Use of a domain model to drive an interactive knowledge-editing tool
International Journal of Man-Machine Studies - Knowledge acquisition for knowledge-based systems, part 1. Based on an AAAI work
Automated generation of model-based knowledge acquisition tools
Automated generation of model-based knowledge acquisition tools
Coupling application design and user interface design
CHI '92 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Knowledge Acquisition - Special issue on knowledge acquisition for therapy-planning tasks
Metatool support for custom-tailored, domain-oriented knowledge acquisition
Knowledge Acquisition
Interview-Based Knowledge Acquisition Using Dynamic Analysis
IEEE Expert: Intelligent Systems and Their Applications
Easy Programming: Empowering People to Build Their Own Applications
IEEE Expert: Intelligent Systems and Their Applications
Reuse with PROTÉGÉ-II: from elevators to ribosomes
SSR '95 Proceedings of the 1995 Symposium on Software reusability
Ontology-based information model development for science information reuse and integration
IRI'09 Proceedings of the 10th IEEE international conference on Information Reuse & Integration
Artificial Intelligence in Medicine
Is knowledge power? the role of knowledge in automated requirements elicitation
CAiSE'13 Proceedings of the 25th international conference on Advanced Information Systems Engineering
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Four prototype metatools, Protege, Dots, Dash, and Spark, which researchers are using to experiment with the automatic generation of knowledge-acquisition tools, are discussed. Protege and Dots are stand-alone metatools; Dash and Spark are subsystems. Dash is part of Protege II, a design environment for knowledge-based systems. Spark is part of the Spark, Burn, and Firefighter framework for the design of application systems. The two stand-alone tools, their environments, and their subsystems are compared. Protege demonstrates how one can instantiate knowledge-acquisition tools from a description of a problem-solving method. Dots, on the other hand, lets one design knowledge-acquisition tools for many applications. Spark, Burn, and Firefighter are similar to Protege II in that they emphasize developing problem-solving methods from reusable components, although Spark, Burn and Firefighter associate a knowledge-acquisition tool with each method in the library. Protege II uses Dash to generate knowledge-acquisition tools from domain ontologies.