@conference {135, title = {EL-ifying Ontologies}, booktitle = {Automated Reasoning - 7th International Joint Conference, IJCAR 2014, Held as Part of the Vienna Summer of Logic, {VSL} 2014, Vienna, Austria, July 19-22, 2014. Proceedings}, year = {2014}, pages = {464{\textendash}479}, abstract = {

The OWL 2 profiles are fragments of the ontology language OWL 2 for which standard reasoning tasks are feasible in polynomial time. Many OWL ontologies, however, contain a typically small number of out-of-profile axioms, which may have little or no influence on reasoning outcomes. We investigate techniques for rewriting axioms into the EL and RL profiles of OWL 2. We have tested our techniques on both classification and data reasoning tasks with encouraging results.

}, keywords = {description logics, OWL, Rewriting, Tractable Reasoning}, doi = {10.1007/978-3-319-08587-6_36}, url = {http://dx.doi.org/10.1007/978-3-319-08587-6_36}, author = {David Carral and Cristina Feier and Cuenca Grau, Bernardo and Pascal Hitzler and Ian Horrocks} } @conference {131, title = {Pushing the Boundaries of Tractable Ontology Reasoning}, booktitle = {The Semantic Web - ISWC 2014 - 13th International Semantic Web Conference, Riva del Garda, Italy, October 19-23, 2014. Proceedings, Part II}, year = {2014}, pages = {148{\textendash}163}, abstract = {

We identify a class of Horn ontologies for which standard reasoning tasks such as instance checking and classification are tractable. The class is general enough to include the OWL 2 EL, QL, and RL profiles. Verifying whether a Horn ontology belongs to the class can be done in polynomial time. We show empirically that the class includes many real-world ontologies that are not included in any OWL 2 profile, and thus that polynomial time reasoning is possible for these ontologies.

}, keywords = {description logics, OWL, Tractable Reasoning}, doi = {10.1007/978-3-319-11915-1_10}, url = {http://dx.doi.org/10.1007/978-3-319-11915-1_10}, author = {David Carral and Cristina Feier and Cuenca Grau, Bernardo and Pascal Hitzler and Ian Horrocks} } @conference {134, title = {Is Your Ontology as Hard as You Think? Rewriting Ontologies into Simpler DLs}, booktitle = {Informal Proceedings of the 27th International Workshop on Description Logics, Vienna, Austria, July 17-20, 2014.}, year = {2014}, pages = {128{\textendash}140}, abstract = {

We investigate cases where an ontology expressed in a seemingly hard DL can be polynomially reduced to one in a simpler logic, while preserving reasoning outcomes for classification and fact entailment. Our transformations target the elimination of inverse roles, universal and existential restrictions, and in the best case allow us to rewrite the given ontology into one of the OWL 2 profiles. Even if an ontology cannot be fully rewritten into a profile, in many cases our transformations allow us to exploit further optimisation techniques. Moreover, the elimination of some out-of-profile axioms can improve the performance of modular reasoners, such as MORe. We have tested our techniques on both classification and data reasoning tasks with encouraging results.

}, keywords = {description logics, OWL, Tractable Reasoning}, url = {http://ceur-ws.org/Vol-1193/paper_75.pdf}, author = {David Carral and Cristina Feier and Ana Armas Romero and Cuenca Grau, Bernardo and Pascal Hitzler and Ian Horrocks} } @conference {130, title = {A Geo-ontology Design Pattern for Semantic Trajectories}, booktitle = {Spatial Information Theory - 11th International Conference, COSIT 2013, Scarborough, UK, September 2-6, 2013. Proceedings}, year = {2013}, pages = {438{\textendash}456}, abstract = {

Trajectory data have been used in a variety of studies, including human behavior analysis, transportation management, and wildlife tracking. While each study area introduces a different perspective, they share the need to integrate positioning data with domain-specific information. Semantic annotations are necessary to improve discovery, reuse, and integration of trajectory data from different sources. Consequently, it would be beneficial if the common structure encountered in trajectory data could be annotated based on a shared vocabulary, abstracting from domain-specific aspects. Ontology design patterns are an increasingly popular approach to define such flexible and self-contained building blocks of annotations. They appear more suitable for the annotation of interdisciplinary, multi-thematic, and multi-perspective data than the use of foundational and domain ontologies alone. In this paper, we introduce such an ontology design pattern for semantic trajectories. It was developed as a community effort across multiple disciplines and in a data-driven fashion. We discuss the formalization of the pattern using the Web Ontology Language (OWL) and apply the pattern to two different scenarios, personal travel and wildlife monitoring.

}, keywords = {Ontology Design Pattern, OWL, Trajectory}, doi = {10.1007/978-3-319-01790-7_24}, url = {http://dx.doi.org/10.1007/978-3-319-01790-7_24}, author = {Yingjie Hu and Krzysztof Janowicz and David Carral and Simon Scheider and Werner Kuhn and Gary Berg-Cross and Pascal Hitzler and Mike Dean and Dave Kolas} }