Scientists, engineers, and decision makers in a wide variety of fields are faced with the problem of visualizing the effect of multiple parameters on quantities of interest. Oftentimes a model of some physical system is involved in which the participants are interested not only in the model results, but also how the various driving parameters of the model have influenced that result. Moreover, the data sources and models have uncertainties associated with them. It is generally important to be able to visualize those uncertainties, and especially to be able to quickly focus on areas where there is considerable disagreement. In this paper, we review the use of a new visualization technique called Attribute Blocks and demonstrate how this can be used to visualize uncertainty in multiple driving model parameters simultaneously.
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