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Milan: automatic generation of R2RML mappings

Mathur, Sahil Nakul, O’Sullivan, Declan and Brennan, Rob orcid logoORCID: 0000-0001-6546-6408 (2018) Milan: automatic generation of R2RML mappings. In: 26th Irish Conference on Artificial Intelligence and Cognitive Science (AICS 2018), 6-7 Dec 2018, Dublin, Ireland.

Abstract
Milan automatically generates R2RML mappings between a source relational database and a target ontology, using a novel multi-level algorithms. It address real world inter-model semantic gap by resolving naming conflicts, structural and semantic heterogeneity, thus enabling high fidelity mapping generation for realistic databases. Despite the importance of mappings for interoperability across relational databases and ontologies, a labour and expertise-intensive task, the current state of the art has achieved only limited automation. The paper describes an experimental evaluation of Milan with respect to the state of the art systems using the RODI benchmarking tool which shows that Milan outperforms all systems in all categories
Metadata
Item Type:Conference or Workshop Item (UNSPECIFIED)
Event Type:Conference
Uncontrolled Keywords:RDB2RDF; OBDA; Schema and Ontology Matching; Mapping Rules; Linked Data; Automatic Mapping
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > ADAPT
Published in: Proceedings for the 26th AIAI Irish Conference on Artificial Intelligence and Cognitive Science. 2259. CEUR -WS.
Publisher:CEUR -WS
Official URL:http://ceur-ws.org/Vol-2259/aics_10.pdf
Copyright Information:© 2018 The Authors
Funders:ADAPT Centre for Digital Content Technology, funded under the SFI Research Centres Programme (Grant 13/RC/2106) and co-funded by the European Regional Development Fund.
ID Code:22986
Deposited On:15 Feb 2019 12:51 by Thomas Murtagh . Last Modified 15 Feb 2019 12:51
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