<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>13</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Antrea Christou</style></author><author><style face="normal" font="default" size="100%">Chris Davis Jaldi</style></author><author><style face="normal" font="default" size="100%">Joseph Zalewski</style></author><author><style face="normal" font="default" size="100%">Hande Kucuk McGinty</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Cogan Shimizu</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">An Ontology for Representing Curriculum and Learning Material</style></title></titles><keywords><keyword><style  face="normal" font="default" size="100%">education</style></keyword><keyword><style  face="normal" font="default" size="100%">modular ontology design</style></keyword><keyword><style  face="normal" font="default" size="100%">ontology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2025</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://arxiv.org/abs/2506.05751</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Educational, learning, and training materials have become extremely commonplace across the Internet. Yet, they frequently remain disconnected from each other, fall into platform silos, and so on. One way to overcome this is to provide a mechanism to integrate the material and provide cross-links across topics.
In this paper, we present the Curriculum KG Ontology, which we use as a framework for the dense interlinking of educational materials, by first starting with organizational and broad pedagogical principles. We provide a materialized graph for the Prototype Open Knowledge Network use-case, and validate it using competency questions sourced from domain experts and educators. </style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cogan Shimizu</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Quinn Hirt</style></author><author><style face="normal" font="default" size="100%">Dean Rehberger</style></author><author><style face="normal" font="default" size="100%">Seila Gonzalez Estrecha</style></author><author><style face="normal" font="default" size="100%">Catherine Foley</style></author><author><style face="normal" font="default" size="100%">Alicia M. Sheill</style></author><author><style face="normal" font="default" size="100%">Walter Hawthorne</style></author><author><style face="normal" font="default" size="100%">Jeff Mixter</style></author><author><style face="normal" font="default" size="100%">Ethan Watrall</style></author><author><style face="normal" font="default" size="100%">Ryan Carty</style></author><author><style face="normal" font="default" size="100%">Duncan Tarr</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The Enslaved Ontology: Peoples of the Historic Slave Trade</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Web Semantics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">data integration</style></keyword><keyword><style  face="normal" font="default" size="100%">digital humanities</style></keyword><keyword><style  face="normal" font="default" size="100%">history of the slave trade</style></keyword><keyword><style  face="normal" font="default" size="100%">modular ontology</style></keyword><keyword><style  face="normal" font="default" size="100%">Ontology Design Patterns</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2020</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">63</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We present the Enslaved Ontology (V1.0) which was developed for integrating data about the historic slave trade from diverse sources in a use case driven by historians. Ontology development followed modular ontology design principles as derived from ontology design pattern application best practices and the eXtreme Design Methodology. Ontology content focuses on data about historic persons and the event records from which this data can be taken. It also incorporates provenance modeling and some temporal and spatial aspects. The ontology is available as serialized in the Web Ontology Language OWL, and carries modularization annotations using the Ontology Pattern Language (OPLa). It is available under the Creative Commons CC BY 4.0 license.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cogan Shimizu</style></author><author><style face="normal" font="default" size="100%">Aaron Eberhart</style></author><author><style face="normal" font="default" size="100%">Nazifa Karima</style></author><author><style face="normal" font="default" size="100%">Quinn Hirt</style></author><author><style face="normal" font="default" size="100%">Adila Krisnadhi</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Method for Automatically Generating Schema Diagrams for OWL Ontologies</style></title><secondary-title><style face="normal" font="default" size="100%">1st Iberoamerican Knowledge Graph and Semantic Web Conference (KGSWC)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">design patterns</style></keyword><keyword><style  face="normal" font="default" size="100%">evaluation</style></keyword><keyword><style  face="normal" font="default" size="100%">implementation</style></keyword><keyword><style  face="normal" font="default" size="100%">ontology</style></keyword><keyword><style  face="normal" font="default" size="100%">schema diagrams</style></keyword><keyword><style  face="normal" font="default" size="100%">visualization</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">06/2019</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Villa Clara, Cuba</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Interest in Semantic Web technologies, including knowledge graphs and ontologies, is increasing rapidly in industry and academics. In order to support ontology engineers and domain experts, it is necessary to provide them with robust tools that facilitate the ontology engineering process. Often, the schema diagram of an ontology is the most important tool for quickly conveying the overall purpose of an ontology. In this paper, we present a method for programmatically generating a schema diagram from an OWL file. We evaluate its ability to generate schema diagrams similar to manually drawn schema diagrams and show that it outperforms VOWL and OWLGrEd. In addition, we provide a prototype implementation of this tool.&lt;/p&gt;
