Diego Calvanese, Tahir Emre Kalayci, Marco Montali, Ario Santoso, Wil M. P. van der Aalst. Conceptual Schema Transformation in Ontology-Based Data Access. In Catherine Faron-Zucker, Chiara Ghidini, Amedeo Napoli, Yannick Toussaint, editors, Knowledge Engineering and Knowledge Management - 21st International Conference, EKAW 2018, Nancy, France, November 12-16, 2018, Proceedings. Volume 11313 of Lecture Notes in Computer Science, pages 50-67, Springer, 2018.
Ontology-based Data Access (OBDA) is a by now well-established paradigm that relies on conceptually representing a domain of interest to provide access to relational data sources. The conceptual representation is given in terms of a domain schema (also called an ontology), which is linked to the data sources by means of declarative mapping specifications, and queries posed over the conceptual schema are automatically rewritten into queries over the sources. We consider the interesting setting where users would like to access the same data sources through a new conceptual schema, which we call the upper schema. This is particularly relevant when the upper schema is a reference model for the domain, or captures the data format used by data analysis tools. We propose a solution to this problem that is based on using transformation rules to map the upper schema to the domain schema, building upon the knowledge contained therein. We show how this enriched framework can be automatically transformed into a standard OBDA specification, which directly links the original relational data sources to the upper schema. This allows us to access data directly from the data sources while leveraging the domain schema and upper schema as a lens. We have realized the framework in a tool-chain that provides modeling of the conceptual schemas, a concrete annotation-based mechanism to specify transformation rules, and the automated generation of the final OBDA specification.