Pourabbas,
Rafanelli, Ferri, and others have published widely on PQL, a pictorial query language
for spatial data using OLAP operators (Ferri, Pourabbas, & Rafanelli, 2002;
Pourabbas, 2003; Pourabbas & Rafanelli, 2002). Pourabbas (2003) has presented
the use of binding attributes to build a bridge while preserving the structure of both
the spatial database and the OLAP datacube. Pestana is developing the concept of
spatial dashboard based on SOLAP technology and collaborates with Laval team
on conceptual modeling of spatial datacubes (Pestana, da Silva, & B?©dard, 2005).
Other projects aim at improving spatial indexation, spatial aggregation, or spatial
operators (e.g., Gupta, Harinarayan, Rajaraman, & Ullman, 1997; Han et al., 1998;
Papadias, Kalnis, Zhang, & Tao, 2001; Prasher & Zhou, 2004; Stefanovic et al.,
2000; Wang, Pan, Ren, Cui, Ding, & Perrizo, 2003; Zhang, Li, Rao, Yu, Chen, &
Liu, 2003; Zhou, Truffet, & Han, 1999).
In spite of all this research activity, commercial solutions efficiently coupling OLAP
and GIS appeared on the market only very recently. These solutions, some OLAPcentric,
some GIS-centric, some hybrid, present only a subset of the desirable
functionalities of a spatial OLAP technology. Some are still limited to static map
visualization of OLAP query results. Others require the storage of each potential
individual map view on the server, thus affecting the update effectiveness of spatial
data.
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