You can use an XBRL dimension to add context to a measure value. You can think of them as a categorization or segmentation of concepts. XBRL dimensions use categories to describe how you arrived at a measured value by illustrating semantic relationships between facts and how they have been segmented. For example, if a Revenue dimension contains a region concept and a product line concept, you could reuse the region and product line concepts for other concepts including “net” or gross revenue”.
Dimension members belong to a context. As such, the dimension mapping is associated with the concept map (that is a fact value) only through the context. When a dimension member is defined as a “domainItemType” and abstract—it is valid to associate it with a context. However, the “high level” dimension items (such as “hypercubeItem”) cannot be associated with contexts.
XBRL dimensions are not the same as dimensions in Oracle Hyperion data sources (such as Oracle Essbase or Oracle Hyperion Financial Management). While some conceptual similarities exist, no systematic relationships exists between XBRL dimensions and Oracle Hyperion data source dimensions. The two should not be confused.
Basic concepts of XBRL dimensions:
Hypercube—Expresses a collection of dimensions
Primary Item—A nondimension concept within a taxonomy that identifies the hypercubes that can be associated with it. Not all concepts in a taxonomy are primary items; however, concepts that are declared primary items must have hypercube associations
Dimension—Category by which information is analyzed
Domain and Domain Members—A domain is all of the domain members that are used to express a dimension