  Though the mediums for visualization are limited, the potential dimensions of
a dataset are not. In many areas of scientific study, understanding the
correlations between those dimensions and their uncertainties is pivotal to
mining useful information from a dataset. Obtaining this insight can
necessitate visualizing the many relationships among temporal, spatial, and
other dimensionalities of data and its uncertainties. We utilize multiple views
for interactive dataset exploration and selection of important features, and we
apply those techniques to the unique challenges of cosmological particle
datasets. We show how interactivity and incorporation of multiple visualization
techniques help overcome the problem of limited visualization dimensions and
allow many types of uncertainty to be seen in correlation with other variables.
