Detecting patterns and OLAP operations in the GOLD model

The aim of our GOLD model ([7], [9]) is to provide an Object Oriented (OO) Multidimensional data model supported by an OO formal specification language that allows us to automatically generate prototypes from the specification at the conceptual level, and therefore, to animate and check system properties. Within the context of OO modeling and automatic prototyping, the basis of the mapping from modeling to programming is focused on the identification of (cardinality and behavioral) patterns in the design phase and their relationships with the data model, process model and interface design. The aim of this paper, therefore, is the identification of these patterns based on the relationships between the dimension attributes included in cube classes. These patterns will associate data together with OLAP operations and will allow us to have a concise execution model that maps every pattern of modeling into its corresponding implementation making users able to accomplish OLAP operations on cube classes. Furthermore, we extend the set of classical OLAP operations with two more operations (combine, divide) to allow us to navigate along attributes that are not part of any classification hierarchy.