</style></abstract><section><style face="normal" font="default" size="100%">149-161</style></section></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Raghava Mutharaju</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Prabhaker Mateti</style></author><author><style face="normal" font="default" size="100%">Freddy Lécué</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Distributed and Scalable OWL EL Reasoning</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 12th Extended Semantic Web Conference (ESWC 2015) </style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">DistEL</style></keyword><keyword><style  face="normal" font="default" size="100%">Distributed Reasoning</style></keyword><keyword><style  face="normal" font="default" size="100%">Ontology Classification</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL EL</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Portoroz, Slovenia</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;OWL 2 EL is one of the tractable proles of the Web Ontology&amp;nbsp;Language (OWL) which is a W3C-recommended standard. OWL 2&amp;nbsp;EL provides sucient expressivity to model large biomedical ontologies&amp;nbsp;as well as streaming data such as trac, while at the same time allows&amp;nbsp;for ecient reasoning services. Existing reasoners for OWL 2 EL, however,&amp;nbsp;use only a single machine and are thus constrained by memory and&amp;nbsp;computational power. At the same time, the automated generation of&amp;nbsp;ontological information from streaming data and text can lead to very&amp;nbsp;large ontologies which can exceed the capacities of these reasoners. We&amp;nbsp;thus describe a distributed reasoning system that scales well using a cluster&amp;nbsp;of commodity machines. We also apply our system to a use case on&amp;nbsp;city trac data and show that it can handle volumes which cannot be&amp;nbsp;handled by current single machine reasoners.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Carral</style></author><author><style face="normal" font="default" size="100%">Adila Krisnadhi</style></author><author><style face="normal" font="default" size="100%">Sebastian Rudolph</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">C. Maria Keet</style></author><author><style face="normal" font="default" size="100%">Valentina A. M. Tamma</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">All But Not Nothing: Left-Hand Side Universals for Tractable OWL Profiles</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 11th International Workshop on OWL: Experiences and Directions (OWLED 2014) co-located with 13th International Semantic Web Conference on (ISWC 2014), Riva del Garda, Italy, October 17-18, 2014.</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">description logics</style></keyword><keyword><style  face="normal" font="default" size="100%">Horn Logics</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2014</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ceur-ws.org/Vol-1265/owled2014_submission_13.pdf</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">CEUR-WS.org</style></publisher><volume><style face="normal" font="default" size="100%">1265</style></volume><pages><style face="normal" font="default" size="100%">97-108</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We show that occurrences of the universal quantifier in the left-hand side of general concept inclusions can be rewritten into EL++ axioms under certain circumstances. I.e., this intuitive modeling feature is available for OWL EL while retaining tractability. Furthermore, this rewriting makes it possible to reason over corresponding extensions of EL++ and Horn-SROIQ using standard reasoners.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michelle Cheatham</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Peter Mika</style></author><author><style face="normal" font="default" size="100%">Tania Tudorache</style></author><author><style face="normal" font="default" size="100%">Abraham Bernstein</style></author><author><style face="normal" font="default" size="100%">Chris Welty</style></author><author><style face="normal" font="default" size="100%">Craig A. Knoblock</style></author><author><style face="normal" font="default" size="100%">Denny Vrandecic</style></author><author><style face="normal" font="default" size="100%">Paul T. Groth</style></author><author><style face="normal" font="default" size="100%">Natasha F. Noy</style></author><author><style face="normal" font="default" size="100%">Krzysztof Janowicz</style></author><author><style face="normal" font="default" size="100%">Carole A. Goble</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Conference v2.0: An uncertain version of the OAEI Conference benchmark</style></title><secondary-title><style