In the last years, the vision of the Semantic Web fostered the interest in reasoning over ever larger sets of
assertional statements in ontologies. In this senario, state-of-the-art description logic reasoning systems cannot
deal with real-world ontologies any longer, since they rely on in-memory structures.
In these scenarios it will become more important to rely on unsound or incomplete reasoning structures, to
obtain a set of candidates/obvious solutions to queries, i.e. only apply state-of-the-art reasoning systems to the
computationally hard solutions. In this paper we propose a summarization-based approach which is always
sound, but possibly incomplete. We think that this technique will support description logic systems to deal
with the steadily growing amounts of assertional data.