Invited talk: automata theory for database theoreticians
PODS '89 Proceedings of the eighth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Federated database systems for managing distributed, heterogeneous, and autonomous databases
ACM Computing Surveys (CSUR) - Special issue on heterogeneous databases
Irrelevance reasoning in knowledge-based systems
Irrelevance reasoning in knowledge-based systems
Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Methodologies, tools and languages for building ontologies: where is their meeting point?
Data & Knowledge Engineering
Ontology Matching
The Description Logic Handbook
The Description Logic Handbook
Tractable Reasoning and Efficient Query Answering in Description Logics: The DL-Lite Family
Journal of Automated Reasoning
Automatic Extraction of Ontologies Wrapping Relational Data Sources
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Effective query rewriting with ontologies over DBoxes
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Journal on data semantics X
Enabling ontology-based access to streaming data sources
ISWC'10 Proceedings of the 9th international semantic web conference on The semantic web - Volume Part I
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We consider the problem of designing data wrapping ontologies whose purpose is to describe relational data sources and to provide a semantically enriched access to the underlying data. Since such ontologies must be close to the data they wrap, the new terms that they introduce must be "supported" by data from the relational sources; i.e. when queried, they should return nonempty answers. In order to ensure non-emptiness, those wrapping ontologies are usually carefully handcrafted by taking into account the query answering mechanism. In this paper we address the problem of supporting an ontology engineer in this task. We provide an algorithm for verifying emptiness of a term in the data wrapping ontology w.r.t.the data sources. We also show how this algorithm can be used to guide the ontology engineer in fixing potential terms unsupported by the data. Finally, we present an implemented tool and an empirical study showing benefits of our approach.