Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
MAFRA - A MApping FRAmework for Distributed Ontologies
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
Representing and reasoning about mappings between domain models
Eighteenth national conference on Artificial intelligence
Promptdiff: a fixed-point algorithm for comparing ontology versions
Eighteenth national conference on Artificial intelligence
Ontology mapping: the state of the art
The Knowledge Engineering Review
Ontology Evolution: Not the Same as Schema Evolution
Knowledge and Information Systems
Qualitative Spatial Representation and Reasoning: An Overview
Fundamenta Informaticae - Qualitative Spatial Reasoning
A scheme for integrating concrete domains into concept languages
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Algebras of Ontology Alignment Relations
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
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Ontology mappings provide a common layer which allows distributed applications to share and to exchange semantic information. Providing mechanized ways for mapping ontologies is a challenging issue and main problems to be faced are related to structural and semantic heterogeneity. The complexity of these problems increases in the presence of spatiotemporal information such as geometry and topological intrinsic characteristics. Our proposal is intended for spatiotemporal ontologies and focuses on providing an integrated access to information sources using local ontologies. Our approach is set to build a system that guides users to derive meaningful mappings and to reason about them. To achieve this we use a description logic extended to spatiotemporal concrete domain. The ontology of each source is normalized in a common extended Ontology Web Language (OWL) which enables a natural correspondence with the spatiotemporal description logic formalism.