CONSTRUCTING KNOWLEDGE
FROM MULTIVARIATE SPATIOTEMPORAL DATA:
Integrating
Geographic Visualization (Geovisualization) with Knowledge Discovery
in Database (KDD) Methods
Alan M. MacEachren,
Monica Wachowicz, Robert Edsall, Daniel Haug, Raymon Masters
ABSTRACT We
present an approach to the process of constructing knowledge through
structured exploration of large spatiotemporal data sets. First, we
introduce our problem context and define both Geographic Visualization
(geovisualization) and Knowledge Discovery in Databases (KDD), the
source domains for methods being integrated. Next, we review and compare
recent geovisualization and KDD developments and consider the potential
for their integration, emphasizing that an iterative process with
user interaction is a central focus for uncovering interesting and
meaningful patterns through each. We then introduce an approach to
design of an integrated geovisualization-KDD environment directed
to exploration and discovery in the context of spatiotemporal environmental
data. The approach emphasizes a matching of geovisualization and KDD
meta-operations. Following description of the geovisualization and
KDD methods that are linked in our prototype system, we present a
demonstration of the prototype applied to a typical spatiotemporal
dataset. We conclude by outlining, briefly, research goals directed
toward more complete integration of geovisualization and KDD methods
and their connection to temporal GIS.
