Database techniques for the World-Wide Web: a survey
ACM SIGMOD Record
Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Heterogeneous database integration in biomedicine
Computers and Biomedical Research
Source Integration in Data Warehousing
DEXA '98 Proceedings of the 9th International Workshop on Database and Expert Systems Applications
SD-Core: Generic Semantic Middleware Components for the Semantic Web
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
Towards generating ETL processes for incremental loading
IDEAS '08 Proceedings of the 2008 international symposium on Database engineering & applications
SD-Core: A Semantic Middleware Applied to Molecular Biology
OTM '08 Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS
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Biological research and development are routinely producing terabytes of data that need to be organized, queried and reduced to useful scientific knowledge. Even though data integration can provide solutions to such biological problems, it is often problematic due to the sources' heterogeneity and their semantic and structural diversity. Moreover, necessary updates of both structure and content of databases provide further challenges for an integration process. We present a new biological data warehouse for Pseudomonas species "PseudomonasDW" to integrate annotation and pathway data from highly different resources. The combination of knowledge from multiple disciplines and sources should advance the understanding of cellular processes and lead to the prediction of cellular behavior in its entirety. The key aspect of our approach is the combination of a materialized and a virtual data integration to exploit their advantages in a new hybrid approach. The data are extracted from the original data sources using SB-KOM (System Biology Khaos Ontology-based Mediator) and then stored locally in the data warehouse to ensure a fast performance and data consistency.