2 research outputs found
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 categorie
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 categorie