985 resultados para Ontology Engineering


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Knowledge resource reuse has become a popular approach within the ontology engineering field, mainly because it can speed up the ontology development process, saving time and money and promoting the application of good practices. The NeOn Methodology provides guidelines for reuse. These guidelines include the selection of the most appropriate knowledge resources for reuse in ontology development. This is a complex decision-making problem where different conflicting objectives, like the reuse cost, understandability, integration workload and reliability, have to be taken into account simultaneously. GMAA is a PC-based decision support system based on an additive multi-attribute utility model that is intended to allay the operational difficulties involved in the Decision Analysis methodology. The paper illustrates how it can be applied to select multimedia ontologies for reuse to develop a new ontology in the multimedia domain. It also demonstrates that the sensitivity analyses provided by GMAA are useful tools for making a final recommendation.

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Ontology antipatterns are structures that reflect ontology modelling problems, they lead to inconsistencies, bad reasoning performance or bad formalisation of domain knowledge. Antipatterns normally appear in ontologies developed by those who are not experts in ontology engineering. Based on our experience in ontology design, we have created a catalogue of such antipatterns in the past, and in this paper we describe how we can use SPARQL-DL to detect them. We conduct some experiments to detect them in a large OWL ontology corpus obtained from the Watson ontology search portal. Our results show that each antipattern needs a specialised detection method.

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This paper describes the main goals and outcomes of the EU-funded Framework 7 project entitled Semantic Evaluation at Large Scale (SEALS). The growth and success of the Semantic Web is built upon a wide range of Semantic technologies from ontology engineering tools through to semantic web service discovery and semantic search. The evaluation of such technologies ? and, indeed, assessments of their mutual compatibility ? is critical for their sustained improvement and adoption. The SEALS project is creating an open and sustainable platform on which all aspects of an evaluation can be hosted and executed and has been designed to accommodate most technology types. It is envisaged that the platform will become the de facto repository of test datasets and will allow anyone to organise, execute and store the results of technology evaluations free of charge and without corporate bias. The demonstration will show how individual tools can be prepared for evaluation, uploaded to the platform, evaluated according to some criteria and the subsequent results viewed. In addition, the demonstration will show the flexibility and power of the SEALS Platform for evaluation organisers by highlighting some of the key technologies used.

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Knowledge resource reuse has become a popular approach within the ontology engineering field, mainly because it can speed up the ontology development process, saving time and money and promoting the application of good practices. The NeOn Methodology provides guidelines for reuse. These guidelines include the selection of the most appropriate knowledge resources for reuse in ontology development. This is a complex decision-making problem where different conflicting objectives, like the reuse cost, understandability, integration workload and reliability, have to be taken into account simultaneously. GMAA is a PC-based decision support system based on an additive multi-attribute utility model that is intended to allay the operational difficulties involved in the Decision Analysis methodology. The paper illustrates how it can be applied to select multimedia ontologies for reuse to develop a new ontology in the multimedia domain. It also demonstrates that the sensitivity analyses provided by GMAA are useful tools for making a final recommendation.

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The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub; award reference: EP/G066051/1.

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* The work is partly supported by RFFI grant 08-07-00062-a

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This article presents the principal results of the Ph.D. thesis Intelligent systems in bioinformatics: mapping and merging anatomical ontologies by Peter Petrov, successfully defended at the St. Kliment Ohridski University of Sofia, Faculty of Mathematics and Informatics, Department of Information Technologies, on 26 April 2013.

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This paper proposes a preliminary classification of knowledge organization research, divided among epistemology, theory, and methodology plus three spheres of research: design, study, and critique. This work is situated in a metatheoretical framework, drawn from sociological thought. Example works are presented along with preliminary classification. The classification is then briefly described as a comparison tool which can be used to demonstrate overlap and divergence in cognate discourses of knowledge organization (such as ontology engineering).

