Fast Track to MDX

Modelling and querying geographical data warehouses

“…MDX (multidimensional expressions) [51] is one of the most important approaches to querying multidimensional data. By using MDX, users can perform many complex queries in a multidimensional data cube, making available configurable data that cross different perspectives and aggregation levels by using multidimensional operators.…”

“…However, there is no query language with a unified syntax that allows the use of spatial and multidimensional operators for querying a geographical data warehouse. Thus, we propose GeoMDQL (Geographical and Multidimensional Query Language), a query language based on both MDX [51] and OGC SFS 4SQL [5] that offers a unified syntax for the statement of queries containing both multidimensional and spatial operators. Positional operators defined according to the work described in [18,4] were also included in the GeoMDQL language.…”

“…This query only contains the OLAP operators found in [51], based on the MDX language. For example, in a retail data cube, users may wish to know the list of the 10 most sold products for each category and for a specific month of the year.…”

Lily: A Geo-Enhanced Library for Location Intelligence

“…In [16] the authors propose GeoMDQL, a query language based on MDX [18] and OGC (Open Geospatial consortium) for querying spatial data cubes. Also GISOLAP-QL [7] extends MDX, but while GeoMDQL relies on a tightly-coupled architecture, GISOLAP-QL relies on a loosely-coupled one.…”

“…The GeoMDQL GUI [18] extends JPivot and is capable of displaying results in charts, tables, and maps but it is not described in detail, making it hard to understand how advanced the interaction with the system is. SOVAT [15] combines OLAP and GIS capabilities; its interface supports spatial drill-down and roll-up operations as well as drill-out, that allows users to submit queries based on both numerical and spatial aggregation.…”