Monotone Abstractions in Ontology-Based Data Management


  • Gianluca Cima CNRS University of Bordeaux
  • Marco Console Sapienza University of Rome
  • Maurizio Lenzerini Sapienza University of Rome
  • Antonella Poggi Sapienza University of Rome



Knowledge Representation And Reasoning (KRR)


In Ontology-Based Data Management (OBDM), an abstraction of a source query q is a query over the ontology capturing the semantics of q in terms of the concepts and the relations available in the ontology. Since a perfect characterization of a source query may not exist, the notions of best sound and complete approximations of an abstraction have been introduced and studied in the typical OBDM context, i.e., in the case where the ontology is expressed in DL-Lite, and source queries are expressed as unions of conjunctive queries (UCQs). Interestingly, if we restrict our attention to abstractions expressed as UCQs, even best approximations of abstractions are not guaranteed to exist. Thus, a natural question to ask is whether such limitations affect even larger classes of queries. In this paper, we answer this fundamental question for an essential class of queries, namely the class of monotone queries. We define a monotone query language based on disjunctive Datalog enriched with an epistemic operator, and show that its expressive power suffices for expressing the best approximations of monotone abstractions of UCQs.




How to Cite

Cima, G., Console, M., Lenzerini, M., & Poggi, A. (2022). Monotone Abstractions in Ontology-Based Data Management. Proceedings of the AAAI Conference on Artificial Intelligence, 36(5), 5556-5563.



AAAI Technical Track on Knowledge Representation and Reasoning