A Datalog Rewriting Algorithm for Warded Ontologies

Abstract

Existential rules, a.k.a. tuple-generating dependencies (TGDs), form a well-established formalism for specifying ontologies. In particular, the warded language is a well-behaved fragment of TGD-based ontologies, striking a good balance between expressive power and computational complexity of answering Ontology-Mediated Queries (OMQs). The theoretical foundations of answering OMQs over warded ontologies are by now well-understood, but to the best of our knowledge, very few efforts exist that exploit such a rich theory for building practical query answering algorithms. Our goal is to fill the above gap by designing a novel Datalog rewriting algorithm for OMQs over warded ontologies which is amenable to practical implementations, as well as providing an implementation and an experimental evaluation, with the aim of understanding how key input parameters affect the performance of this approach, and what are its limits when combined with off-the-shelf Datalog-based engines.

Cite

Text

Benedetto et al. "A Datalog Rewriting Algorithm for Warded Ontologies." International Joint Conference on Artificial Intelligence, 2025. doi:10.24963/IJCAI.2025/485

Markdown

[Benedetto et al. "A Datalog Rewriting Algorithm for Warded Ontologies." International Joint Conference on Artificial Intelligence, 2025.](https://mlanthology.org/ijcai/2025/benedetto2025ijcai-datalog/) doi:10.24963/IJCAI.2025/485

BibTeX

@inproceedings{benedetto2025ijcai-datalog,
  title     = {{A Datalog Rewriting Algorithm for Warded Ontologies}},
  author    = {Benedetto, Davide and Calautti, Marco and Hammad, Hebatalla and Sallinger, Emanuel and Vlad-Starrabba, Adriano},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2025},
  pages     = {4356-4364},
  doi       = {10.24963/IJCAI.2025/485},
  url       = {https://mlanthology.org/ijcai/2025/benedetto2025ijcai-datalog/}
}