Ontology-Enriched Query Answering on Relational Databases

No. 17: IAAI-21, EAAI-21, AAAI-21 Special Programs and Special Track

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 35

IAAI Technical Track on Emerging Applications of AI

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.

10.1609/aaai.v35i17.17789