face="normal" font="default" size="100%">13th International Semantic Web Conference (ISWC 2014)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">benchmark</style></keyword><keyword><style  face="normal" font="default" size="100%">OAEI</style></keyword><keyword><style  face="normal" font="default" size="100%">Ontology Alignment</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Lecture Notes in Computer Science, Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Riva del Garda, Italy</style></pub-location><volume><style face="normal" font="default" size="100%">8797</style></volume><pages><style face="normal" font="default" size="100%">148-163</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The Ontology Alignment Evaluation Initiative is a set of benchmarks for evaluating the performance of ontology alignment systems. In this paper we re-examine the Conference track of the OAEI, with a focus on the degree of agreement between the reference alignments within this track and the opinion of experts. We propose a new version of this benchmark that more closely corresponds to expert opinion and confidence on the matches. The performance of top alignment systems is compared on both versions of the benchmark. Additionally, a general method for crowdsourcing the development of more benchmarks of this type using Amazon’s Mechanical Turk is introduced and shown to be scalable, cost-effective and to agree well with expert opinion.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Raghava Mutharaju</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Prabhaker Mateti</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Thorsten Liebig</style></author><author><style face="normal" font="default" size="100%">Achille Fokoue</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Distributed OWL EL Reasoning: The Story So Far</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 10th International Workshop on Scalable Semantic Web Knowledge Base Systems, Riva Del Garda, Italy</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Distributed Reasoning</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL EL</style></keyword><keyword><style  face="normal" font="default" size="100%">Scalability</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">CEUR-WS.org</style></publisher><pub-location><style face="normal" font="default" size="100%">Riva del Garda, Italy</style></pub-location><volume><style face="normal" font="default" size="100%">1261</style></volume><pages><style face="normal" font="default" size="100%">61-76</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Automated generation of axioms from streaming data, such as traffic and text, can result in very large ontologies that single machine reasoners cannot handle. Reasoning with large ontologies requires distributed solutions. Scalable reasoning techniques for RDFS, OWL Horst and OWL 2 RL now exist. For OWL 2 EL, several distributed reasoning approaches have been tried, but are all perceived to be inefficient. We analyze this perception. We analyze completion rule based distributed approaches, using different characteristics, such as dependency among the rules, implementation optimizations, how axioms and rules are distributed. We also present a distributed queue approach for the classification of ontologies in description logic EL+ (fragment of OWL 2 EL).&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Carral</style></author><author><style face="normal" font="default" size="100%">Cristina Feier</style></author><author><style face="normal" font="default" size="100%">Cuenca Grau, Bernardo</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Ian Horrocks</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">EL-ifying Ontologies</style></title><secondary-title><style face="normal" font="default" size="100%">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</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">description logics</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword><keyword><style  face="normal" font="default" size="100%">Rewriting</style></keyword><keyword><style  face="normal" font="default" size="100%">Tractable Reasoning</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-319-08587-6_36</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">464–479</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Carral</style></author><author><style face="normal" font="default" size="100%">Cristina Feier</style></author><author><style face="normal" font="default" size="100%">Cuenca Grau, Bernardo</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Ian Horrocks</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pushing the Boundaries of Tractable Ontology Reasoning</style></title><secondary-title><style face="normal" font="default" size="100%">The Semantic Web - ISWC 2014 - 13th International Semantic Web Conference, Riva del Garda, Italy, October 19-23, 2014. Proceedings, Part II</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">description logics</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword><keyword><style  face="normal" font="default" size="100%">Tractable Reasoning</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-319-11915-1_10</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">148–163</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kunal Sengupta</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Krzysztof Janowicz</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">T. Supnithi</style></author><author><style