In the last years, ontologies have played a major role for building large, distributed, and heterogeneous intelligent systems. E.g., ontologies are one key technique of the semantic web layer. The development process of an ontology heavily depends on its evaluation. In this paper, we introduce several measures for the evaluation of ontological knowledge. Besides standard methods like taxonomic errors we also present novel metrics focusing on design anomalies. For the implementation of these measures we propose a declarative approach using the logic-based language FNQuery.

Summary. In this chapter we present a methodology for introducing and maintaining ontology based knowledge management applications into enterprises with a focus on Knowledge Processes and Knowledge Meta Processes. While the former process circles around the usage of ontologies, the latter process guides their initial set up. We illustrate our methodology by an example from a case study on skills management. The methodology serves as a scaffold for Part B “Ontology Engineering” of the handbook. It shows where more specific concerns of ontology engineering find their place and how they are related in the overall process. 1

Ontology evaluation is a maturing discipline with methodologies and measures being developed and proposed. However, evaluation methods that have been proposed have not been applied to specific examples. In this paper, we present the state-of-the-art in ontology evaluation- current methodologies, criteria and measures, analyse appropriate evaluations that are important to our application- browsing in Wikipedia, and apply these evaluations in the context of ontologies with varied properties. Specifically, we seek to evaluate ontologies based on categories found in Wikipedia. Categories and Subject Descriptors

We explore the use of ontological constraints in a new way: deploying them in a software system's formal evaluation. We present a formalism for ontological constraints and elaborate on a meta interpretation technique in the field of ontologies.

Although ontology reuse is an important research issue only one of its subprocesses (merge) is fairly well understood. The time has come to change the current state of affairs with the other reuse subprocess: integration. In this paper we characterize the ontology integration process, we identify the activities that should be performed in this process and describe a methodology to perform the ontology integration process.

Experienceware is a paradigm which emerged in the late eighties and evolved during the nineties, resulting in technologies such as experience factories and their constituent experience bases. These are designed to manage experiences collected throughout the life-cycle of a software project. Ontologies emerged round about the same time as a way to represent consensual knowledge about a domain of interest in reusable and sharable formats. Despite their diverse origins and ways of development, there is an overlap of scope regarding one of their goals: to support reuse. In this paper we make use of this overlap by applying the experience factories paradigm to ontology deployment and in particular, to support ontology verification. 1. Motivation In knowledge engineering, the study of ontologies is an attempt to prescribe appropriate, restricted formal languages for describing a target problem or domain. The idea is that by charting these in advance we make it easier for others to begin de...

In this paper we explore the need to understand the human-behavioral factors within an organization's information security management processes. We frame this investigation around development of an information security ontology. This ontology is intended for use within organizations that aim not only to maintain compliance with external standards, but also to consider and adjust the attitude towards security as exhibited by those within the organization. We provide an ontology that combines information security standards (in this case ISO27002) and representation of the human-behavioral implications of information security management decisions. Our ontology explicitly represents the human-behavioral concerns attached to specific security processes and policy decisions. As such it encourages consideration of the security behavior of individuals towards technical security controls. We demonstrate use of our ontology with an applied example concerning management of an organization's password policy. This example illustrates how password configuration may be perceived by individuals within the organization, and how this perception alters their behavior and consequently the attitude to information security in the workplace.

The contributions of this thesis bridge two disciplines: environmental science (specifically, wastewater management) and computer science (specifically, artificial intelligence). Wastewater management as a discipline operates using a range of different approaches and methods which include: manual control, on-line automatic control, numerical or non-numerical models, statistical models and simulation models. The thesis characterizes an interdisciplinary research on artificial intelligence techniques (rule-based reasoning, case-based reasoning, ontologies and planning) applied to environmental decision-support systems. The integrated architecture's design of this application, the OntoWEDSS system, augments classic reasoning systems (rule-based reasoning and case-based reasoning) with a domain ontology about the management of wastewater treatment plants. The integration of the newly created WaWO ontology provides a more flexible management capability to OntoWEDSS. The construction of the OntoWEDSS decision support system is based on a specific case study but the system is also of general interest, given that its ontologyunderpinned architecture can be applied to any wastewater treatment plant and, at an appropriate level of abstraction, to other environmental domains. The OntoWEDSS system improves the diagnosis of the state of a treatment plant, provides support for wastewater-related complex problem-solving, and facilitates knowledge modelling and reuse by means of the WaWO ontology.

This document is part of a research project partially funded by the IST Programme of the Commission of the European Communities as project number IST-1999-10132. The partners in this project are: Vrije Universiteit Amsterdam VUA (coordinator, NL), University of Karlsruhe (Germany), Schweizerische Lebensversicherungs- und Rentenanstalt/Swiss Life (Switzerland), British Telecommunications plc (UK), CognIT a.s. (Norway), EnerSearch AB (Sweden), AIdministrator Nederland BV (NL)

Ontologies have become popular in the Articial Intelligence community as a way to standardise representation of domain knowledge. Despite their advocated use in areas such as knowledge sharing and reuse there is little discussion in the community regarding their application in other areas. In this paper we explore the use of ontologies in improving systems engineering reliability by consistency checking with respect to ontological axioms - making it possible to reason about the correctness of an application with respect to ontological constraints. We applied this approach to diverse areas, each of which demonstrates a dierent use: deploying ontological axioms in business process modelling and enriching the axiomatisation of an Air Campaign Planning(ACP)-based application; identication of ontological constraints in ecological modelling; and evaluation of ontologies on system dynamics theory at the application level. 1.