A Survey and Comparative Review
* 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 major goal of this article is to develop a framework for comparing various projects in ontology design and put a number of prominent ontologies in this framework.
According to Webster's dictionary (Woolf 1981), ontology is a particular theory about the nature of being or the kinds of existent. The task of intelligent systems in computer science is to formally represent these existents. A body of formally represented knowledge is based on conceptualization. Conceptualization consists of a set of objects, concepts, and other entities about which knowledge is being expressed and of relationships that hold among them. Every knowledge model is committed to some conceptualization, implicitly or explicitly. An explicit specification of this conceptualization is called an ontology (Gruber 1993). Formally, an ontology consists of terms, their definitions, and axioms relating them (Gruber 1993); terms are normally organized in a taxonomy.
Most of the researchers in the area of ontology design agree that the current important goals of ontology research are to (1) make ontologies sharable by developing common formalisms and tools; (2) develop the content of ontologies (ontology design); and (3) compare, gather, translate, and compose different ontologies. Recent work in ontology design has produced a range of different projects, from ontologies that represent general world knowledge to domain-specific ontologies to knowledge representation systems that embody ontological frameworks. There is an agreement in the ontology engineering community that it would be 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 well-developed theory of time, another ontology (say, the one representing biology experiments) could then use this theory without having to reinvent it. There is also an understanding that achieving the interoperability of ontologies is a 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 the differences and similarities in the way they treat some basic knowledge representation aspects. With this understanding, we can see where there is some common base and what the obstacles are to the integration of different ontologies.
Identifying a framework for comparing ontologies and placing a number of the more prominent existing projects in this framework is the objective of the study presented here. After giving a brief introduction to a number of ontology projects, we compare them with respect to what they were created for; what the design process was; and how they treat certain fundamental issues in representing knowledge, such as taxonomies, properties, and relations. …