face="normal" font="default" size="100%">T. Yamaguchi</style></author><author><style face="normal" font="default" size="100%">Jeff Z. Pan</style></author><author><style face="normal" font="default" size="100%">V. Wuwongse</style></author><author><style face="normal" font="default" size="100%">M. Buranarach</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Revisiting default description logics – and their role in aligning ontologies</style></title><secondary-title><style face="normal" font="default" size="100%">Semantic Technology, 4th Joint International Conference, JIST 2014</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">default logic</style></keyword><keyword><style  face="normal" font="default" size="100%">defaults</style></keyword><keyword><style  face="normal" font="default" size="100%">description logics</style></keyword><keyword><style  face="normal" font="default" size="100%">Ontology Alignment</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Lecture Notes in Computer Science, Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Chiang Mai, Thailand</style></pub-location><volume><style face="normal" font="default" size="100%">8943</style></volume><pages><style face="normal" font="default" size="100%">3-18</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We present a new approach to extend the Web Ontology Language (OWL) with the capabilities to reason with defaults. This work improves upon the previously established results on integrating defaults with description logics (DLs), which were shown to be decidable only when the application of defaults is restricted to named individuals in the knowledge base. We demonstrate that the application of defaults (integrated with DLs) does not have to be restricted to named individuals to retain decidability and elaborate on the application of defaults in the context of ontology alignment and ontology-based systems.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Carral</style></author><author><style face="normal" font="default" size="100%">Cristina Feier</style></author><author><style face="normal" font="default" size="100%">Ana Armas Romero</style></author><author><style face="normal" font="default" size="100%">Cuenca Grau, Bernardo</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Ian Horrocks</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Is Your Ontology as Hard as You Think? Rewriting Ontologies into Simpler DLs</style></title><secondary-title><style face="normal" font="default" size="100%">Informal Proceedings of the 27th International Workshop on Description Logics, Vienna, Austria, July 17-20, 2014.</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">description logics</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword><keyword><style  face="normal" font="default" size="100%">Tractable Reasoning</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://ceur-ws.org/Vol-1193/paper_75.pdf</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">128–140</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Raghava Mutharaju</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Prabhaker Mateti</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Thorsten Liebig</style></author><author><style face="normal" font="default" size="100%">Achille Fokoue</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">DistEL: A Distributed EL+ Ontology Classifier</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 9th International Workshop on Scalable Semantic Web Knowledge Base Systems, co-located with the International Semantic Web Conference (ISWC 2013)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Classification</style></keyword><keyword><style  face="normal" font="default" size="100%">DistEL</style></keyword><keyword><style  face="normal" font="default" size="100%">Distributed Reasoning</style></keyword><keyword><style  face="normal" font="default" size="100%">EL+</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword><keyword><style  face="normal" font="default" size="100%">Scalability</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2013</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">CEUR-WS.org</style></publisher><pub-location><style face="normal" font="default" size="100%">Sydney, Australia</style></pub-location><volume><style face="normal" font="default" size="100%">1046</style></volume><pages><style face="normal" font="default" size="100%">17-32</style></pages><abstract><style face="normal" font="default" size="100%">OWL 2 EL ontologies are used to model and reason over data from diverse domains such as biomedicine, geography and road traffic. Data in these domains is increasing at a rate quicker than the increase in main memory and computation power of a single machine. Recent efforts in OWL reasoning algorithms lead to the decrease in classification time from several hours to a few seconds even for large ontologies like SNOMED CT. This is especially true for ontologies in the description logic EL+ (a fragment of the OWL 2 EL profile). Reasoners such as Pellet, Hermit, ELK etc. make an assumption that the ontology would fit in the main memory, which is unreasonable given projected increase in data volumes. Increase in the data volume also necessitates an increase in the computation power. This lead us to the use of a distributed system, so that memory and computation requirements can be spread across machines. We present a distributed system for the classification of EL+ ontologies along with some results on its scalability and performance.