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.

A Pattern-Based Method for Re-Engineering Non-Ontological Resources into Ontologies

Abstract: To speed up the ontology development process, ontology developers are reusing all available ontological and non-ontological resources, such as classification schemes, thesauri, lexicons, and so forth, that have already reached some consensus. Non-ontological resources are highly heterogeneous in their data model and storage system or implementation. The reuse of these non-ontological resources involves their re-engineering into ontologies. This paper presents a method for re-engineering non-ontological resources into ontologies. The method is based on so-called re-engineering patterns, which define a procedure that transforms the non-ontological resource components into ontology representational primitives using WordNet for making explicit the relations among the non-ontological resource terms. The paper also provides the description of NOR2O, a software library that implements the transformations suggested by the patterns. Finally, it depicts an evaluation of the method, patterns, and software library proposed.

Semantic EPC: Enhancing Process Modeling Using Ontology Languages

Abstract: In this article we describe a semantic extension of event-driven proc- ess chains, with which it is possible to specify the semantics of individual model elements as it is indicated by their label in natural language using con- cepts of a formal ontology. To do so, a multi-level approach was developed, which comprises an ontology level, a metadata level, as well as a model level. With the approach presented here, ambiguity that is introduced by the use of natural language in semi-formal models can be removed. Moreover, new possi- bilities of reasoning over business process models are introduced which im- prove the analysis, search and validation of business processes. 1

A top-level ontology of functions and its application in the Open Biomedical Ontologies

Abstract: Motivation: A clear understanding of functions in biology is a key component in accurate modelling of molecular, cellular and organismal biology. Using the existing biomedical ontologies it has been impossible to capture the complexity of the community's knowledge about biological functions. Results: We present here a top-level ontological framework for representing knowledge about biological functions. This framework lends greater accuracy, power and expressiveness to biomedical ontologies by providing a means to capture existing functional knowledge in a more formal manner. An initial major application of the ontology of functions is the provision of a principled way in which to curate functional knowledge and annotations in biomedical ontologies. Further potential applications include the facilitation of ontology interoperability and automated reasoning. A major advantage of the proposed implementation is that it is an extension to existing biomedical ontologies, and can be applied without substantial changes to these domain ontologies. Availability: The Ontology of Functions (OF) can be downloaded in OWL format from. Additionally, a UML profile and supplementary information and guides for using the OF can be accessed from the same website. Contact: bioonto@lists.informatik.uni-leipzig.de

Ontology (network) evaluation

Abstract: Ontology evaluation refers to the activity of checking the technical quality of an ontology against a frame of reference. As such, it is of core importance for ontology engineering supporting scenarios such as ontology validation, knowledge selection, or the evaluation of knowledge extraction algorithms. In this chapter, we provide methodological guidelines for evaluating stand-alone ontologies as well as ontology networks. Our goal is not only to present the NeOn perspective on this issue but to also provide a practical outlook to the vast area of work in the area of ontology evaluation. Without performing an extensive state-of-the-art analysis of this research field, we aim to illustrate how various evaluation methods developed by the NeOn project, and not only, can be used at different stages of the evaluation process. We conclude the chapter with some concrete examples of performing ontology evaluation.

Domain Ontology for Construction Knowledge

Abstract: An ontology is a claim on/for knowledge that attempts to model what is known about a domain of discourse. A domain ontology does not aim to exhaustively list all concepts in a domain, but rather to build an abstract (yet extendable) philosophical (yet practical) conceptualization of the essence of knowledge in a domain. At the core of any ontology is an ontological model—an architecture of how the world (in a domain) behaves (or becomes). The ontology categorizes construction knowledge across three main dimensions: concept, modality, and context. Concept encompasses five key terms: entity (further subdivided into generic and secondary), environmental element, abstract concept, attribute, and system (combinations of the previous four types). Modality is a means for generating a variety of types for each of the described concepts. Context allows for linking concepts in a variety of ways—creating different worlds.