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Historically, asset management focused primarily on the reliability and maintainability of assets; organisations have since then accepted the notion that a much larger array of processes govern the life and use of an asset. With this, asset management’s new paradigm seeks a holistic, multi-disciplinary approach to the management of physical assets. A growing number of organisations now seek to develop integrated asset management frameworks and bodies of knowledge. This research seeks to complement existing outputs of the mentioned organisations through the development of an asset management ontology. Ontologies define a common vocabulary for both researchers and practitioners who need to share information in a chosen domain. A by-product of ontology development is the realisation of a process architecture, of which there is also no evidence in published literature. To develop the ontology and subsequent asset management process architecture, a standard knowledge-engineering methodology is followed. This involves text analysis, definition and classification of terms and visualisation through an appropriate tool (in this case, the Protégé application was used). The result of this research is the first attempt at developing an asset management ontology and process architecture.

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© 2014, Springer-Verlag London. Engineering changes are essential for any product development, and their management has become a crucial discipline. Research in engineering change management has brought about some methods and tools to support dealing with changes. This work extends the change prediction method through incorporation of a function–behaviour–structure (FBS) scheme. These additional levels of detail provide the rationales for change propagation and allow a more proactive management of changes. First, we develop the ontology of this method based on a comprehensive comparison of three seminal functional reasoning schemes. Then, we demonstrate the FBS Linkage technique by applying it to a diesel engine. Finally, we evaluate the method.

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The main objective of this text is to warn against atmospherics. However comfortable it might appear, an atmosphere is politically suspicious because it numbs a body into an affective embrace of stability and permanence. It becomes doubly suspicious because a body desires to be part of the atmosphere. For this reason, I rethink both affect and atmosphere ontologically rather than phenomenologically. I argue that an atmosphere is engineered by subsuming individual affects to what I call, following Sloterdijk, an atmospheric glasshouse. I suggest that this happens in four steps: a distinction between inside and outside through partitioning; inclusion of the outside inside; illusion of synthesis; and dissimulation. In order to do this, I begin with air as the elemental paradox of ontological continuum and rupture. I carry on with the passage from air to atmosphere while retaining the discourse around continuum and rupture. Finally, I indicate a way of rupturing the atmospheric continuum through the ontological movement of withdrawal from the atmosphere. The ultimate goal of the article is to sketch a problematic of atmospherics that puts together without synthesising an elemental ontology of continuum and rupture.

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The main objective of this text is to warn against atmospherics. However comfortable it might appear, an atmosphere is politically suspicious because it numbs a body into an affective embrace of stability and permanence. It becomes doubly suspicious because a body desires to be part of the atmosphere. For this reason, I rethink both affect and atmosphere ontologically rather than phenomenologically. I argue that an atmosphere is engineered by subsuming individual affects to what I call, following Sloterdijk, an atmospheric glasshouse. I suggest that this happens in four steps: a distinction between inside and outside through partitioning; inclusion of the outside inside; illusion of synthesis; and dissimulation. In order to do this, I begin with air as the elemental paradox of ontological continuum and rupture. I carry on with the passage from air to atmosphere while retaining the discourse around continuum and rupture. Finally, I indicate a way of rupturing the atmospheric continuum through the ontological movement of withdrawal from the atmosphere. The ultimate goal of the article is to sketch a problematic of atmospherics that puts together without synthesising an elemental ontology of continuum and rupture.

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This paper describes the development of an ontology for autonomous systems, as the initial stage of a research programe on autonomous systems’ engineering within a model-based control approach. The ontology aims at providing a unified conceptual framework for the autonomous systems’ stakeholders, from developers to software engineers. The modular ontology contains both generic and domain-specific concepts for autonomous systems description and engineering. The ontology serves as the basis in a methodology to obtain the autonomous system’s conceptual models. The objective is to obtain and to use these models as main input for the autonomous system’s model-based control system.

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Autonomous systems refer to systems capable of operating in a real world environment without any form of external control for extended periods of time. Autonomy is a desired goal for every system as it improves its performance, safety and profit. Ontologies are a way to conceptualize the knowledge of a specific domain. In this paper an ontology for the description of autonomous systems as well as for its development (engineering) is presented and applied to a process. This ontology is intended to be applied and used to generate final applications following a model driven methodology.