Structure-based brushes: A mechanism for navigating hierarchically organized data and information spaces

Interactive selection is a critical component in exploratory visualization, allowing users to isolate subsets of the displayed information for highlig hting, deleting, analysis, or focused investigation. Brushing, a popular me thod for implementing the selection process, has traditionally been perform ed in either screen space or data space. In this paper, we introduce an alt ernate, and potentially powerful, mode of selection that we term structure- based brushing, for selection in data sets with natural or imposed structur e. Our initial implementation has focused on hierarchically structured data , specifically very large multivariate data sets structured via hierarchica l clustering and partitioning algorithms. The structure-based brush allows users to navigate hierarchies by specifying focal extents and level-of-deta il on a visual representation of the structure. Proximity-based coloring, w hich maps similar colors to data that are closely related within the struct ure, 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 tech niques, namely hierarchical parallel coordinates and tree-maps. Finally, we discuss relationships between different classes of brushes and identify me thods by which structure-based brushing could be extended to alternate data structures.