The data warehouse toolkit: practical techniques for building dimensional data warehouses
The data warehouse toolkit: practical techniques for building dimensional data warehouses
A foundation for capturing and querying complex multidimensional data
Information Systems - Data warehousing
What can Hierarchies do for Data Warehouses?
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Multidimensional Modeling with UML Package Diagrams
ER '02 Proceedings of the 21st International Conference on Conceptual Modeling
Hand-OLAP: A System for Delivering OLAP Services on Handheld Devices
ISADS '03 Proceedings of the The Sixth International Symposium on Autonomous Decentralized Systems (ISADS'03)
Operators for multidimensional aggregate data
Multidimensional databases
Incomplete information in multidimensional databases
Multidimensional databases
Multidimensional data modeling for location-based services
The VLDB Journal — The International Journal on Very Large Data Bases
Web services-oriented architectures for mobile SOLAP applications
International Journal of Web Engineering and Technology
Spatio-temporal and multi-representation modeling: a contribution to active conceptual modeling
Active conceptual modeling of learning
Spatial hierarchies and topological relationships in the spatial MultiDimER model
BNCOD'05 Proceedings of the 22nd British National conference on Databases: enterprise, Skills and Innovation
Designing Data Warehouses for Geographic OLAP Querying by Using MDA
ICCSA '09 Proceedings of the International Conference on Computational Science and Its Applications: Part I
A personalization process for spatial data warehouse development
Decision Support Systems
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Data warehousing and On Line Analytical Processing (OLAP) are technologies intended to support business intelligence. Spatial OLAP integrates spatial data into OLAP systems. Spatial OLAP models reformulate main OLAP concepts to define spatial dimensions and measures, and spatio-multidimensional navigation operators. Spatial OLAP reduces geographic information to its spatial component without taking into account map generalization relationships into the multidimensional decision process. In this paper, we present the concept of Geographic Dimensionwhich extends the classical definition of spatial dimension by introducing map generalization hierarchies, as they enhance analysis capabilities of SOLAP models and systems. A Geographic Dimension is described by spatial, descriptiveand/ormap generalizationhierarchies. These hierarchies permit to define ad-hoc aggregation functions, but at the same time raise several modeling problems.