OWL is a logic-based ontology language standard designed to promote interoperability, particularly in the context of the (Semantic) Web. The standard has encouraged the development of numerous OWL reasoning
systems, and such systems are already key components of many applications.
The goal of this workshop is to bring together the developers of reasoners for (subsets of) OWL, including systems focusing on both intensional (ontology) and extensional (data) query answering.
The workshop will give developers a perfect opportunity to promote their systems.
CALL FOR PAPERS --------------------------------------------------------------------------
Submissions are solicited from developers interested in describing OWL reasoning and query answering systems.
We invite submission of both SHORT SYSTEM DESCRIPTION papers and LONG SYSTEM DESCRIPTION AND EVALUATION papers. Papers should include a description of the system in question, including:
* language subset(s) supported;
* syntax(es) and interface(s) supported;
* reasoning algorithm(s) implemented;
* important optimisation techniques used;
* particular advantages (or disadvantages);
* application focus (e.g., large datasets, large ontologies, complex ontologies, etc.);
* other novel or interesting features.
Full papers should also include an evaluation (see guidelines), preferably using (some of) the datasets provided. Short papers may also include a brief performance analysis.
If possible, evaluations should use the standard datasets provided and present results for the following reasoning
tasks (where relevant for the system being evaluated):
* Classification. The dataset consists of a set of OWL ontologies. The total time taken to load and classify each ontology should be reported. It would also be interesting to report on comparisons of the computed taxonomy
with the "reference" taxonomies that are provided with the dataset (in preparation).
* Class satisfiability. The dataset consists of a set of OWL ontologies, and for each ontology one or more class URIs. The time taken to perform each test along with the satisfiability result for each class should be reported.
* Ontology satisfiability. That dataset consists of a set of OWL ontologies. The total time taken to load and test the satisfiability of each ontology should be reported, along with the satisfiability result for each ontology.
* Logical entailment. The dataset consists of a set of pairs of OWL ontologies. The total time take to determine if the first ontology entails the second ontology should be reported, along with the entailment result (true or false).
* Instance retrieval. The dataset is an OWL ontology and a class expression. For each ontology the total time taken to load the ontology and retrieve the sets of instances for each class expression should be reported. It would also be
interesting to report on comparisons of the retrieved instances with the "reference" set that are provided with the dataset.
It is suggested that full results of any evaluations performed are made available via the web, with summaries of the results
being included in the papers submission as space permits.
* Ian Horrocks, University of Oxford, UK * Mikalai Yatskevich, University of Oxford, UK * Ernesto Jiménez-Ruiz, University of Oxford, UK
* Franz Baader, TU Dresden, Germany * Jérôme Euzenat, INRIA, Grenoble, France * Pavel Klinov, Clark & Parsia, USA * Jeff Heflin, Lehigh University, PA, USA * Francisco Martin-Recuerda, Universidad Politécnica de Madrid, Spain
* Bijan Parsia, University of Manchester, UK * Stefan Schlobach, Vrije Universiteit Amsterdam, The Netherlands
For enquiries, please contact the Organisers at ore2012@...
-- Ernesto Jiménez-Ruiz Research Assistant
Department of Computer Science
University of Oxford Wolfson Building, Parks Road, Oxford OX1 3QD, UK