1,403 research outputs found

    A review of the state of the art in Machine Learning on the Semantic Web: Technical Report CSTR-05-003

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    R2O, an extensible and semantically based database-to-ontology mapping language

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    We present R2O, an extensible and declarative language to describe mappings between relational DB schemas and ontologies implemented in RDF(S) or OWL. R2O provides an extensible set of primitives with welldefined semantics. This language has been conceived expressive enough to cope with complex mapping cases arisen from situations of low similarity between the ontology and the DB models

    Creating ontology-based metadata by annotation for the semantic web

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    Fund Finder: A case study of database-to-ontology mapping

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    The mapping between databases and ontologies is a basic problem when trying to "upgrade" deep web content to the semantic web. Our approach suggests the declarative definition of mappings as a way to achieve domain independency and reusability. A specific language (expressive enough to cover some real world mapping situations like lightly structured databases or not 1st normal form ones) is defined for this purpose. Along with this mapping description language, the ODEMapster processor is in charge of carrying out the effective instance data migration. We illustrate this by testing both the mappings definition and processor on a case study

    Using ontologies to synchronize change in relational database systems

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    Ontology is a building block of the semantic Web. Ontology building requires a detailed domain analysis, which in turn requires financial resources, intensive domain knowledge and time. Domain models in industry are frequently stored as relational database schemas in relational databases. An ontology base underlying such schemas can represent concepts and relationships that are present in the domain of discourse. However, with ever increasing demand for wider access and domain coverage, public databases are not static and their schemas evolve over time. Ontologies generated according to these databases have to change to reflect the new situation. Once a database schema is changed, these changes in the schema should also be incorporated in any ontology generated from the database. It is not possible to generate a fresh version of the ontology using the new database schema because the ontology itself may have undergone changes that need to be preserved. To tackle this problem, this paper presents a generic framework that will help to generate and synchronize ontologies with existing data sources. In particular we address the translation between ontologies and database schemas, but our proposal is also sufficiently generic to be used to generate and maintain ontologies based on XML and object oriented databases
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