Reusable ontologies are becoming increasingly important for tasks such as information integration, knowledge-level interoperation, and knowledgebase development. We have developed a set of tools and services to support the process of achieving consensus on common shared ontologies by geographically distributed groups. These tools make use of the worldwide web to enable wide access and provide users with the ability to publish, browse, create, and edit ontologies stored on an ontology server. Users can quickly assemble a new ontology from a library of modules. We discuss how our system was constructed, how it exploits existing protocols and browsing tools, and our experience supporting hundreds of users. We describe applications using our tools to achieve consensus on ontologies and to integrate information. The Ontolingua Server may be accessed through the URL http://ontolingua.stanford.edu/

The Suggested Upper Merged Ontology (SUMO) is an upper level ontology that has been proposed as a starter document for The Standard Upper Ontology Working Group, an IEEE-sanctioned working group of collaborators from the fields of engineering, philosophy, and information science. The SUMO provides definitions for general-purpose terms and acts as a foundation for more specific domain ontologies. In this paper we outline the strategy used to create the current version of the SUMO, discuss some of the challenges that we faced in constructing the ontology, and describe in detail its most general concepts and the relations between them. Categories & Descriptors --- I.2.4 [Knowledge Representation Formalisms and Methods]: Artificial Intelligence -- representations (procedural and rule-based), semantic networks. General Terms --- Documentation, Languages, Standard-ization, Theory. Keywords --- Ontologies, Knowledge Interchange Format.

Ontology mapping is seen as a solution provider in today's landscape of ontology research. As the number of ontologies that are made publicly available and accessible on the Web increases steadily, so does the need for applications to use them. A single ontology is no longer enough to support the tasks envisaged by a distributed environment like the Semantic Web. Multiple ontologies need to be accessed from several applications. Mapping could provide a common layer from which several ontologies could be accessed and hence could exchange information in semantically sound manners. Developing such mappings has been the focus of a variety of works originating from diverse communities over a number of years. In this article we comprehensively review and present these works. We also provide insights on the pragmatics of ontology mapping and elaborate on a theoretical approach for defining ontology mapping.

Researchers in artificial intelligence first developed ontologies to facilitate knowledge sharing and reuse. Since the beginning of the 1990s, ontologies have become a popular research topic, and several AI research communities—including Ontologies play a major role in supporting information exchange across various networks. A prerequisite for such a role is the development of a joint standard for specifying and exchanging ontologies. The authors present OIL, a proposal for

An ontology is a set of definitions of content-specific knowledge representation primitives: classes, relations, functions, and object constants. Ontolingua is mechanism for writing ontologies in a canonical format, such that they can be easily translated into a variety of representation and reasoning systems. This allows one to maintain the ontology in a single, machine-readable form while using it in systems with different syntax and reasoning capabilities. The syntax and semantics are based on the KIF knowledge interchange format [11]. Ontolingua extends KIF with standard primitives for defining classes and relations, and organizing knowledge in object-centered hierarchies with inheritance. The Ontolingua software provides an architecture for translating from KIF-level sentences into forms that can be efficiently stored and reasoned about by target representation systems. Currently, there are translators into LOOM, Epikit, and Algernon, as well as a canonical form of KIF. This paper describes the asic approach of Ontologia to the ontology sharing problem, introduces the syntax, and describes the semantics of a few ontological commitments made in the software. Those commitments, that are reflected in the ontological syntax and the primitive vocabulary of the frame ontology, include: a distinction between definitional and nondefinitional assertions; the organization of knowledge with classes, instances, sets, and second-order relations; and assertions whose meaning depends on the contents of the knowledge base. Limitations of Ontologia's "conservative" approach to sharing ontologies and alternative approaches to the problem are discussed.

A common problem during the life cycle of knowledge-based systems is that symbolically represented knowledge needs to be translated into some different form. Translation needs occur along a variety of dimensions, such as KR language syntax and expressivity, modeling conventions, representation paradigms, etc. As a tool to support the translation problem, we present the OntoMorph system. OntoMorph provides a powerful rule language to represent complex syntactic transformations, and it is fully integrated with the PowerLoom KR system to allow transformations based on any mixture of syntactic and semantic criteria. We describe OntoMorph's successful application as an input translator for a critiquing system and as the core of a translation service for agent communication. We further motivate how OntoMorph can be used to support knowledge base merging tasks.

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More and more resources are becoming available on the Web, and there is a growing need for infrastructures that, based on advertised descriptions, are able to semantically match demands with supplies. We formalize general properties a matchmaker should have, then we present a matchmaking facilitator, compliant with desired properties. The system embeds a NeoClassic reasoner, whose structural subsumption algorithm has been modified to allow match categorization into potential and partial, and ranking of matches within categories. Experiments carried out show the good correspondence between users and system rankings.

Information integration is enabled by having a precisely defined common terminology. We call this combination of terminology and definitions an ontology. We have developed a set of tools and services to support the process of achieving consensus on such a common shared ontologies by geographically distributed groups. These tools make use of the world-wide web to enable wide access and provide users with the ability to publish, browse, create, and edit ontologies stored on an ontology server. Users can quickly assemble a new ontology from a library of modules. We discuss how our system was constructed, how it exploits existing protocols and browsing tools, and our experience supporting hundreds of users. We describe applications using our tools to achieve consensus on ontologies and to integrate information.

Exploiting the full potential of the World Wide Web will require semantic as well as syntactic interoperability. This can best be achieved by providing a further representation and inference layer that builds on existing and proposed web standards. The OIL language extends the RDF schema standard to provide just such a layer. It combines the most attractive features of frame based languages with the expressive power, formal rigour and reasoning services of a very expressive description logic. 1