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KNOWLEDGE DICHOTOMY AND SEMANTIC KNOWLEDGE MANAGEMENT

Explore the application of semantic knowledge management in modern business contexts, addressing knowledge standardization, instantiation, and the evolution of KM models. Learn about computer-aided KM and solidification modes.

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KNOWLEDGE DICHOTOMY AND SEMANTIC KNOWLEDGE MANAGEMENT

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  1. KNOWLEDGE DICHOTOMY AND SEMANTIC KNOWLEDGE MANAGEMENT Jiehan Zhou Technical Research Centre of Finland Kaitoväylä 1, 90571 Oulu, Finland Email: jiehan.zhou@vtt.fi

  2. Outline 1. Introduction 2. Notions 6.Semantic KM and Case study Semantic KM 3. Computer-based KM 5. Semantic KM requirements 4. Knowledge solidification modes

  3. Introduction • Modern knowledge-intensive businesses • Multi-disciplinary • Decision-making • Implementation • Multi-culture • Semantic knowledge management

  4. Notions • Data, information and knowledge • Knowledge in context and dichotomy • Ontology • Knowledge management and its objectives • Knowledge standardization and instantiation • Semantic KM

  5. Computer-based KM • General KM model • Nonaka's knowledge conversion model • Knowledge dichotomy and Nonaka's KM model transcription • Computer-aided KM • Matters in computer-aided KM

  6. General KM model

  7. Nonaka and Takeuk 's knowledge conversion mechanisms

  8. Knowledge dichotomy Evolution Standardization Instantiation Evolution

  9. Computer-aided KM and standardization and instantiation • People to people • People to computer • Computer to computer • Computer to people

  10. Matters in computer-aided KM • Partly freeing human from mental work • Enlarging the scope of knowledge reusing and sharing • Reducing knowledge management costs • Unifying knowledge processing

  11. Knowledge solidification modes

  12. Requirements on Semantic KM • Knowledge sharing and reusing • Knowledge types • Knowledge quality • Knowledge cost • Knowledge timeliness • Knowledge unification

  13. A common Semantic KMS

  14. Case study - System model

  15. Case study: -knowledge standardization

  16. Case study: -Knowledge instantiation <!-- DEFINITION OF THE CLASSES AND SUB CLASSES --> <rdfs:Class rdf:ID="Entity"> <rdfs:label xml:lang="en">Entity</rdfs:label> <rdfs:comment xml:lang="en">Root of the classes</rdfs:comment> </rdfs:Class> <rdfs:Class rdf:ID="Manufacturing"> <rdfs:subClassOf rdf:resource="#Entity"/> <rdfs:label xml:lang="en">Manufacturing</rdfs:label> <rdfs:comment xml:lang="en">the process of producing economic goods, including tangible goods and intangible services from resources of production, thus creating utility by increasing value added.</rdfs:comment> </rdfs:Class> <rdfs:Class rdf:ID="ManufacturingMarket"> <rdfs:subClassOf rdf:resource="#Manufacturing"/> <rdfs:label xml:lang="en">manufacturing market</rdfs:label> <rdfs:comment xml:lang="en">manufacturing market</rdfs:comment> </rdfs:Class> <rdfs:Class rdf:ID="IntegratedManufacturingManagementSystem"> <rdfs:subClassOf rdf:resource="#Manufacturing"/> <rdfs:label xml:lang="en">integrated manufacturing management system</rdfs:label> <rdfs:comment xml:lang="en"></rdfs:comment> </rdfs:Class> …..

  17. Case study:-Knowledge query

  18. Conclusion and discussion • Knowledge-intensive business and semantic KM • Fundamentals on KM • Knowledge dichotomy and semantic KM • Automation knowledge standardization and instantiation

  19. Thanks and Questions

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