Authors:
Cristiane A. G. Huve
1
;
Alex M. Porn
2
and
Leticia M. Peres
2
Affiliations:
1
Department of Informatics, Federal University of Paraná, Av. Cel. Francisco H. dos Santos, 100, Curitiba, Brazil, Polytechnic School, Uninter, Rua Luiz Xavier, 103, Curitiba and Brazil
;
2
Department of Informatics, Federal University of Paraná, Av. Cel. Francisco H. dos Santos, 100, Curitiba and Brazil
Keyword(s):
Mapping, Ontology, Relational Database, Mutation Test.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Collaboration and e-Services
;
Complex Systems Modeling and Simulation
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Integration/Interoperability
;
Interoperability
;
Knowledge Engineering and Ontology Development
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Model Driven Architectures and Engineering
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Sensor Networks
;
Simulation and Modeling
;
Software Agents and Internet Computing
;
Software and Architectures
;
Software Engineering
;
Symbolic Systems
;
Tools, Techniques and Methodologies for System Development
Abstract:
Ontologies are structures used to represent a specific domain. One well-known method to simplify the ontology building is to extract domain concepts from a relational database. This article presents an architecture which enables an automatic mapping process from a relational database to OWL ontology. It proposes to enrich the terminology of ontology elements and it was validated with mutation tests. The architecture mapping process makes use of new and existent mapping rules and overcome lacks not previously addressed, such as the use of database logic model to eliminate duplicated elements of ontology and mapping inheritance relationships from tables and records. We stand out the structure of element mapping, which allows maintaining source-to-target traceability for verification. We validate our approach with two experiments: the first one focuses on architecture validation applying an experiment with three scenarios and the second one uses a testing engine applying a mutation test
methodology to OWL ontology validation.
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