Matches in ScholarlyData for { ?s ?p A major challenge in information management today is the integration of huge amounts of data distributed across multiple data sources. One suggested approach to this problem is ontology-based data integration where legacy data systems are integrated via a common on- tology that represents a unified global view over all data sources. In many domains (e.g., biology, medicine) there exist established ontolo- gies to integrate data from existing data sources. However, data is often not natively born using these ontologies. Instead, much data resides in relational databases. Therefore, mappings that relate the legacy data sources to the ontology need to be constructed. Recent techniques and systems that automatically construct such mappings have been devel- oped. The quality metrics of these systems are, however, often only based on self-designed, highly biased benchmarks. This paper introduces a new publicly available benchmarking suite called RODI which is designed to cover a wide range of integration challenges in Relational-to-Ontology Data Integration scenarios. RODI provides a set of different relational data sources and ontologies as well as a scoring function with which the performance of relational-to-ontology mapping construction systems may be evaluated.. }
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- 72 abstract "A major challenge in information management today is the integration of huge amounts of data distributed across multiple data sources. One suggested approach to this problem is ontology-based data integration where legacy data systems are integrated via a common on- tology that represents a unified global view over all data sources. In many domains (e.g., biology, medicine) there exist established ontolo- gies to integrate data from existing data sources. However, data is often not natively born using these ontologies. Instead, much data resides in relational databases. Therefore, mappings that relate the legacy data sources to the ontology need to be constructed. Recent techniques and systems that automatically construct such mappings have been devel- oped. The quality metrics of these systems are, however, often only based on self-designed, highly biased benchmarks. This paper introduces a new publicly available benchmarking suite called RODI which is designed to cover a wide range of integration challenges in Relational-to-Ontology Data Integration scenarios. RODI provides a set of different relational data sources and ontologies as well as a scoring function with which the performance of relational-to-ontology mapping construction systems may be evaluated.".