Structure-Based Brushes: A Mechanism for Navigating Hierarchically
Organized Data and Information Spaces
Authors: Ying-Huey Fua, Matthew O. Ward and Elke A. Rundensteiner
Interactive selection is a critical component in exploratory
visualization, allowing users to isolate subsets of the displayed
information for highlighting, deleting, analysis, or focussed
investigation. Brushing, a popular method for implementing the
selection process, has traditionally been performed in either
screen space or data space. In this paper, we introduce an alternate,
and potentially powerful, mode of selection that we term structure-based
brushing, for selection in data sets with natural or imposed structure.
Our initial implementation has focussed on hierarchically structured
data, specifically very large multivariate data sets structured
via hierarchical clustering and partitioning algorithms. The structure-based
brush allows users to navigate hierarchies by specifying focal
extents and level-of-detail on a visual representation of the
structure. Proximity-based coloring, which maps similar colors
to data that are closely related within the structure, helps convey
both structural relationships and anomalies. We describe the design
and implementation of our structure-based brushing tool. We also
validate its usefulness using two distinct hierarchical visualization
techniques, namely hierarchical parallel coordinates and tree-maps.
Finally, we discuss relationships between different classes of
brushes and identify methods by which structure-based brushing
could be extended to alternate data structures.
Brushing, hierarchical representation, interactive selection,
exploratory data analysis.
on Visualization and Computer Graphics. (invited paper selected
from IEEE Symposium on Information Visualization), May - June