Combining objects with rules to represent aggregation knowledge in data warehouse and OLAP systems - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Data and Knowledge Engineering Année : 2011

Combining objects with rules to represent aggregation knowledge in data warehouse and OLAP systems

Résumé

Data warehouses are based on multidimensional modeling. Using On-Line Analytical Processing (OLAP) tools, decision makers navigate through and analyze multidimensional data. Typically, users need to analyze data at different aggregation levels (using roll-up and drill-down functions). Therefore, aggregation knowledge should be adequately represented in conceptual multidimensional models, and mapped in subsequent logical and physical models. However, current conceptual multidimensional models poorly represent aggregation knowledge, which (1) has a complex structure and dynamics and (2) is highly contextual. In order to account for the characteristics of this knowledge, we propose to represent it with objects (UML class diagrams) and rules in the Production Rule Representation language (PRR). Static aggregation knowledge is represented in the class diagrams, while rules represent the dynamics (i.e. how aggregation may be performed depending on context). We present the class diagrams, and a typology and examples of associated rules. We argue that this representation of aggregation knowledge enables an early modeling of user requirements in a data warehouse project. A prototype has been developed based on the Java Expert System Shell (Jess).

Dates et versions

hal-01310843 , version 1 (03-05-2016)

Identifiants

Citer

Isabelle Comyn-Wattiau, Jacky Akoka, Nicolas Prat. Combining objects with rules to represent aggregation knowledge in data warehouse and OLAP systems. Data and Knowledge Engineering, 2011, 70 (8), pp.732 - 752. ⟨10.1016/j.datak.2011.03.004⟩. ⟨hal-01310843⟩
135 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More