??? Producing spatial data at different levels of granularity for a same display size:
Today??™s SOLAP implementations sometimes lead to the display of ???zoomed
out??? maps that become too crowded and inappropriate for the analysis of
larger areas. Improperly applying on-the-fly automatic map generalization
may lead to drilling deadends and incoherence between the map and the cube
measures.
??? Integrating spatial data from heterogeneous and spatially divergent sources,
for instance (in spite of advances in interoperability, uncontrolled distortions
cannot be resolved automatically): In particular, spatial aggregation and summarization
often cannot be derived from detailed spatial data, requiring the
use of smaller-scale maps from other sources and to automatically match corresponding
spatial objects between different map scales (a step that is not yet
Spatial Online Analytical Processing (SOLAP)
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fully automatic). A similar challenge is to define and support spatial datacubes
interoperability (e.g., extending ISO/TC211 and OGC standards).
??? Improving the integration of spatiotemporal operators (topological and metric)
in the measures and dimensions of spatial datacubes, and to feed the spatiotemporal
facts
??? Improving conceptual modeling of spatiotemporal datacubes (e.
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