A foundation for capturing and querying complex multidimensional data
Information Systems - Data warehousing
Extending Practical Pre-Aggregation in On-Line Analytical Processing
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
STORM: A Statistical Object Representation Model
Proceedings of the 5th International Conference SSDBM on Statistical and Scientific Database Management
Summarizability in OLAP and Statistical Data Bases
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
Normal Forms for Multidimensional Databases
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Dimension Hierarchies Design from UML Generalizations and Aggregations
ER '01 Proceedings of the 20th International Conference on Conceptual Modeling: Conceptual Modeling
Multidimensional normal forms for data warehouse design
Information Systems
Capturing summarizability with integrity constraints in OLAP
ACM Transactions on Database Systems (TODS)
Research in data warehouse modeling and design: dead or alive?
DOLAP '06 Proceedings of the 9th ACM international workshop on Data warehousing and OLAP
Hierarchies in a multidimensional model: from conceptual modeling to logical representation
Data & Knowledge Engineering - Special issue: WIDM 2004
A UML profile for multidimensional modeling in data warehouses
Data & Knowledge Engineering - Special issue: ER 2003
Reconciling requirement-driven data warehouses with data sources via multidimensional normal forms
Data & Knowledge Engineering
BioStar models of clinical and genomic data for biomedical data warehouse design
International Journal of Bioinformatics Research and Applications
An MDA approach for the development of data warehouses
Decision Support Systems
Multidimensional data modeling for business process analysis
ER'07 Proceedings of the 26th international conference on Conceptual modeling
Extending visual OLAP for handling irregular dimensional hierarchies
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
A taxonomy of inaccurate summaries and their management in OLAP systems
ER'05 Proceedings of the 24th international conference on Conceptual Modeling
Ontologies and summarizability in OLAP
Proceedings of the 2010 ACM Symposium on Applied Computing
Combining objects with rules to represent aggregation knowledge in data warehouse and OLAP systems
Data & Knowledge Engineering
A model-driven approach for enforcing summarizability in multidimensional modeling
ER'11 Proceedings of the 30th international conference on Advances in conceptual modeling: recent developments and new directions
Detecting summarizability in OLAP
Data & Knowledge Engineering
Extending ER models to capture database transformations to build data sets for data mining
Data & Knowledge Engineering
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Multidimensional analysis allows decision makers to efficiently and effectively use data analysis tools, which mainly depend on multidimensional (MD) structures of a data warehouse such as facts and dimension hierarchies to explore the information and aggregate it at different levels of detail in an accurate way. A conceptual model of such MD structures serves as abstract basis of the subsequent implementation according to one specific technology. However, there is a semantic gap between a conceptual model and its implementation which complicates an adequate treatment of summarizability issues, which in turn may lead to erroneous results of data analysis tools and cause the failure of the whole data warehouse project. To bridge this gap for relationships between facts and dimension, we present an approach at the conceptual level for (i) identifying problematic situations in fact-dimension relationships, (ii) defining these relationships in a conceptual MD model, and (iii) applying a normalization process to transform this conceptual MD model into a summarizability-compliant model that avoids erroneous analysis of data. Furthermore, we also describe our Eclipsebased implementation of this normalization process.