Ontology Engineering Group


Ontology Engineering Group

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Garijo D.,Ontology Engineering Group | Corcho O.,Ontology Engineering Group | Gil Y.,University of Southern California
Proceedings of the 7th International Conference on Knowledge Capture: "Knowledge Capture in the Age of Massive Web Data", K-CAP 2013 | Year: 2013

Provenance plays a major role when understanding and reusing the methods applied in a scientific experiment, as it provides a record of inputs, the processes carried out and the use and generation of intermediate and final results. In the specific case of in-silico scientific experiments, a large variety of scientific workflow systems (e.g., Wings, Taverna, Galaxy, Vistrails) have been created to support scientists. All of these systems produce some sort of provenance about the executions of the workflows that encode scientific experiments. However, provenance is normally recorded at a very low level of detail, which complicates the understanding of what happened during execution. In this paper we propose an approach to automatically obtain abstractions from low-level provenance data by finding common workflow fragments on workflow execution provenance and relating them to templates. We have tested our approach with a dataset of workflows published by the Wings workflow system. Our results show that by using these kinds of abstractions we can highlight the most common abstract methods used in the executions of a repository, relating different runs and workflow templates with each other. Copyright 2013 ACM.

Palma R.,Ontology Engineering Group | Palma R.,Poznan Supercomputing and Networking Center | Corcho O.,Ontology Engineering Group | Gomez-Perez A.,Ontology Engineering Group | And 2 more authors.
Journal of Web Semantics | Year: 2011

This paper describes our methodological and technological approach for collaborative ontology development in inter-organizational settings. It is based on the formalization of the collaborative ontology development process by means of an explicit editorial workflow, which coordinates proposals for changes among ontology editors in a flexible manner. This approach is supported by new models, methods and strategies for ontology change management in distributed environments: we propose a new form of ontology change representation, organized in layers so as to provide as much independence as possible from the underlying ontology languages, together with methods and strategies for their manipulation, version management, capture, storage and maintenance, some of which are based on existing proposals in the state of the art. Moreover, we propose a set of change propagation strategies that allow keeping distributed copies of the same ontology synchronized. Finally, we illustrate and evaluate our approach with a test case in the fishery domain from the United Nations Food and Agriculture Organisation (FAO). The preliminary results obtained from our evaluation suggest positive indication on the practical value and usability of the work here presented. © 2011 Elsevier B.V. All rights reserved.

Aranguren M.E.,Ontology Engineering Group | Antezana E.,Norwegian University of Science and Technology
ACM International Conference Proceeding Series | Year: 2012

Biomedical ontologies are key to the success of Semantic Web technologies in Life Sciences; therefore, it is important to provide appropriate tools for their development and further exploitation. The Ontology Pre Processor Language (OPPL) can be used for automating the complex manipulation needed to devise biomedical ontologies with richer axiomatic content, which in turn pave the way towards advanced biological data analyses. We present OPPL-Galaxy, an OPPL wrapper for the Galaxy platform, and a series of examples demonstrating its functionality for enriching ontologies. As Galaxy provides an integrated framework to make use of various bioinformatics tools, the functionality delivered by OPPL to manipulate ontologies can be combined along with the tools and workows devised in Galaxy. As a result, those workows can be used to perform more thorough analyses of biological information by exploiting extant biological knowledge codified in (enriched) biomedical ontologies. Copyright © 2011 ACM.

Xing W.,University of Manchester | Corcho O.,Ontology Engineering Group | Goble C.,University of Manchester | Dikaiakos M.D.,University of Cyprus
Future Generation Computer Systems | Year: 2010

We describe a semantic information service that aggregates metadata from a large number of information sources of a large-scale Grid infrastructure. It uses an ontology-based information integration architecture (ActOn) suitable for the highly dynamic distributed information sources available in Grid systems, where information changes frequently and where the information of distributed sources has to be aggregated in order to solve complex queries. These two challenges are addressed by a Metadata Cache that works with an update-on-demand policy and by an information source selection module that selects the most suitable source at a given point in time. We have evaluated the quality of this information service, and compared it with other similar services from the EGEE production testbed, with promising results. © 2009 Elsevier B.V. All rights reserved.

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