Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Declarative Data Cleaning: Language, Model, and Algorithms
Proceedings of the 27th International Conference on Very Large Data Bases
Semantic and schematic similarities between database objects: a context-based approach
The VLDB Journal — The International Journal on Very Large Data Bases
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
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Researchers at the medical research institute Inserm U522, specialized in the liver, use high throughput technologies to diagnose liver disease states. They seek to identify the set of dysregulated genes in different physiopathological situations, along with the molecular regulation mechanisms involved in the occurrence of these diseases, leading at mid-term to new diagnostic and therapeutic tools. To be able to resolve such a complex question, one has to consider both data generated on the genes by in-house transcriptome experiments and annotations extracted from the many publicly available heterogeneous resources in Biomedicine. This paper presents GEDAW, a gene expression data warehouse that has been developed to assist such discovery processes. The distinctive feature of GEDAW is that it systematically integrates gene information from a multitude of structured data sources. Data sources include: i) XML records of GENBANK to annotate gene sequence features, integrated using a schema mapping approach, ii) an inhouse relational database that stores detailed experimental data on the liver genes and is a permanent source for providing expression levels to the warehouse without unnecessary details on the experiments, and iii) a semi-structured data source called BioMeKE-XML that provides for each gene its nomenclature, its functional annotation according to Gene Ontology, and its medical annotation according to the UMLS. Because GEDAW is a liver gene expression data warehouse, we have paid more attention to the medical knowledge to be able to correlate biology mechanisms and medical knowledge with experimental data. The paper discusses the data sources and the transformation process that is applied to resolve syntactic and semantic conflicts between the source format and the GEDAW schema.