A user's view of current practice and possibilities.- The management and maintenance of an operational KADS system development.- Knowledge engineering trends in Europe.- Applications of machine learning.- Conceptual models for automatic generation of knowledge-acquisition tools.- An approach to operationalize conceptual models: The shell AIDE.- Linking modeling to make sense and modeling to implement systems in an operational modeling environment.- Common ground and differences of the KADS and strong-problem-solving-shell approach.- Differentiating problem solving methods.- Using generalised directive models in knowledge acquisition.- Towards a formal framework to compare protocol interpretations and task specifications.- Knowledge acquisition driven by constructive and interactive induction.- Knowledge refinement using Knowledge Acquisition and Machine Learning Methods.- Generating configuration expert systems from conceptual specifications of the expert knowledge.- Yet another formalisation of KADS conceptual models.- The KEEP model, a knowledge engineering process model.- Domain-driven knowledge modelling: Mediating & intermediate representations for knowledge acquisition.- PMI: Knowledge elicitation and De Bono's thinking tools.- A new approach to the solution of expert classification problems.- Knowledge acquisition for explainable, multi-expert, knowledge-based design systems.- Causal model-based knowledge acquisition tools: Discussion of experiments.- Knowledge base maintenance and consistency checking in MOLTKE/HyDi.- Acquiring knowledge of knowledge acquisition: A self-study of generic tasks.- Reusable analysis and design components for knowledge-based system development.- Acquiring descriptive knowledge for classification and identification.- Intelligent documentation as a catalyst for developing cooperative knowledge-based systems.- eQuality: An application of DDUCKS to process management.