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Documents
Title:
High Dimensional Brushing for Interactive Exploration of Multivariate
Data
Authors:
Allen R. Martin, Matthew O. Ward
Abstract:
Brushing is an operation found in many data visualization
systems. It is a mechanism for interactively selecting subsets
of the data so that they may be highlighted, deleted, or masked.
Traditionally, brushes have been defined in screen space via methods
such as painting and rubberband rectangles. In this paper we describe
the design of N-dimensional brushes which are defined in data
space rather than screen space, and show how they have been integrated
into XmdvTool, a visualization package for displaying multivariate
data. Depending on the data display technique in use, brushes
may be specified and manipulated via direct or indirect methods,
and the specification may be demand-driven or data-driven. Various
brush operations such as highlighting, linking, masking, moving
average, and quantitative display have been developed to apply
to the selected data. In addition, we have explored several new
brush concepts, such as non-discrete brush boundaries, simultaneous
display of multiple brushes, and creating composite brushes via
logical operators. Preliinary experimental evaluation with test
subjects supports the usefulness of N-dimensional brushes in data
exploration tasks.
Source:
IEEE Visualization
'95 Conference
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