Ontology-Enriched Query Answering on Relational Databases


  • Shqiponja Ahmetaj TU Wien, Austria
  • Vasilis Efthymiou FORTH, Greece
  • Ronald Fagin IBM Research - Almaden, USA
  • Phokion G. Kolaitis IBM Research - Almaden, USA UC Santa Cruz, USA
  • Chuan Lei IBM Research - Almaden, USA
  • Fatma Özcan Google, USA
  • Lucian Popa IBM Research - Almaden, USA




Query Answering, Data Exchange, OBDA


We develop a flexible, open-source framework for query answering on relational databases by adopting methods and techniques from the Semantic Web community and the data exchange community, and we apply this framework to a medical use case. We first deploy module-extraction techniques to derive a concise and relevant sub-ontology from an external reference ontology. We then use the chase procedure from the data exchange community to materialize a universal solution that can be subsequently used to answer queries on an enterprise medical database. Along the way, we identify a new class of well-behaved acyclic EL-ontologies extended with role hierarchies, suitably restricted functional roles, and domain/range restrictions, which cover our use case. We show that such ontologies are C-stratified, which implies that the chase procedure terminates in polynomial time. We provide a detailed overview of our real-life application in the medical domain and demonstrate the benefits of this approach, such as discovering additional answers and formulating new queries.




How to Cite

Ahmetaj, S., Efthymiou, V., Fagin, R., Kolaitis, P. G., Lei, C., Özcan, F., & Popa, L. (2021). Ontology-Enriched Query Answering on Relational Databases. Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 15247-15254. https://doi.org/10.1609/aaai.v35i17.17789



IAAI Technical Track on Emerging Applications of AI