Goal-directed tracing of inferences in EL ontologies

Abstract

ε L is a family of tractable Description Logics (DLs) that is the basis of the OWL 2 EL profile. Unlike for many expressive DLs, reasoning in ε L can be performed by computing a deductively-closed set of logical consequences of some specific form. In some ontology-based applications, e.g., for ontology debugging, knowing the logical consequences of the ontology axioms is often not sufficient. The user also needs to know from which axioms and how the consequences were derived. Although it is possible to record all inference steps during the application of rules, this is usually not done in practice to avoid the overheads. In this paper, we present a goal-directed method that can generate inferences for selected consequences in the deductive closure without re-applying all rules from scratch. We provide an empirical evaluation demonstrating that the method is fast and economical for large ε L ontologies. Although the main benefits are demonstrated for ε L reasoning, the method can be potentially applied to many other procedures based on deductive closure computation using fixed sets of rules.