Upper ontology

About: Upper ontology is a research topic. Over the lifetime, 9767 publications have been published within this topic receiving 220721 citations. The topic is also known as: top-level ontology & foundation ontology.

Using Goal Modeling to Capture Competency Questions in Ontology-based Systems

Abstract: Most of the available ontology engineering methodologies presuppose the existence of a set of questions which provide the objective and scope of the ontology under development. However, these so-called competency questions are not always clear from start. In this sense, such competency questions are comparable to system requirements, elicited and modeled during the requirements engineering stage of a software development process. Having this in mind, this work proposes the use of the Tropos methodology to help the ontology engineer reason and model competency questions. For that, he should follow the traditional Tropos process, starting with the early requirements activity to analyze the objectives of an organization. This initial stage is followed by the late requirements activity, in which the competency question are captured and linked to the organization’s goals, following the goal modeling process. In this way, we aim at providing a methodology which will consistently drive the ontology engineer in developing an ontology from scratch.

Instance-Based Ontology Population Exploiting Named-Entity Substitution

Abstract: We present an approach to ontology population based on a lexical substitution technique. It consists in estimating the plausibility of sentences where the named entity to be classified is substituted with the ones contained in the training data, in our case, a partially populated ontology. Plausibility is estimated by using Web data, while the classification algorithm is instance-based. We evaluated our method on two different ontology population tasks. Experiments show that our solution is effective, outperforming existing methods, and it can be applied to practical ontology population problems.

Ontology Engineering for Distributed Collaboration in Manufacturing

Abstract: The problems of inter-operability are acute for manufacturing applications, as applications using process specifications do not necessarily share syntax and definitions of concepts. The Process Specification Language developed at the National Institute of Standards and Technology proposes a formal ontology and translation mechanisms representing manufacturing concepts. When an application becomes ‘PSL compliant,’ its concepts are expressed using PSL, with a direct one-to-one mapping or with a mapping under certain conditions. An example of how to resolve semantic ambiguities is provided for the manufacturing concept ‘resource’. Finally some ideas on how to use PSL for inter-operability in agent-based systems are presented.

The Logic of Biological Classification and the Foundations of Biomedical Ontology

Abstract: Biomedical research is increasingly a matter of the navigation through large computerized information resources deriving from functional genomics or from the biochemistry of disease pathways. To make such navigation possible, controlled vocabularies are needed in terms of which data from different sources can be unified. One of the most influential developments in this regard is the so-called Gene Ontology, which consists of controlled vocabularies of terms used by biologists to describe cellular constituents, biological processes and molecular functions, organized into hierarchies via the relation of class subsumption. Here we seek to provide a rigorous account of the logic of classification that underlies GO and similar biomedical ontologies. Drawing on Aristotle, we develop a system of axioms and definitions for the treatment of biological classes and instances. Introduction In reflection of the huge amounts of data accumulating in areas such as genomics and proteomics, biology and biomedicine have come to rely increasingly on the use of computational methods in their research. One of the most impressive and influential developments in this regard is the so-called Gene Ontology (GO), which is being developed as part of the effort to produce controlled vocabularies for shared use across different biological domains within the framework of the Open Biological Ontologies project. We take GO as our test case in what follows, not only because it has proved so successful in serving as a common reference system for a variety of groups working at the forefront of biomedical research, but also because, as we shall see, it suffers from a series of problems which are characteristic of almost all current ontologies used in bioinformatics. 1 The Gene Ontology Consortium, “Gene Ontology: Tool for the Unification of Biology. Nature Genetics, 25 (2000), 25-29. See also: http://www.geneontology.org. 2 http://obo.sourceforge.net.

OAM: An Ontology Application Management Framework for Simplifying Ontology-Based Semantic Web Application Development

Abstract: Although the Semantic Web data standards are established, ontology-based applications built on the standards are relatively limited. This is partly due to high learning curve and efforts demanded in building ontology-based Semantic Web applications. In this paper, we describe an ontology application management (OAM) framework that aims to simplify creation and adoption of ontology-based application that is based on the Semantic Web technology. OAM introduces an intermediate layer between user application and programming and development environment in order to support ontology-based data publishing and access, abstraction and interoperability. The framework focuses on providing reusable and configurable data and application templates, which allow the users to create the applications without programming skill required. Three forms of templates are introduced: database to ontology mapping configuration, recommendation rule and application templates. We describe two case studies that adopted the framework: activity recognition in smart home domain and thalassemia clinical support system, and how the framework was used in simplifying development in both projects. In addition, we provide some performance evaluation results to show that, by limiting expressiveness of the rule language, a specialized form of recommendation processor can be developed for more efficient performance. Some advantages and limitations of the application framework in ontology-based applications are also discussed.