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Yingjie Hu</style></author><author><style face="normal" font="default" size="100%">Krzysztof Janowicz</style></author><author><style face="normal" font="default" size="100%">David Carral</style></author><author><style face="normal" font="default" size="100%">Simon Scheider</style></author><author><style face="normal" font="default" size="100%">Werner Kuhn</style></author><author><style face="normal" font="default" size="100%">Gary Berg-Cross</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Mike Dean</style></author><author><style face="normal" font="default" size="100%">Dave Kolas</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Geo-ontology Design Pattern for Semantic Trajectories</style></title><secondary-title><style face="normal" font="default" size="100%">Spatial Information Theory - 11th International Conference, COSIT 2013, Scarborough, UK, September 2-6, 2013. Proceedings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Ontology Design Pattern</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword><keyword><style  face="normal" font="default" size="100%">Trajectory</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-319-01790-7_24</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">438–456</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Carral</style></author><author><style face="normal" font="default" size="100%">Simon Scheider</style></author><author><style face="normal" font="default" size="100%">Krzysztof Janowicz</style></author><author><style face="normal" font="default" size="100%">Charles Vardeman</style></author><author><style face="normal" font="default" size="100%">Adila Krisnadhi</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Philipp Cimiano</style></author><author><style face="normal" font="default" size="100%">Óscar Corcho</style></author><author><style face="normal" font="default" size="100%">Valentina Presutti</style></author><author><style face="normal" font="default" size="100%">Laura Hollink</style></author><author><style face="normal" font="default" size="100%">Sebastian Rudolph</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">An Ontology Design Pattern for Cartographic Map Scaling</style></title><secondary-title><style face="normal" font="default" size="100%">The Semantic Web: Semantics and Big Data, 10th International Conference, ESWC 2013, Montpellier, France, May 26-30, 2013. Proceedings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Map Scaling</style></keyword><keyword><style  face="normal" font="default" size="100%">Ontology Design Patterns</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-642-38288-8_6</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><volume><style face="normal" font="default" size="100%">7882</style></volume><pages><style face="normal" font="default" size="100%">76–93</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The concepts of scale is at the core of cartographic abstraction and mapping. It defines which geographic phenomena should be displayed, which type of geometry and map symbol to use, which measures can be taken, as well as the degree to which features need to be exaggerated or spatially displaced. In this work, we present an ontology design pattern for map scaling using the Web Ontology Language (OWL) within a particular extension of the OWL RL profile. We explain how it can be used to describe scaling applications, to reason over scale levels, and geometric representations. We propose an axiomatization that allows us to impose meaningful constraints on the pattern, and, thus, to go beyond simple surface semantics. Interestingly, this includes several functional constraints currently not expressible in any of the OWL profiles. We show that for this specific scenario, the addition of such constraints does not increase the reasoning complexity which remains tractable.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Frederick Maier</style></author><author><style face="normal" font="default" size="100%">Yue Ma</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Paraconsistent OWL and Related Logics</style></title><secondary-title><style face="normal" font="default" size="100%">Semantic Web</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Automated Deduction</style></keyword><keyword><style  face="normal" font="default" size="100%">Complexity</style></keyword><keyword><style  face="normal" font="default" size="100%">Description Logic</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword><keyword><style  face="normal" font="default" size="100%">Paraconsistency</style></keyword><keyword><style  face="normal" font="default" size="100%">Semantic Web</style></keyword><keyword><style  face="normal" font="default" size="100%">Web Ontology Language</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.3233/SW-2012-0066</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">395–427</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The Web Ontology Language OWL is currently the most prominent formalism for representing ontologies in Semantic Web applications. OWL is based on description logics, and automated reasoners are used to infer knowledge implicitly present in OWL ontologies. However, because typical description logics obey the classical principle of explosion, reasoning over inconsistent ontologies is impossible in OWL. This is so despite the fact that inconsistencies are bound to occur in many realistic cases, e.g., when multiple ontologies are merged or when ontologies are created by machine learning or data mining tools. In this paper, we present four-valued paraconsistent description logics which can reason over inconsistencies. We focus on logics corresponding to OWL DL and its profiles. We present the logic SROIQ4, showing that it is both sound relative to classical SROIQ and that its embedding into SROIQ is consequence preserving. We also examine paraconsistent varieties of EL++, DL-Lite, and Horn-DLs. The general framework described here has the distinct advantage of allowing classical reasoners to draw sound but nontrivial conclusions from even inconsistent knowledge bases. Truth-value gaps and gluts can also be selectively eliminated from models (by inserting additional axioms into knowledge bases). If gaps but not gluts are eliminated, additional classical conclusions can be drawn without affecting paraconsistency.