GeoVisual Analytics - Integrated methods
for knowledge construction
Related Projects:
Representing, analyzing, modeling and extracting meaning from
the complex heterogeneous geospatial datasets being assembled
requires new approaches that can scale up to current and future
data complexity and data volume. Our work addresses a wide variety
of issues, including:
- the development of 'complex' spatiotemporal
systems with emergent properties,
- new techniques for data mining,
knowledge discovery, visualization (for application to geospatial
and spatiotemporal information about the past, present,
and future),
- advanced and semantically aware
spatial databases that can represent and integrate both
the data and the various higher level knowledge constructs,
such as categories and relationships that emerge from the
data during knowledge construction and
- developing a geographical agent
modeling environment for investigating human activities.
These activities, when integrated, support the entire geo-scientific
process, from initial exploration of data, hypothesis generation,
concept discovery, model formulation, analysis and validation,
and, when fused together seamlessly in GeoVISTA Studio, will
form a complete Problem Solving Environment (PSE) for teams
of scientists to use, thus supporting our geocollaboration focus.
By bringing these activities together in GeoVISTA Studio we
avoid many of the integration problems that plague traditional
computational analysis. To accomplish this goal, Center affiliates
and their collaborators are working to integrate methods and
tools that span many disciplines including machine learning,
pattern recognition, agent and cellular modeling, data mining,
multivariate information visualization and spatial statistics.
|
|
|