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It has been a widespread conviction in knowledge engineering that methodologies for building knowledge-based systems help knowledge engineering projects to successfully reach their goals in time (cf. Schreiber et al., 1999 for one of the most widely deployed methodologies). With the arrival of ontologies in knowledge-based systems the same kind of methodological achievement for structuring the ontology-engineering process has been pursued by approaches like the ones presented in the next section. In this section, we will look at the general criteria for and speci c properties of methodologies for the ontology life cycle. We will rst apply a de nition of methodology to our eld of interest, and then point out to the conclusions drawn from this de nition.

Binomial distribution, n = 5,

p = 03

The IEEE de nes a methodology as a comprehensive, integrated series of techniques or methods creating a general systems theory of how a class of thought-intensive work ought be performed (IEEE, 1990). A methodology should de ne an objective (ideally quanti ed) set of

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Binomial distribution, n = 15,

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criteria for determining whether the results of the procedure are of acceptable quality. 1 By contrast, a method is a orderly process or procedure used in the engineering of a product or performing a service (IEEE, 1990). A technique is a technical and managerial procedure used to achieve a given objective (IEEE, 1990). A process is a function that must be performed in the software life cycle. A process is composed of activities (IEEE, 1996). An activity is a constituent task of a process (IEEE, 1996). A task is a well de ned work assignment for one or more project members. Related tasks are usually grouped to form activities (IEEE, 1996).

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015 0125 01 0075 005 0025 5 10 15 X 20 25 30

An ontology engineering methodology needs to consider the following three types of activities: Ontology management activities. Ontology development activities. Ontology support activities. 9.2.2.1. 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. 9.2.2.2. 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. 9.2.2.3. 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

p = 03

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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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binomial distribution are possible using a statistical calculator or a computer algebra system, and so we do not need to approximate these probabilities with a normal curve, which we study in the chapter on continuous distributions Here are some examples

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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