Interest in the nature, development and use of ontologies is becoming increasingly widespread. Since the early nineties, numerous workshops have been held. Representatives from historically separate disciplines concerned with philosophical issues, knowledge acquisition and representation, planning, process management, database schema integration, natural language processing and enterprise modelling, came together to identify a common core of issues of interest. There was highly varied and inconsistent usage of a wide variety of terms, most notably, “ontology”, rendering cross-discipline communication difficult. However, progress was made toward understanding the commonality among the disciplines. Subsequent workshops addressed various aspects of the field, including theoretical issues, methodologies for building ontologies, as well as specific applications in government and industry.

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.

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.

This document provides the specification of the Process Interchange Format (PIF) version 1.2. The goal of this work is to develop an interchange format to help automatically exchange process descriptions among a wide variety of business process modelling and support systems such as workflow software, flow charting tools, planners, process simulation systems and process repositories. Instead of having to write ad hoc translators for each pair of such systems each system will only need to have a single translator for converting process descriptions in that system into and out of the common PIF format. Then any system will be able to automatically exchange basic process descriptions with any other system. This document describes the PIF-CORE 1.2, i.e. the core set of object types (such as activities, agents and prerequisite relations) that can be used to describe the basic elements of any process. The document also describes a framework for extending the core set of object types to include additional information needed in specific applications. These extended descriptions are exchanged in such a way that the common elements are interpretable by any PIF translator, and the additional elements are interpretable by any translator that knows about the extensions. The PIF format was developed by a working group including representatives from several universities and companies, and has been used for experimental automatic translations among systems developed independently at three of these sites. This document is being distributed in the hopes that other groups will comment upon the interchange format proposed here, and that this format (or future versions of it) may be useful to other groups as well. The PIF Document 1.0 was released in December 1994, and the current document reports the revised PIF that incorporate the feedback received since then.

The Defense Advanced Research Projects Agency (DARPA) and US Air Force Research Laboratory Planning Initiative (ARPI) has initiated a project to draw on the range of previous work in planning and activity ontologies to create a practically useful Shared Planning and Activity Representation (SPAR) for use in technology and applications projects within their communities. This article describes the previous work which has been used to create the initial SPAR representation. Key examples of the work drawn upon are published in this issue. The paper provides a comprehensive bibliography and related world wide web resources for work in the area of plan, process and activity representation. SPAR is now being subjected to refinement during several review cycles by a number of expert and user panels.