deeper understanding of visualization
cognition and the development of more robust methods for evaluating the
effectiveness of visualizations.
