Abstract: A method of managing knowledge in a knowledge base involves representing instantiations of knowledge in knowledge objects, each of which has elements of information, managing knowledge objects to minimize the number of knowledge objects while ensuring that all known instantiations are represented in the knowledge base, generalizing instantiations to develop generalized instantiations, testing generalized instantiations against all known instantiations to identify redundancies among knowledge objects and to identify additional knowledge, and modifying the knowledge base to minimize redundancies and to add to the knowledge base only to facilitate retrieval of knowledge or to add additional knowledge.

Abstract: Improving an entity's operational performance involves monitoring use of its knowledge by measuring use of a knowledge base storing its knowledge, and monitoring knowledge that it generates by evaluating knowledge quality and efficiency of its knowledge generation. In another embodiment, an entity's operational performance is improved by developing processes to build knowledge and sustain its knowledge use, developing systems to facilitate reuse of knowledge (including storing its knowledge in a knowledge base); and developing systems to generate knowledge and incorporate it into the knowledge base. The entity's knowledge use is analyzed to analyze its operational performance.

Abstract: A method of and system for managing and maintaining knowledge bases having knowledge in objects involves authors creating authoring output comprising knowledge objects and analysts managing knowledge base content. Authors use conventions and guides to add uniformity among knowledge objects. Analysts manage backlog of knowledge awaiting entry into the knowledge base, provide to authors feedback from knowledge base users and beneficiaries, and review authoring output for technical accuracy, adherence with the conventions and guides, knowledge base usability, and responsiveness by authors to feedback.

Abstract: A method for creating knowledge bases comprises conducting a baseline analysis of aspects of developing a knowledge base. At least one aspect is surveyed, results developed, and a knowledge base complexity indicator is developed to demonstrate for each aspect an expected level of effort required in developing and operating the knowledge base. The results are used to define a scope of and approach for developing the knowledge base. They are input to an in-depth analysis, which may comprise a domain analysis, a reservoir analysis, and a vector analysis, and a construction and seeding plan for the knowledge base is output. The knowledge base is constructed and seeded in accordance with the plan. A deployment plan for deployment of the knowledge base is developed, and used to deploy the knowledge base. Operational processes for using, monitoring and maintaining the knowledge base are specified and implemented according to their specifications.

Abstract: A method and a domain candidate benefit indicator for selecting knowledge domains for a knowledge base from at least one domain candidate involves developing a domain candidate benefit value for each domain candidate. Domain selection is based on a comparison of the domain candidate benefit values, which are numerical values developed by identifying for each domain candidate at least one forecasting attribute having an ability to forecast an extent of benefit of selecting the domain candidate to be the selected domain. Sub-domains may be selected by identifying sub-domain candidates in the selected domain and developing a sub-domain candidate benefit value for each sub-domain candidate. The selected sub-domain is selected based on a comparison of sub-domain candidate benefit values. The domain selection methodology may also be used to develop a knowledge base seeding methodology.