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Abstract: Intense interest in knowledge-acquisition research began 25 years ago, stimulated by the excitement about knowledge-based systems that emerged in the 1970s followed by the realities of the “AI Winter” that arrived in the 1980s. The knowledge-acquisition workshops that responded to this interest led to the formation of a vibrant research community that has achieved remarkable consensus on a number of issues. These viewpoints include (1) the rejection of the notion of knowledge as a commodity to be transferred from one locus to another, (2) an acceptance of the situated nature of human expertise, (3) emphasis on knowledge acquisition as the modeling of problem solving, and (4) the pursuit of reusable patterns in problem solving and in domain descriptions that can facilitate both modeling and system implementation. The Semantic Web community will benefit greatly by incorporating these perspectives in its work. [Copyright &y& Elsevier]

Problem-solving methods provide reusable architectures and components for implementing the reasoning part of knowledge-based systems. The Unified Problem-Solving Method Description Language (UPML) has been developed to describe and implement such architectures and components to facilitate their semi-automatic reuse and adaptation. In a nutshell, UPML is a framework for developing knowledge-intensive reasoning systems based on libraries ofg eneric problem-solving components. The paper describes the components and adapters, architectural constraints, development guidelines, and tools provided by UPML. UPML is developed as part of the IBROW project, which provides an Internet-based brokering service for reusing problem-solving methods. [ABSTRACT FROM AUTHOR]

The Prote´ge´ project has come a long way since Mark Musen first built the Prote´ge´ meta-tool for knowledge-based systems in 1987. The original tool was a small application, aimed at building knowledge-acquisition tools for a few specialized programs in medical planning. From this initial tool, the Prote´ge´ system has evolved into a durable, extensible platform for knowledge-based systems development and research. The current version, Prote´ge´-2000, can be run on a variety of platforms, supports customized user-interface extensions, incorporates the Open Knowledge-Base Connectivity (OKBC) knowledge model, interacts with standard storage formats such as relational databases, XML, and RDF, and has been used by hundreds of individuals and research groups. In this paper, we follow the evolution of the Prote´ge´ project through three distinct re-implementations. We describe our overall methodology, our design decisions, and the lessons we have learned over the duration of the project. We believe that our success is one of infrastructure: Prote´ge´ is a flexible, well-supported, and robust development environment. Using Prote´ge´, developers and domain experts can easily build effective knowledge-based systems, and researchers can explore ideas in a variety of knowledge-based domains. [Copyright &y& Elsevier]