Abstract
This article presents a novel definition of a declarative mapping language, which is able to map precisely and unambiguously the semantics of a domain conceptualization (defined as an ontology) into queries to a set of data sources, where the data is residing. In this way, a system making use of this mapping language is able to access the data actually stored in the data sources thought a semantically rich representation. The mapping model proposed in this paper is also an ontology and therefore is machine understandable: it can be shared with other users or systems, processed by external tools for consistency checking, or collaboratively created and so on. Besides the contributions of the mapping model itself, this paper introduces the concepts of Semantic Join and Semantic Identifiers: a declarative approach to semantic data fusion and entity resolution over multiple unrelated databases, which allow to define extremely expressive mapping.
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Notes
Since ontologies also contain the concept of relation, we use the term DB relation to refer to the ones in data bases and the term relation to refer to the ontology relation.
E.g.: a reasoning service on T-Box is subsumption, typically written as \(C \sqsubseteq D. \) Determining subsumption is the problem of checking whether the concept denoted by D (the subsumer) is considered more general than the one denoted by C (the subsumee). In other words, subsumption checks whether the first concept always denotes a subset of the set denoted by the second one. For example, one might be interested in knowing whether \(Router \sqsubseteq Network Devices.\)
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The authors would like to thank Prof. Ernesto Damiani of Universitá degli Studi di Milano for his valuable support.
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Leida, M., Gusmini, A. & Davies, J. Semantics-aware data integration for heterogeneous data sources. J Ambient Intell Human Comput 4, 471–491 (2013). https://doi.org/10.1007/s12652-012-0165-4
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DOI: https://doi.org/10.1007/s12652-012-0165-4