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Conceptual Framework, Models, and Methods of Knowledge Acquisition and Management for Competency Management in Various Areas

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Knowledge Engineering and the Semantic Web (KESW 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 394))

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Abstract

An approach to organizing knowledge acquisition and management (KAM) and an appropriate conceptual framework for wide competency management sphere and other traditional humanities subject domains (SD) are described. The main purpose of the approach is to support possibility of SD experts work not only with the knowledge, but also with the knowledge metamodel without knowledge engineers’ participation. The framework combines methods of knowledge elicitation and description well-known in humanities with formal methods for knowledge modeling. The framework includes the set of principles, a model of multidimensional space for visualization of continuing education (LifeLong Learning Space, LLLS), normalized competency metamodel (NCMM), and the process of NCMM tailoring. LLLS is used as domain-specific KAM goals model and as a tool for intuitively obvious goals visualization. Well-order and partial order relationships defined on LLLS dimensions are used for competency profiles evaluation and comparison. NCMM facilitates KAM process structuring and control. Rules for KAM process support and performance are described. The types of completed projects for more specific domains are mentioned.

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Zinder, E.Z., Yunatova, I.G. (2013). Conceptual Framework, Models, and Methods of Knowledge Acquisition and Management for Competency Management in Various Areas. In: Klinov, P., Mouromtsev, D. (eds) Knowledge Engineering and the Semantic Web. KESW 2013. Communications in Computer and Information Science, vol 394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41360-5_18

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  • DOI: https://doi.org/10.1007/978-3-642-41360-5_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41359-9

  • Online ISBN: 978-3-642-41360-5

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