This paper gives an overview about the development of the field of Knowledge Engineering over the last 15 years. We discuss the paradigm shift from a transfer view to a modeling view and describe two approaches which considerably shaped research in Knowledge Engineering: Role-limiting Methods and Generic Tasks. To illustrate various concepts and methods which evolved in the last years we describe three modeling frameworks: CommonKADS, MIKE, and PROTÉGÉ-II. This description is supplemented by discussing some important methodological developments in more detail: specification languages for knowledge-based systems, problem-solving methods, and ontologies. We conclude with outlining the

Problem solving methods (PSMs) are domain-independent reasoning components, which specify patterns of behavior which can be reused across applications. While the availability of extensive PSM libraries and the emerging consensus on PSM specification languages indicate the maturity of the field, a number of important research issues are still open. In particular, very little progress has been achieved on foundational and methodological issues. Existing libraries of PSMs lack a clear theoretical basis and only provide weak support for the method development process, usually in the form of informal guidelines. In this paper we will address these issues by illustrating a framework which characterizes PSMs in terms of problem commitments, problem-solving paradigms and domain assumptions. This framework provides i) a theoretical foundation for situating PSM research and individual PSMs, as well as ii) an organization which allows us to characterize method development and selection as a process of navigating through a three-dimensional space (defined by the three components of our framework). Individual moves through this space are specified by means of adapters. In the paper we will illustrate these ideas in detail, with examples taken from parametric design problem solving. 1.

Ontologies and problem-solving methods are promising candidates for reuse in Knowledge Engineering. Ontologies define domain knowledge at a generic level, while problem-solving methods specify generic reasoning knowledge. Both type of components can be viewed as complementary entities that can be used to configure new knowledge systems from existing, reusable components. In this paper, we give an overview of approaches for ontologies and problem-solving methods. 1 Introduction In 1991, the ARPA Knowledge Sharing Effort [NFF 91] envisioned a new way in which intelligent systems could be built. They proposed the following: "Building knowledgebased systems today usually entails constructing new knowledge bases from scratch. It could be done by assembling reusable components. Systems developers would then only need to worry about creating the specialized knowledge and reasoners new to the specific task of their system. This new system would interoperate with existing systems, us...

This paper describes a principled approach towards creating an IT-support environment for knowledge workers. Starting in the analysis phase our approach paves the way for putting an intelligent assistant to work within a typical business process environment. Thereby, this support intelligence is centred around the interdependencies between documents providing the background knowledge and business processes.

In this paper it is shown how specification of behavioural requirements from informal to formal can be integrated within knowledge engineering. The integration of requirements specification has addressed, in particular: the integration of requirements acquisition and specification with ontology acquisition and specification, the relations between requirements specifications and specifications of task models and problem solving methods, and the relation of requirements specification to verification.

Knowledge engineering has shown that besides the general methodologies from software engineering it is useful to develop special purpose methodologies for knowledge based systems (KBS). PROforma is a newly developed methodology for a specific type of knowledge based systems. PROforma is intended for decision support systems and in particular for clinical procedures in the medical domain. This paper reports on an evaluation study of PROforma, and on the trade-off that is involved between general purpose and special purpose development methods in Knowledge Engineering and Medical AI. Our method for evaluating PROforma is based on re-engineering a realistic system in two methodologies: the new and special purpose KBS methodology PROforma and the widely accepted, and more general KBS methodology CommonKADS. The four most important results from our study are as follows. Firstly, PROforma has some strong points which are also strong related to requirements of medical reasoning. Secondly, PRO...

: The development of knowledge-based systems requires the availability of domain and problem-solving knowledge. This knowledge must be acquired from domain experts. For this purpose the paper proposes to adopt the concept of scenarios known from requirements engineering and object oriented modelling to enrich the set of acquisition techniques. In RE and OO scenarios are used to define a vision of a future system. In knowledge engineering their scope has to be extended, but their advantages (ease of understanding, support of communication, focus on relevant aspects etc.) still hold for knowledge-based systems. 1 Motivation In the knowledge acquisition (KA) community it is common sense that for developing knowledgebased systems (KBS), a modelling approach has to be pursued to guarantee reliable, traceable, and maintainable systems of high quality. A prerequisite for such systems is the availability of the needed knowledge. Most current KA methods support knowledge engineers in ...

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Abstract—There is no standardised approach to modelling knowledge-based systems; where modelling is adopted, the techniques used are those from the software engineering domain. These tend to be used in an ad hoc way and are highly dependent on the experience of the knowledge engineers. This paper presents the adoption of a profile mechanism for the design of knowledge-based systems. The profile is created using the metamodel extension approach of UML and is based on XMF (eXecutable Meta-modelling Framework). XMF is an extension to the existing standards for meta-models: MOF, OCL and QVT. XMF offers an alternative approach in profile design which allows modification or the addition of new modelling constructs that are easily integrated with the core meta-model of UML. Keywords—knowledge-based system; XMF Profile; knowledge modelling; executable models; I.

This paper describes a principled approach towards creating an IT-support environment for knowledge workers. Starting in the analysis phase our approach paves the way for putting an intelligent assistant to work within a typical business process environment. Thereby, this support intelligence is centred around the interdependencies between documents providing the background knowledge and business processes.