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Milan: Automatic Generation of R2RML Mappings

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