This paper is intended to serve as a comprehensive i n troduction 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 c o mmunication among people, organisations, and/or software systems. We s h o w h o w t h e development and implementation of an explicit account of a shared understanding (i.e. an`ontology') in a given subject area, can improve s u c h 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, w e review the state of the art and practice in this emerging eld, considering various case studies, software tools for ontology development, key research issues and future prospects.

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 effort 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 required for the project, which will appeal to a wider audience. We present natural language definitions for all the terms, starting with the foundational concepts (e.g. entity, relationship, actor). These are used to define the main body of terms, which are divided into the following subject areas: activities, organisation, strategy and marketing. We review some of the things learned during the formalisation process of converting the natural language definitions into Ontolingua. We identify and propose solutions for what may be general problems occurring in the development of a wide range of ontologies in other domains. We then characterise in general terms the sorts of issues that will be faced when converting an informal ontology into a formal one. Finally, we describe our experiences in using the Enterprise Ontology. We compare these with the intended uses, noting our successes and failures. We conclude with an overall evaluation and summary of what we have learned.

The goal of having networks of seamlessly connected people, software agents and IT systems remains elusive. Early integration efforts focused on connectivity at the physical and syntactic layers. Great strides were made; there are many commercial tools available, for example to assist with enterprise application integration. It is now recognized that physical and syntactic connectivity is not adequate. A variety of research systems have been developed addressing some of the semantic issues. In this paper, we argue that ontologies in particular and semantics-based technologies in general will play a key role in achieving seamless connectivity. We give a detailed introduction to ontologies, summarize the current state of the art for applying ontologies to achieve semantic connectivity and highlight some key challenges.

We address the problem of highly varied and inconsistent usage of terms by the knowledge technology community in the area of knowledge-level modelling. It is arguably difficult or impossible for any standard set of terms and definitions to be agreed on. However, de facto standard usage is already emerging within and across certain segments of the community. This is very difficult to see, however, especially for newcomers to the field. It is the goal of this paper to identify and reflect the most common usage of terms as currently found in the literature. To this end, we introduce and define the concept of a knowledge level model, comparing how the term is used today with Newell's original usage. We distinguish two major types of knowledge level model: ontologies and problem solving models. We describe what an ontology is, what they may be used for and how they are represented. We distinguish various kinds of ontologies and define a number of additional related concepts. We describe what is meant by a problem solving model, what they are used for, and attempt to clarify some terminological confusion that exists in the literature. We define what is meant by the term ‘problem’, and some common notions used to characterise and represent problems. We introduce and describe the ideas of tasks, problem solving methods and a variety of other important related concepts.