) and indexing (see for
example the evolution of the R-Tree spatial indexing method in Manolopoulos
et al., 2005)
??? Improving existing technologies for enriched SOLAP and better integration
into spatial data production workflows
Future.Trends.and. Conclusion
Research related to spatial data warehousing and spatial OLAP has grown over a 10
year period from the first ideas developed in a small number of isolated university
4 B?©dard, Rivest, & Proulx
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laboratories to today??™s emergence of an R&D community. Researchers from several
countries are addressing fundamental issues. Insofar, this community comes mainly
from computer science departments. The geomatics community is only discovering
the power of datacubes and OLAP. Rather, this community has looked into other
directions such as geovisualization, advanced GIS, and expert systems to better
support spatial decision making and geographic knowledge discovery. Looking at
the issues of SOLAP from a geomatics engineering perspective is very promising.
It brings a new level of challenges that relate to the very nature of spatial data and
its use in multistakeholder environments. This enriches the concepts and technologies
already available.
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