Building the data warehouse (2nd ed.)
Building the data warehouse (2nd ed.)
Decision Support Systems - Special issue on WITS '97
A survey of logical models for OLAP databases
ACM SIGMOD Record
A foundation for capturing and querying complex multidimensional data
Information Systems - Data warehousing
Modeling Multidimensional Databases, Cubes and Cube Operations
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
Querying Multidimensional Databases
DBLP-6 Proceedings of the 6th International Workshop on Database Programming Languages
Applying Data Warehouse Concepts to Gene Expression Data Management
BIBE '01 Proceedings of the 2nd IEEE International Symposium on Bioinformatics and Bioengineering
GIMS - A Data Warehouse for Storage and Analysis of Genome Sequence and Functional Data
BIBE '01 Proceedings of the 2nd IEEE International Symposium on Bioinformatics and Bioengineering
MedTAKMI-CDI: interactive knowledge discovery for clinical decision intelligence
IBM Systems Journal
Solving summarizability problems in fact-dimension relationships for multidimensional models
Proceedings of the ACM 11th international workshop on Data warehousing and OLAP
OntoPath: a language for retrieving ontology fragments
OTM'07 Proceedings of the 2007 OTM Confederated international conference on On the move to meaningful internet systems: CoopIS, DOA, ODBASE, GADA, and IS - Volume Part I
Multidimensional integrated ontologies: a framework for designing semantic data warehouses
Journal on Data Semantics XIII
BioStar+: a data warehouse schema for integrating clinical and genomic data from HIV patients
ACM SIGBioinformatics Record
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Biomedical research is now generating large amounts of data, ranging from clinical test results to microarray gene expression profiles. The scale and complexity of these datasets give rise to substantial challenges in data management and analysis. It is highly desirable that data warehousing and online analytical processing technologies can be applied to biomedical data integration and mining. The major difficulty probably lies in the task of capturing and modelling diverse biological objects and their complex relationships. This paper describes multidimensional data modelling for biomedical data warehouse design. Since the conventional models such as star schema appear to be insufficient for modelling clinical and genomic data, we develop a new model called BioStar schema. The new model can capture the rich semantics of biomedical data and provide greater extensibility for the fast evolution of biological research methodologies.