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9.2.2. Methodology
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An ontology engineering methodology needs to consider the following three types of activities:  Ontology management activities.  Ontology development activities.  Ontology support activities. Ontology Management Activities Procedures for ontology management activities must include de nitions for the scheduling of the ontology engineering task. Further it is necessary to de ne control mechanism and quality assurance steps. Ontology Development Activities When developing the ontology it is important that procedures are de ned for environment and feasibility studies. After the decision to build an ontology the ontology engineer needs procedures to specify, conceptualize, formalize, and implement the ontology. Finally, the users and engineers need guidance for the maintenance, population, use, and evolution of the ontology. Ontology Support Activities To aid the development of an ontology, a number of important supporting activities should be undertaken. These include knowledge acquisition, evaluation, integration, merging and alignment, and con guration management. These activities are performed in all steps of the development and management process. Knowledge acquisition can happen in a centralized as well as a decentralized way. Ontology
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learning is a way to support the manual knowledge acquisition with machine learning techniques.
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9.2.3. Documentation
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It is important to document the results after each activity. In a later stage of the development process this helps to trace why certain modeling decisions have been undertaken. The documentation of the results can be facilitated with appropriate tool support. Depending on the methodology the documentation level can be quite different. One methodology might require documenting only the results of the ontology engineering process while others give the decision process itself quite some importance.
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9.2.4. Evaluation
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In the ontology engineering setting, evaluation measures should provide means to measure the quality of the created ontology. This is particular dif cult for ontologies, since modeling decisions are in most cases subjective. A general survey of evaluation measures for ontologies can be found in Gomez-Perez (2004). Additionally we want to refer to the evaluation measures which can be derived from statistical data (Tempich and Volz, 2003) and measures which are derived from philosophical principles. One of the existing approaches for ontology evaluation is OntoClean (Guarino and Welty, 2002).
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In the following we summarize the distinctive features of the available ontology engineering methodologies and give quick pointers to existing tool support speci cally targeted to the methodologies. Next, we brie y introduce the most prominent existing tools.
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9.3.1. Methodologies
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An extensive state-of-the-art overview of methodologies for ontology engineering can be found in Gomez-Perez et al. (2003). More recently Cristani and Cuel (2005) proposed a framework to compare ontology engineering methodologies and evaluated the established ones accordingly. In the OntoWeb2 project, the members gathered guidelines and best practices for industry (Leger et al., 2002a, b) with a focus on
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applications for E-Commerce, Information Retrieval, Portals and Web Communities. A very practical oriented description to start building ontologies can be found in Noy and McGuinness (2001). In our context, the following approaches are especially noteworthy. Where it is adequate we give pointers to tools mentioned in the next section, whenever tool support is available for a methodology. CommonKADS (Schreiber et al., 1999) is not per se a methodology for ontology development. It covers aspects from corporate knowledge management, through knowledge analysis and engineering, to the design and implementation of knowledge-intensive information systems. CommonKADS has a focus on the initial phases for developing knowledge management applications. CommonKADS is therefore used in the OTK methodology for the early feasibility stage. For example, a number of worksheets can be used to guide a way through the process of nding potential users and scenarios for successful implementation of knowledge management. CommonKADS is supported by PC PACK, a knowledge elicitation tool set, that provides support for the use of elicitation techniques such as interviewing, that is it supports the collaboration of knowledge engineers and domain experts. DOGMA (Jarrar and Meersman, 2002; Spyns et al., 2002) is a databaseinspired approach and relies on the explicit decomposition of ontological resources into ontology bases in the form of simple binary facts called lexons and into so-called ontological commitments in the form of description rules and constraints. The modeling approach is implemented in the DOGMA Server and accompanying tools such as the DOGMA Modeler tool set. The Enterprise Ontology (Uschod and King, 1995; Uschold et al., 1998) proposed three main steps to engineer ontologies: (i) to identify the purpose, (ii) to capture the concepts and relationships between these concepts, and the terms used to refer to these concepts and relationships, and (iii) to codify the ontology. In fact, the principles behind this methodology in uenced much work in the ontology community. Explicit tool support is given by the Ontolingua Server, but actually these principles heavily in uenced the design of most of today s more advanced ontology editors. The KACTUS (Bernaras et al., 1996) approach requires an existing knowledge base for the ontology development. The ontology is build based on the existing knowledge model, applying a bottom-up strategy. There is no speci c tool support for this methodology. METHONTOLOGY (Fernandez-Lopez et al., 1999) is a methodology for building ontologies either from scratch, reusing other ontologies as they are, or by a process of re-engineering them. The framework enables the construction of ontologies at the knowledge level, that is the conceptual level, as opposed to the implementation level. The framework consists of: identi cation of the ontology development process containing the main activities (evaluation, con guration, management, conceptualization,
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