Talks and Poster Presentations (with Proceedings-Entry):

L. Bajraktari, M. Ortiz de la Fuente, G. Xiao:
"Optimizing Horn-SHIQ Reasoning for OBDA";
Talk: ISWC 2019 - International Semantic Web Conference, Auckland, New Zealand; 2019-10-26 - 2019-10-30; in: "The Semantic Web - {ISWC} 2019 - 18th International Semantic Web Conference, Auckland, New Zealand, October 26-30, 2019, Proceedings, Part {I}", Springer, 11778 (2019), ISBN: 978-3-030-30792-9; 75 - 92.

English abstract:
The ontology-based data access (OBDA) paradigm can ease access to heterogeneous and incomplete data sources in many application domains. However, state-of-the-art tools are still based on the DLLite family of description logics (DLs) that underlies OWL 2 QL, which despite its usefulness is not sufficiently expressive for many domains.
Accommodating more expressive ontology languages remains an open
challenge, and the consensus is that Horn DLs like Horn-SHIQ are
particularly promising. Query answering in Horn-SHIQ, a prerequisite
for OBDA, is supported in existing reasoners, but many ontologies cannot be handled. This is largely because algorithms build on an ABoxindependent approach to ontological reasoning that easily incurs in an exponential behaviour. As an alternative to full ABox-independence, in this paper we advocate taking into account general information about the structure of the ABoxes of interest. This is especially natural in the setting of OBDA, where ABoxes are generated via mappings, and thus have a predictable structure. We present a simple yet effective approach that guides ontological reasoning using the possible combinations of concepts that may occur in the ABox, which can be obtained from the mappings of an OBDA specification. We implemented and tested our optimization in the Clipper reasoner with encouraging results.

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Related Projects:
Project Head Mantas Simkus:

Created from the Publication Database of the Vienna University of Technology.