Paper 194 (Research track)

Milan: Automatic Generation of R2RML Mappings

Author(s): Sahil Nakul Mathur, Declan O’Sullivan, Rob Brennan

Abstract: Milan automatically generates R2RML mappings between a source relational database and a target ontology. It uses a novel multi-level algorithm to address the inter-model semantic gap by resolving naming conflicts and structural or semantic heterogeneity. This enables high fidelity mapping generation for realistic databases that are de-normalised or utilise features of the relational data model that do not easily map to RDF. Milan is unlike many state of the art mapping systems which first produce a direct mapping ontology, and then apply ontology alignment techniques. 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. An experimental evaluation of Milan with respect to the state of the art systems using the Relational-to-Ontology Data Integration (RODI) metric is provided which shows that Milan outperforms all systems in all categories.

Keywords: RDB2RDF; Automatic Mapping; Schema and Ontology Matching; OBDA; Mapping Rules; Linked Data

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