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Carral</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Extending Description Logic Rules</style></title><secondary-title><style face="normal" font="default" size="100%">The Semantic Web: Research and Applications - 9th Extended Semantic Web Conference, ESWC 2012, Heraklion, Crete, Greece, May 27-31, 2012. Proceedings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">description logics</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword><keyword><style  face="normal" font="default" size="100%">Rules</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-642-30284-8_30</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">345–359</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Description Logics – the logics underpinning the Web Ontology Language OWL – and rules are currently the most prominent paradigms used for modeling knowledge for the Semantic Web. While both of these approaches are based on classical logic, the paradigms also differ significantly, so that naive combinations result in undesirable properties such as undecidability. Recent work has shown that many rules can in fact be expressed in OWL. In this paper we extend this work to include some types of rules previously excluded. We formally define a set of first order logic rules, C-Rules, which can be expressed within OWL extended with role conjunction. We also show that the use of nominal schemas results in even broader coverage.&lt;/p&gt;
</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">David Carral</style></author><author><style face="normal" font="default" size="100%">Krzysztof Janowicz</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A logical geo-ontology design pattern for quantifying over types</style></title><secondary-title><style face="normal" font="default" size="100%">SIGSPATIAL 2012 International Conference on Advances in Geographic Information Systems (formerly known as GIS), SIGSPATIAL'12, Redondo Beach, CA, USA, November 7-9, 2012</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Biodiversity</style></keyword><keyword><style  face="normal" font="default" size="100%">description logics</style></keyword><keyword><style  face="normal" font="default" size="100%">Ontology Design Patterns</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://doi.acm.org/10.1145/2424321.2424352</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">239–248</style></pages><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Matthias Knorr</style></author><author><style face="normal" font="default" size="100%">David Carral</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author><author><style face="normal" font="default" size="100%">Adila Krisnadhi</style></author><author><style face="normal" font="default" size="100%">Frederick Maier</style></author><author><style face="normal" font="default" size="100%">Cong Wang</style></author></authors><secondary-authors><author><style face="normal" font="default" size="100%">Markus Krötzsch</style></author><author><style face="normal" font="default" size="100%">Umberto Straccia</style></author></secondary-authors></contributors><titles><title><style face="normal" font="default" size="100%">Recent Advances in Integrating OWL and Rules</style></title><secondary-title><style face="normal" font="default" size="100%">Web Reasoning and Rule Systems - 6th International Conference, RR 2012, Vienna, Austria, September 10-12, 2012. Proceedings</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">description logics</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword><keyword><style  face="normal" font="default" size="100%">Rules</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">09/2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1007/978-3-642-33203-6_20</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Springer</style></publisher><pub-location><style face="normal" font="default" size="100%">Austria, Vienna</style></pub-location><volume><style face="normal" font="default" size="100%">7497</style></volume><pages><style face="normal" font="default" size="100%">225-228</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">As part of the quest for a unifying logic for the Semantic Web Technology Stack, a central issue is finding suitable ways of integrating description logics based on the Web Ontology Language (OWL) with rule-based approaches based on logic programming. Such integration is difficult since naive approaches typically result in the violation of one or more desirable design principles. For example, while both OWL 2 DL and RIF Core (a dialect of the Rule Interchange Format RIF) are decidable, their naive union is not, unless carefully chosen syntactic restrictions are applied.

