Cancer Institute awarded a contract to Dr.
Alan MacEachren and Robert
Edsall of the GeoVISTA Center to develop and evaluate the dynamic
parallel coordinate plot for spatiotemporal analysis of health statistics
data. The dynamic parallel coordinate plot has been demonstrated to
be a powerful tool for visual multivariate data analysis (Edsall 1999),
but has not been applied to health statistics. The plots employ a
novel methodology to visualize more than three dimensions by representing
each observation not as a point in a scatter plot but as a series
of unbroken line segments connecting parallel axes, each of which
represents a different variable. By representing variables (X1, X2,
etc. on the figure right) as parallel - as opposed to orthogonal -
axes, the representation breaks the bonds of two or three-dimensional
representations such as scatter plots (Inselberg 1985; Wegman 1990).
This project is designed to explore the potential of dynamic parallel
coordinate plots for depicting multivariate health data linked to
maps depicting the geographic aspects of those data. Attention is
also directed to the use of PCPs for exploring time series of these
plan specifies a review of relevant literature in visualizing multivariate
geo-referenced health statistics, the development of an environment
with a dynamic parallel coordinate plot linked to geographic and other
statistical graphics (like scatter plots and histograms), and the
execution of an evaluation of the usability of the environment for
problem solving and data exploration.
Download a copy
of HealthVis PCP by clicking here (~9.22 MB).
You must have ArcView GIS 3.x and an unzip utility to use this program.
A user manual for installation and use of HealthVis PCP can be viewed
To read more
about the use of this software, see the following publication:
MacEachren, A.M. and Pickle, L.J. 2001. Case
Study: Design and Assessment of an Enhanced Geographic Information
System for Exploration of Multivariate Health Statistics. In:
K. Andrews, S.Roth and P.C. Wong,Proceedings of the IEEE Symposium
on Information Visualization 2001, San Diego, CA, October 22-25, 2001.