A data warehouse conceptual data model

In this short paper we will briefly introduce a Data Ware-house Conceptual Data Model, which gracefully extends the standard Entity-Relationship (ER) conceptual data model with multi-dimensional aggregated entities. The conceptual data model has a clear model-theoretic semantics grounded on the extension of the standard ER semantics with the GMD logic-based multi-dimensional data model. The goal of the work presented here is to extend the standard ER conceptual data model, as defined in the database textbooks, with constructs which allow the mod-elling of multi-dimensional aggregated entities together with their interrelationships with the other parts of the con-ceptual schema. An important aspect is that a formal model-theoretic semantics is given to the resulting con-ceptual data model, by combining the well known first order semantics of standard ER—as described, for exam-ple, by [2]—with the model-theoretic semantics of the GMD logical data model for multi-dimensional informa-tion [5, 6]. This work is also based on a similar preliminary work done by one author on the use of Description Log-ics as a mean to give precise semantics to a data warehouse conceptual data model and to study its computational prop-erties [8]. In this short paper we do not present any formal aspect of the conceptual data model, but we only intro-duce it by means of an example. The conceptual data model we have obtained is ex-emplified in this short paper in Figure 1. A basic multi-dimensional entity such as Calls is described in the diagram of the figure using a standard star schema—i.e., it is rep-resented by means of a weak entity with respect to its di-mensions. In this example, this basic multi-dimensional en-tity may be useful for analysing the nature of telephone calls by considering, among others, the dimensions related to the This work has been partially supported by the EU projects Se-wasie, KnowledgeWeb, and Interop