Modelling Ubiquitous Web Applications - The WUML Approach
Revised Papers from the HUMACS, DASWIS, ECOMO, and DAMA on ER 2001 Workshops
Representing spatiality in a conceptual multidimensional model
Proceedings of the 12th annual ACM international workshop on Geographic information systems
Personalized systems: models and methods from an IR and DB perspective
VLDB '05 Proceedings of the 31st international conference on Very large data bases
A UML profile for multidimensional modeling in data warehouses
Data & Knowledge Engineering - Special issue: ER 2003
Piet: a GIS-OLAP implementation
Proceedings of the ACM tenth international workshop on Data warehousing and OLAP
A set of aggregation functions for spatial measures
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
A Conceptual Modeling Approach for OLAP Personalization
ER '09 Proceedings of the 28th International Conference on Conceptual Modeling
GeWOlap: a web based spatial OLAP proposal
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part II
ADVIS'06 Proceedings of the 4th international conference on Advances in Information Systems
A personalization process for spatial data warehouse development
Decision Support Systems
High-performance online spatial and temporal aggregations on multi-core CPUs and many-core GPUs
Proceedings of the fifteenth international workshop on Data warehousing and OLAP
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Spatial data warehouses (SDW) rely on extended multidimensional (MD) models in order to provide decision makers with appropriate structures to intuitively analyse spatial data. Several SDW development approaches provide a conceptual modeling and some guidelines in order to obtain logical schemas. However, there are two main drawbacks (i) spatial modeling is still complex for providing each decision maker with their own information needs, and (ii) SDW may be potentially large and spatial structures become increasingly complex to be analysed at a glance. Thus, representing and acquiring the required spatial information is more costly than expected and decision makers may get frustrated during the analysis. On the other hand, Web Engineering address similar problems (heterogeneous audience, different data sources and increasing amount and complexity of information) by using personalization rules. PRML (Personalization Rules Modeling Language) is a language that has been successfully applied to several Web systems in order to perform those personalization rules for every particular user and needs. Therefore, we have decided to use personalization rules and we have adapted the PRML to certain SDW aspects in order to introduce the right spatiality and deliver the correct information for every user needs. The great advantage of our approach is that each decision maker can easily include spatial data according to their own needs at conceptual level, while they can also conceptually get the right spatial schema instance avoiding exploring in a large and complex SDW.