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Documents
Title:
XmdvTool: Integrating Multiple Methods for Visualizing Multivariate
Data
Authors:
Matthew O. Ward
Abstract:
Much of the attention in visualization research has focussed
on data rooted in physical phenomena, which is generally limted
to three or four dimensions. However, many sources of data do
not share this dimensional restriction. A critical problem in
the analysis of such data is providing researchers with tools
to gain insights into characteristics of the data, such as anomalies
and patterns. Several visualization methods have been developed
to address this problem, and each has its strenghts and weaknesses.
This paper describes a system named XmdvTool which integrates
several of the most common methods for projecting multivariate
data onto a two-dimensional screen. This integration allows users
to explore their data in a variety of formats with ease. A view
enhancement mechanism called an N-dimensional brush is also described.
The brush allows users to gain insights into spatial relationships
over N dimensions by highlighting data which falls within a user-specified
subspace.
Source:
IEEE Visualization
'94 Conference
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