A Hybrid Approach to Query Answering Under Expressive Datalog$$^\pm $$

Datalog\(^\pm \) is a family of ontology languages that combine good computational properties with high expressive power. Datalog\(^\pm \) languages are provably able to capture many relevant Semantic Web languages. In this paper we consider the class of weakly-sticky (WS) Datalog\(^\pm \) programs, which allow for certain useful forms of joins in rule bodies as well as extending the well-known class of weakly-acyclic TGDs. So far, only nondeterministic algorithms were known for answering queries on WS Datalog\(^\pm \) programs. We present novel deterministic query answering algorithms under WS Datalog\(^\pm \). In particular, we propose: (1) a bottom-up grounding algorithm based on a query-driven chase, and (2) a hybrid approach based on transforming a WS program into a so-called sticky one, for which query rewriting techniques are known. We discuss how our algorithms can be optimized and effectively applied for query answering in real-world scenarios.