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The State of the Art in Ontology Design: A Survey and Comparative Review

AI Magazine

We have selected 10 specific projects for this study, including general ontologies, domain-specific ones, and one knowledge representation system. The comparison framework includes general characteristics, such as the purpose of an ontology, its coverage (general or domain specific), its size, and the formalism used. Characteristics that describe the content of an ontology include taxonomic organization, types of concept covered, top-level divisions, internal structure of concepts, representation of part-whole relations, and the presence and nature of additional axioms. By identifying the similarities and differences among existing ontologies, we clarify the range of alternatives in creating a standard framework for ontology design.


The State of the Art in Ontology Design

AI Magazine

In this article, we develop a framework for comparing ontologies and place a number of the more prominent ontologies into it. We have selected 10 specific projects for this study, including general ontologies, domain-specific ones, and one knowledge representation system. The comparison framework includes general characteristics, such as the purpose of an ontology, its coverage (general or domain specific), its size, and the formalism used. It also includes the design process used in creating an ontology and the methods used to evaluate it. Characteristics that describe the content of an ontology include taxonomic organization, types of concept covered, top-level divisions, internal structure of concepts, representation of part-whole relations, and the presence and nature of additional axioms.


The State of the Art in Ontology Design: A Survey and Comparative Review

AI Magazine

In this article, we develop a framework for comparing ontologies and place a number of the more prominent ontologies into it. We have selected 10 specific projects for this study, including general ontologies, domain-specific ones, and one knowledge representation system. The comparison framework includes general characteristics, such as the purpose of an ontology, its coverage (general or domain specific), its size, and the formalism used. It also includes the design process used in creating an ontology and the methods used to evaluate it. Characteristics that describe the content of an ontology include taxonomic organization, types of concept covered, top-level divisions, internal structure of concepts, representation of part-whole relations, and the presence and nature of additional axioms. Finally, we consider what experiments or applications have used the ontologies. Knowledge sharing and reuse will require a common framework to support interoperability of independently created ontologies. Our study shows there is great diversity in the way ontologies are designed and the way they represent the world. By identifying the similarities and differences among existing ontologies, we clarify the range of alternatives in creating a standard framework for ontology design.


The State of the Art in Ontology Design: A Comparative Review

AAAI Conferences

Recent work in ontology design has produced a range of different projects from ontologies that represent general world knowledge, to domain-specific ones, to knowledge representation systems which embody ontological frameworks. There is an agreement in the ontology engineering community that it would be very beneficial to be able to integrate ontologies so that they can share and reuse each other's knowledge. If one ontology, for example, has a very well developed theory of time, another ontology (say, the one representing biology experiments) could then use that without having to reinvent the time microtheory. There is also an understanding that achieving interoperability of ontologies is a very challenging task. For smooth integration to be (at least partially) possible, the first thing to do is to look at the ontology projects that already exist and are fairly well developed and consider what are the differences and similarities in the way they treat some basic knowledge representation aspects.


Toward t Distributed Use of Large-Scale Ontologies

AAAI Conferences

Large scale knowledge bases systems are difficult and expensive to construct. If we could share knowledge across systems, costs would be reduced. However, because knowledge bases are typically constructed from scratch, each with their own idiosyncratic structure, sharing is difficult. Recent research has focused on the use of ontologies to promote sharing. An ontology is a hierarchically structured set of terms for describing a domain that can be used as a skeletal foundation for a knowledge base. If two knowledge bases are built on a common ontology, knowledge can be more readily shared, since they share a common underlying structure. This paper outlines a set of desiderata for ontologies, and then describes how we have used a large-scale (50,000 concept) ontology develop a specialized, domain-specific ontology semiautomatically. We then discuss the relation between ontologies and the process of developing a system, arguing that to be useful, an ontology needs to be created as a "living document", whose development is tightly integrated with the system's. We conclude with a discussion of Web-based ontology tools we are developing to support this approach. Introduction Current knowledge bases are difficult to share or reuse, even when they are expressed in the same formalism and cover the same domain. In our view, this problem stems from the lack of a shared terminology and structure for the knowledge bases. In building a knowledge base, there are many intermediate concepts that a system builder must create and organize to get from specific domain level terms and the very high level concepts that a knowledge representation system provides by default (like "THING").