Data Complexity of Answering Unions of Conjunctive Queries in SHIQ

The novel context of accessing and querying large data repositories through ontologies that are formalized in terms of expressive DLs requires on the one hand to consider query answering as the primary inference technique, and on the other hand to optimize it with respect to the size of the data, which dominates the size of ontologies. While the complexity of DLs has been studied extensively, data complexity in expressive DLs has been characterized only for answering atomic queries, and was still open for more expressive query languages, such as unions of conjunctive queries (UCQs). In this paper we advocate the need for studying this problem, and provide a significant technical contribution in this direction. Specifically, we prove a tight coNP upper bound for answering UCQs over SHIQ knowledge bases, for the case where the queries do not contain transitive roles. We thus establish that for a whole range of DLs from AL to SHIQ, answering such UCQs has coNP-complete data complexity. W...

• Type: Conference
• Year: 2006
• Where: DLOG
• Authors: Magdalena Ortiz, Diego Calvanese, Thomas Eiter
• Keywords: Automated Reasoning, Data Complexity, DLOG 2006, Expressive Dls, Expressive Query Languages