This paper is intended to serve as a comprehensive introduction to the emerging eld concerned with the design and use of ontologies. We observe that disparate backgrounds, languages, tools, and techniques are a major barrier to e ective communication among people, organisations, and/or software systems. We showhowthe development and implementation of an explicit account of a shared understanding (i.e. an `ontology') in a given subject area, can improve such communication, which in turn, can give rise to greater reuse and sharing, inter-operability, and more reliable software. After motivating their need, we clarify just what ontologies are and what purposes they serve. We outline a methodology for developing and evaluating ontologies, rst discussing informal techniques, concerning such issues as scoping, handling ambiguity, reaching agreement and producing de nitions. We then consider the bene ts of and describe, a more formal approach. We re-visit the scoping phase, and discuss the role of formal languages and techniques in the speci cation, implementation and evaluation of ontologies. Finally, we review the state of the art and practice in this emerging eld,

This is a comprehensive description of the Enterprise Ontology, a collection of terms and definitions relevant to business enterprises. We state its intended purposes, describe how we went about building it, define all the terms and describe our experiences in converting these into formal definitions. We then describe how we used the Enterprise Ontology and give an evaluation which compares the actual uses with original purposes. We conclude by summarising what we have learned. The Enterprise Ontology was developed within the Enterprise Project, a collaborative e#ort to provide a framework for enterprise modelling. The Ontology was built to serve as a basis for this framework which includes methods and a computer tool set for enterprise modelling. We give an overview of the Enterprise Project, elaborate on the intended use of the Ontology, and give a brief overview of the process we went through to build it. The scope of the Enterprise Ontology covers those core concepts req...

The word integration has been used with different meanings in the ontology field. This article aims at clarifying the meaning of the word "integration" and presenting some of the relevant work done in integration. We identify three meanings of ontology "integration": when building a new ontology reusing (by assembling, extending, specializing or adapting) other ontologies already available; when building an ontology by merging several ontologies into a single one that unifies all of them; when building an application using one or more ontologies. We discuss the different meanings of "integration", identify the main characteristics of the three different processes and propose three words to distinguish among those meanings: integration, merge and use.

We present a method and a tool, OntoLearn, aimed at the extraction of domain ontologies from web sites, and more generally from documents shared among the members of virtual organizations. OntoLearn first extracts a domain terminology from available documents. Then, complex domain terms are semantically interpreted and arranged in a hierarchical fashion. Finally, a general purpose ontology, i.e. WordNet, is trimmed and enriched with the detected domain concepts. The major novel aspect of this approach is semantic interpretation, that is, the association of a complex concept with a complex term. This involves finding the appropriate WordNet concept for each word of a terminological string and the appropriate conceptual relations that hold among the concept components. Semantic interpretation is based on a new WSD algorithm, called structural semantic interconnections.

The use and importance of ontologies is becoming more widespread, however building ontologies is largely a black art. The aim of this paper is to identify and characterise what we currently know and to move towards the longer term goal of developing a comprehensive unified methodology. We first identify dimensions for characterising ontologies, to be used as a basis for noting which techniques and guidelines for building ontologies apply in different circumstances. We then give an overview of the current state of the art, noting that most work addresses just a small part of the life cycle. The very few more complete methods are limited to case studies involving single ontologies and they are hard to compare. In the main part of this paper, we examine two such methods and give a framework for comparing and unifying them. We emphasise that different approaches are required for difference circumstances, and give some guidelines for when to use which techniques. We conclude by ...

The European GALEN project is developing terminology services based on a large, re-usable medical ontology. The ontology is being built using GRAIL, a description logic with transitivity and general concept inclusions.

s. The Plinius ontology was developed to support the translation of natural-language sentences into expressions in a knowledge representation language [31]. Those design decisions taken during the development of the ontology which appeared to be domain-independent have been proposed as general ontology development principles. These are: (1) conflicting assertions about the same entity can be more readily discovered if the concepts are defined as fully as possible. (2) pre-existing formal theories are taken as given and a domain ontology does not specify the semantics of logical constants. (3) an ontology should be independent of any particular knowledge representation language. (4) the principle of the conceptual construction kit states that an ontology consists of primitives concepts and construction rules that allow the definition of all other concepts in terms of these primitives. (5) a bottom-up approach is taken in order that the ontology exhibits sufficient completeness for the...

Abstract- Though the utility of domain Ontologies is now widely acknowledged in an increasing number of domains, several barriers must be overcome before Ontologies become practical and useful tools. A critical issue is the task of identifying, defining, and entering the concept definitions. In case of large and complex application domains this task can be lengthy, costly, and controversial (since different persons may have different points of view about the same concept). To reduce time, cost (and, sometimes, harsh discussions) it is highly advisable to refer, in constructing or updating an ontology, to the documents available in the field. In this paper we describe OntoLearn, a text-mining tool devised to improve human productivity during the process of ontology construction. 1.

Abstract. Collaborative knowledge base (KB) authoring environments are critical for the construction of high-performance KBs. Such environments must support rapid construction of KBs by a collaborative e ort of teams of knowledge engineers through reuse of existing knowledge and software components. They should support the manipulation of knowledge by diverse problem-solving engines even if that knowledge is encoded in di erent languages and by di erent researchers. They should support large KBs and provide a scalable and interoperable development infrastructure. In this paper, we present anenvironment that satis es many of these goals. We present an architecture for scalable frame representation systems (FRSs). The Generic Frame Protocol (GFP) provides infrastructure for reuse of software components. It is a procedural interface to frame representation systems that provides a common means of accessing and modifying frame KBs. The Generic KB Editor (Gkb-Editor) provides graphical KB browsing, editing, and comprehension services for large KBs. Scalability of loading and saving time is provided by a storage system (PERK) which submerges a database management system in an FRS. Multi-user access is controlled through a collaboration subsystem that uses a novel optimistic concurrency control algorithm. All the results have been implemented and tested in the development of several real KBs.

Collaborative ontology building requires both knowledge integration and knowledge reconciliation. Wiki@nt is an ontology building environment that supports collaborative ontology development. Wiki@nt is based on an extension to with (partial order on axioms) and (localized axioms in package ) constructors. Wiki@nt supports integration and reconciliation of multiple independently developed, semantically heterogeneous, and very likely inconsistent ontology modules. A web browser based editor interface is provided, with features to support team work, version control, page locking, and navigation.