As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
A data warehouse is built by collecting data from external sources. Several changes on contents and structures can usually happen on these sources. Therefore, these changes have to be reflected in the data warehouse using schema updating or versioning. However a data warehouse has also to evolve according to new users' analysis needs. In this case, the evolution is rather driven by knowledge than by data. In this paper, we propose a Rule-based Data Warehouse (R-DW) model, in which rules enable the integration of users' knowledge in the data warehouse. The R-DW model is composed of two parts: one fixed part that contains a fact table related to its first level dimensions, and a second evolving part, defined by means of rules. These rules are used to dynamically create dimension hierarchies, allowing the analysis contexts evolution, according to an automatic and concurrent way. Our proposal provides flexibility to data warehouse's evolution by increasing users' interaction with the decision support system.