This paper describes a resolution based Description Logic reasoning system called DLog. DLog transforms Description Logic axioms into a Prolog program and uses the standard Prolog execution for efficiently answering instance retrieval queries. From the Description Logic point of view, DLog is an ABox reasoning engine for the full SHIQ language. The DLog approach makes it possible to store the individuals in a database instead of memory, which results in better scalability and helps using description logic ontologies directly on top of existing information sources. To appear in Theory and Practice of Logic Programming (TPLP).
The goal of this paper is to present how the Prolog Technology Theorem Proving (PTTP) approach can be used for ABox-reasoning. This work presents an inference algorithm over the language ALC, and evaluates its performance highlighting the advantages and drawbacks of this method.  In this paper we present a novel approach for determining the instances of description logic concepts when huge amounts of underlying data are expected. In such cases, traditional description logic theorem proving techniques cannot be used due to performance problems. Our idea is to transform a concept description into a Prolog program which represents a query-plan. This transformation is done without any knowledge of the particular data. Data are accessed dynamically during the normal Prolog execution of the generated program. With this technique only those pieces of data are accessed which are indeed important for answering the query, i.e. we solve the original problem in a database friendly way. We evaluate the performance of our approach and compare it to several description logic reasoners.