We report on recent advances and ongoing work by the authors in integrating OWL and rulesWe take an OWL-centric perspective, which means that we take OWL 2 DL as a starting point and pursue the question of how features of rulebased formalisms can be added without jeopardizing decidability. We also report on incorporating the closed world assumption and on reasoning algorithms. This paper essentially serves as an entry point to the original papers, to which we will refer throughout, where detailed expositions of the results can be found.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Matthias Knorr</style></author><author><style face="normal" font="default" size="100%">José Júlio Alferes</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Local Closed World Reasoning with Description Logics under the Well-Founded Semantics</style></title><secondary-title><style face="normal" font="default" size="100%">Artificial Intelligence</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Description Logic</style></keyword><keyword><style  face="normal" font="default" size="100%">Knowledge representation</style></keyword><keyword><style  face="normal" font="default" size="100%">Logic Programming</style></keyword><keyword><style  face="normal" font="default" size="100%">Non-monotonic reasoning</style></keyword><keyword><style  face="normal" font="default" size="100%">Ontologies</style></keyword><keyword><style  face="normal" font="default" size="100%">Semantic Web</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://dx.doi.org/10.1016/j.artint.2011.01.007</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">175</style></volume><pages><style face="normal" font="default" size="100%">1528–1554</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;An important question for the upcoming Semantic Web is how to best combine open world ontology languages, such as the OWL-based ones, with closed world rule-based languages. One of the most mature proposals for this combination is known as hybrid MKNF knowledge bases [52], and it is based on an adaptation of the Stable Model Semantics to knowledge bases consisting of ontology axioms and rules. In this paper we propose a well-founded semantics for nondisjunctive hybrid MKNF knowledge bases that promises to provide better efficiency of reasoning, and that is compatible with both the OWL-based semantics and the traditional Well-Founded Semantics for logic programs. Moreover, our proposal allows for the detection of inconsistencies, possibly occurring in tightly integrated ontology axioms and rules, with only little additional effort. We also identify tractable fragments of the resulting language.&lt;/p&gt;
</style></abstract><issue><style face="normal" font="default" size="100%">9-10</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Jens Lehmann</style></author><author><style face="normal" font="default" size="100%">Pascal Hitzler</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Concept learning in description logics using refinement operators</style></title><secondary-title><style face="normal" font="default" size="100%">Machine Learning</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">description logics</style></keyword><keyword><style  face="normal" font="default" size="100%">Inductive logic programming</style></keyword><keyword><style  face="normal" font="default" size="100%">OWL</style></keyword><keyword><style  face="normal" font="default" size="100%">refinement operators</style></keyword><keyword><style  face="normal" font="default" size="100%">Semantic Web</style></keyword><keyword><style  face="normal" font="default" size="100%">Structured Machine Learning</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://springerlink.metapress.com/content/c040n45u15qrnu44/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">78</style></volume><pages><style face="normal" font="default" size="100%">203–250</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p class=&quot;rtejustify&quot;&gt;With the advent of the Semantic Web, description logics have become one of the most prominent paradigms for knowledge representation and reasoning. Progress in research and applications, however, is constrained by the lack of well-structured knowledge bases consisting of a sophisticated schema and instance data adhering to this schema. It is paramount that suitable automated methods for their acquisition, maintenance, and evolution will be developed. In this paper, we provide a learning algorithm based on refinement operators for the description logic ALCQ including support for concrete roles. We develop the algorithm from thorough theoretical foundations by identifying possible abstract property combinations which refinement operators for description logics can have. Using these investigations as a basis, we derive a practically useful complete and proper refinement operator. The operator is then cast into a learning algorithm and evaluated using our implementation DL-Learner. The results of the evaluation show that our approach is superior to other learning approaches on description logics, and is competitive with established ILP systems.&lt;/p&gt;
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