To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse — definitions of classes, relations, functions, and other objects — is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems. Definitions written in a standard format for predicate calculus are translated by a system called Ontolingua into specialized representations, including frame-based systems as well as relational languages. This allows researchers to share and reuse ontologies, while retaining the computational benefits of specialized implementations. We discuss how the translation approach to portability addresses several technical problems. One problem is how to accommodate the stylistic and organizational differences among representations while preserving declarative content. Another is how to translate from a very expressive language into restricted languages, remaining system-independent while preserving the computational efficiency of implemented systems. We describe how these problems are addressed by basing Ontolingua itself on an ontology of domain-independent, representational idioms.

Recent work in Artificial Intelligence is exploring the use of formal ontologies as a way of specifying content-specific agreements for the sharing and reuse of knowledge among software entities. We take an engineering perspective on the development of such ontologies. Formal ontologies are viewed as designed artifacts, formulated for specific purposes and evaluated against objective design criteria. We describe the role of ontologies in supporting knowledge sharing activities, and then present a set of criteria to guide the development of ontologies for these purposes. We show how these criteria are applied in case studies from the design of ontologies for engineering mathematics and bibliographic data. Selected design decisions are discussed, and alternative representation choices and evaluated against the design criteria.

Factors such as the massive increase in information available via electronic networks and the advent of virtual distributed workgroups for commerce are placing severe burdens on traditional methods of information sharing and retrieval. Matchmaking proposes an intelligent facilitation agent that accepts machinereadable requests and advertisements from information consumers and providers, and determines potential information sharing paths. We argue that matchmaking permits large numbers of dynamic consumers and providers, operating on rapidly-changing data, to share information more effectively than via current methods. This paper introduces matchmaking, as enabled by knowledge sharing standards like KQML, and describes the SHADE and COINS matchmaker implementations. The utility and initial results of matchmaking are illustrated via example scenarios in engineering and consumer information retrieval. 1

Information gathering agents are required in many software agent applications to answer queries, posed by other agents, using a variety of available information sources. We formally consider the problem of designing information gathering agents, and make two important contributions. First, we examine the key issue of integrating knowledge from external sites into our knowledge base, and present an expressive language for this purpose. A noteworthy feature of our language is its ability to capture the knowledge that some external sites have complete information of a certain kind, using rich semantic constraints. Given a query on the knowledge base, it is important for the agent to first determine the set of external sites that contain information relevant to answering the query, and then access those sites. Our second contribution is to show that, given a query and the descriptions of the external sites in our language, it is possible to determine minimal subsets of sites that are neede...

The design of products by multi-disciplinary groups is a knowledge intensive activity. Collaborators must be able to exchange information and share some common understanding of the information's content. The hope, however, that a centralized standards effort will lead to integrated tools spanning the needs of engineering collaborators is misplaced. Standards cannot satisfy the information sharing needs of collaborators, because these needs cannot be standardized. This paper discusses the design and use of a shared representation of knowledge (language and vocabulary) to facilitate communication among specialists and their tools. The paper advances the opinion that collaborators need the ability to establish and customize knowledge sharing agreements (i.e. mutually agreed upon terminology and definitions) that are usable by people and their machines. The paper describes a formal approach to representing engineering knowledge, describes its role in a computational framework that integra...

The massive increase in information available via electronic networks is placing severe burdens on traditional methods of information sharing and retrieval. Matchmaking proposes an intelligent facilitation agent that accepts machine-readable requests and advertisements from information consumers and providers, and determines potential information sharing paths. Matchmaking permits large numbers of dynamic consumers and providers, operating on rapidly-changing data, to locate and share information effectively. This paper introduces matchmaking, as enabled by knowledge sharing standards like KQML, and gives a brief description of the the SHADE and COINS matchmakers. In addition, several applications are described to illustrate the utility of matchmaking for information retrieval. Introduction There has been a phenomenal explosion of information on electronic bitways such as corporate networks, the Internet, personal computer networks, and even television cable networks. This has led not...

Irrelevance reasoning refers to the process in which a system reasons about which parts of its knowledge are relevant (or irrelevant) to a specific query. Aside from its importance in speeding up inferences from large knowledge bases, relevance reasoning is crucial in advanced applications such as modeling complex physical devices and information gathering in distributed heterogeneous systems. This article presents a novel framework for studying the various kinds of irrelevance that arise in inference and efficient algorithms for relevance reasoning. We present a

This paper describes an initial version of a library of sharable and reusable medical ontological theories, organized according to a proposed classification of ontologies. 1 1 What is an ontology? The term ontology arises from the philosophical tradition, within which it's typically polysemous [Poli, 1993]; that is, it presents multiple meanings. However, ontology can be generally defined as the doctrine of being or the science of objects (`real' objects as well as abstract, mental or ideal objects). While classical ontology is the result of "the intuitive study of the fundamental properties, modes, and aspects of being, or of entities in general", formal ontology is "the result of combining the intuitive, informal method of classical ontology with the formal, mathematical method of modern symbolic logic" [Burkhardt & Smith, eds., 1991]. There are analogies between the outlined philosophical notion of ontology and the knowledge engineering notion of conceptualization, as defined e.g...

This paper presents an approach to the development of concurrent engineering software applications based on a knowledge sharing technology. In this approach, individual programmers write their programs in the form of separate modules called Software Agents, which interoperate with their peers using an expressive communication standard called Agent Communication Language. The runtime activities of the individual software agents are coordinated by task-independent programs called Facilitators. Facilitators perform a wide variety of tasks, including the automated selection of agents to accomplish subtasks, the mediation of terminology, the buffering of partial knowledge in communication between agents, and the management of communication with other facilitators on other machines. Once set in operation, software agents interoperate to accomplish the overall task in a heterogeneous distributed architecture called Federation. The paper discusses the major aspects of this approach and briefly...

s and protocols, they also represented information in idiosyncratic ways. Another problem was the achievement of automated concurrent engineering -- the exchange of incomplete design information and the timely propagation of design constraints. Note that whereas the phrase "concurrent engineering" usually applies to human work, here we are discussing concurrent engineering among programs. Automated Concurrent Engineering in Designworld December 21, 1996 2 3.0 Agent-based framework These requirements led to the development of a novel software interoperability framework [2], termed "agent-based", that addresses many important issues critical to effective concurrent engineering. The idea in this approach is for programmers to write their programs as individual software agents. Communication is assured through the use of a standard agent communication language. Agent interaction is assisted through the services of