6 Cube

6.1 Context

Some statistical systems create views of data based on a “cube” structure. In essence, a cube is an n-dimensional object where the value of each dimension can be derived from a hierarchical code list. The utility of such cube systems is that it is possible to “roll up” or “drill down” each of the hierarchy levels for each of the dimensions to specify the level of granularity required to give a “view” of the data – some dimensions may be rolled up, others may be drilled down. Such systems give a dynamic view of the data, with aggregated values for rolled up dimension positions. For example, the individual countries may be rolled up into an economic region such as the EU, or a geographical region such as Europe, whilst another dimension, such as “type of road” may be drilled down to its lower level. The resulting measure (such as “number of accidents”) would then be an aggregation of the value for each individual country for the specific type of road.

Such cube systems rely, not on simple code lists, but on hierarchical code sets (see section 8).

6.2 Support for the Cube in the Information Model

Data reported using a Data Structure Definition structure (where each dimension value, if coded, is taken from a flat code list) can be described by a cube definition and can be processed by cube aware systems. The SDMX-IM supports the definition of such cubes in the following way:

• The HierachicalCodelist defines the (often complex) hierarchies of codes
• If required, the StructureSet can
  • group DataStructureDefinition that describe the cube
  • provide a mapping mechanism between the codes in the flat code lists used by the DataStructureDefinition and a HierarchicalCodelist where the HierarchicalCodelist uses code lists that are not used in the DataStructureDefinition