In Proceedings of the 14th Extended Semantic Web Conference: PhD Symposium (2017)
Ontology-Based Data Access systems provide access to non-RDF data using ontologies. These systems require mappings between the non-RDF data and ontologies to facilitate this access. Manually defining such mappings can become a costly process when dealing with large and complex data sources, and/or multiple data sources at the same time. This resulted in different mapping generation tools. While a number of these tools use knowledge from the original data, existing Linked Data, schemas, and/or mappings, they still fall short when dealing with complex challenges and the user effort can be high. In this paper, we propose an approach, together with an evaluation, that discovers and uses extended knowledge from existing (Linked) Data, schemas, query workload, and mappings, and combines it with knowledge provided by the mapping process to generate a new mapping. Our approach aims to improve the mapping quality, while decreasing the task complexity, and subsequently the user effort.