Title:
Data
Cubes Mapping and Visualization with SOLAP Tool: Support for Geospatial
Decision Making
Abstract: In
a decision-making context, multidimensional geospatial databases are
very important. They often represent data coming from heterogeneous and
evolving sources. Evolution of multidimensional structures makes
difficult, even impossible answering to temporal queries, since
relationships between different temporal versions of spatial cubes
often remain unknown. This paper proposes a semantic mapping model
based on a semantic similarity model to establish semantic relations
between spatial regions of data cubes. The proposed model integrates
several similarity components adapted to the different hierarchical
levels of spatial dimensions in multidimensional databases. Then the
semantic mapping model implementation has been coupled with the SOLAP
(Spatial On-Line Analytical Processing) tool which allows visualizing
semantic mapping results between spatial regions. The developed
prototype shows to be very useful for supporting decision making which
is based on analysis of spatial variability and evolution.
Author: Mohamed
Bakillah