RODI / IncMap: Relational-to-Ontology Data Integration
A major challenge in information management today is the integration of huge amounts of data distributed across multiple data sources. A suggested approach to this problem is ontology-based data integration where legacy data systems are integrated via a common ontology that represents a unified global view over all data sources. However, data is often not natively born using these ontologies. Instead, much data resides in legacy relational databases. Therefore, mappings that relate the legacy relational data sources to the ontology need to be constructed. Recent techniques and systems that automatically construct such mappings have been developed. The quality metrics of these systems are, however, often only based on self-designed benchmarks.
In this project, we design a new mapping system called IncMap and a new publicly available benchmarking suite called RODI, which is designed to cover a wide range of mapping challenges in Relational-to-Ontology Data Integration scenarios.
- IncMap is designed to incrementally map relational schemata to ontologies taking the feedback of users into account.
- RODI provides a set of different relational data sources and ontologies (representing a wide range of mapping challenges) as well as a scoring function with which the performance of relational-to-ontology mapping construction systems may be evaluated.
- Christoph Pinkel, Carsten Binnig, Ernesto Jiménez-Ruiz, Wolfgang May, Dominique Ritze, Martin G. Skjæveland, Alessandro Solimando, Evgeny Kharlamov: RODI: A Benchmark for Automatic Mapping Generation in Relational-to-Ontology Data Integration. ESWC 2015: 21-37
- Christoph Pinkel, Carsten Binnig, Peter Haase, Clemens Martin, Kunal Sengupta, Johannes Trame: How to Best Find a Partner? An Evaluation of Editing Approaches to Construct R2RML Mappings. ESWC 2014: 675-690
- Christoph Pinkel, Carsten Binnig, Evgeny Kharlamov, Peter Haase: IncMap: pay as you go matching of relational schemata to OWL ontologies. OM 2013: 37-48