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Optimizing Queries Across Diverse Data Sources
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IEEE Intelligent Systems
Concept-based querying in mediator systems
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ICWE'10 Proceedings of the 10th international conference on Web engineering
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ITBAM'10 Proceedings of the First international conference on Information technology in bio- and medical informatics
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RW'11 Proceedings of the 7th international conference on Reasoning web: semantic technologies for the web of data
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Adaptive integration of distributed semantic web data
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SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
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SWIM '12 Proceedings of the 4th International Workshop on Semantic Web Information Management
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Journal of Biomedical Informatics
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In this contribution a system is presented, which provides access to distributed data sources using Semantic Web technology. While it was primarily designed for data sharing and scientific collaboration, it is regarded as a base technology useful for many other Semantic Web applications. The proposed system allows to retrieve data using SPARQL queries, data sources can register and abandon freely, and all RDF Schema or OWL vocabularies can be used to describe their data, as long as they are accessible on the Web. Data heterogeneity is addressed by RDF-wrappers like D2R-Server placed on top of local information systems. A query does not directly refer to actual endpoints, instead it contains graph patterns adhering to a virtual data set. A mediator finally pulls and joins RDF data from different endpoints providing a transparent on-the-fly view to the end-user. The SPARQL protocol has been defined to enable systematic data access to remote endpoints. However, remote SPARQL queries require the explicit notion of endpoint URIs. The presented system allows users to execute queries without the need to specify target endpoints. Additionally, it is possible to execute join and union operations across different remote endpoints. The optimization of such distributed operations is a key factor concerning the performance of the overall system. Therefore, proven concepts from database research can be applied.