Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Semantic query optimization in Datalog programs (extended abstract)
PODS '95 Proceedings of the fourteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
SQL/XML is making good progress
ACM SIGMOD Record
Description logic programs: combining logic programs with description logic
WWW '03 Proceedings of the 12th international conference on World Wide Web
XML programming with SQL/XML and XQuery
IBM Systems Journal
RStar: an RDF storage and query system for enterprise resource management
Proceedings of the thirteenth ACM international conference on Information and knowledge management
ACM SIGMOD Record
System RX: one part relational, one part XML
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Supporting ontology-based semantic matching in RDBMS
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Semantic queries in databases: problems and challenges
Proceedings of the 18th ACM conference on Information and knowledge management
IBM UFO repository: object-oriented data integration
Proceedings of the VLDB Endowment
Semantic-distance based evaluation of ranking queries over relational databases
Journal of Intelligent Information Systems
Towards ontology-based OLAP: datalog-based reasoning over multidimensional ontologies
Proceedings of the fifteenth international workshop on Data warehousing and OLAP
Proceedings of the 16th International Conference on Extending Database Technology
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The database community is on a constant quest for better integration of data management and knowledge management. Recently, with the increasing use of ontology in various applications, the quest has become more concrete and urgent. However, manipulating knowledge along with relational data in DBMSs is not a trivial undertaking. In this paper, we introduce a novel, unified framework for managing data and domain knowledge. We provide the user with a virtual view that unifies the data, the domain knowledge and the knowledge inferable from the data using the domain knowledge. Because the virtual view is in the relational format, users can query the data and the knowledge in a seamlessly integrated manner. To facilitate knowledge representation and inferencing within the database engine, our approach leverages XML support in hybrid relational-XML DBMSs (e.g., Microsoft SQL Server & IBM DB2 9 PureXML). We provide a query rewriting mechanism to bridge the difference between logical and physical data modeling, so that queries on the virtual view can be automatically transformed to components that execute on the hybrid relational-XML engine in a way that is transparent to the user.