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Cloud Based Knowledge Quality

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  • Goal Seeking has a memory. Information is a product. Knowledge is a process.
  • Transcript

    • 1. Cloud-based Knowledge Quality
      Farzad Sabetzadeh
      PhD Candidate
      The Hong Kong Polytechnic University
    • 2. Flashback
      KNOWLEDGE
      What is the Difference ?!!!!
      MEASERABILITY
    • 3. Pushing to the edge of envelop
      Example of Semantic Web And Natural Language Disambiguation
    • 4. Quality Problems
      Objective
      Subjective
      Adopted and Developed From Eppler M.J. (2006) & Pierce et al. (2006)
    • 5. What are we missing in Knowledge Quality ?
      Example:
      No one can eat just one !!!
    • 6. Quality Metrics Comparison
      Adopted From Pierce et al. (2006)
    • 7. Why Quality Metrics are Different ?
      Knowledge
      Expectations = Uncertainty ?!!!!
      Purposeful (Choice of Mean and End)
      Chaotic
      Information
      Relations
      Goal-Seeking (Choice of Mean but no choice of End)
      Fuzzy
      Data
      Stimuli
      Self-maintaining (No choice of Mean and End)
      Crisp
    • 8. Godel Incompleteness Theorem
      If A is a theory based on an axiom B, B can not be proved to be a true statement within A; Thus A is an incomplete theory.
      Data
      Info
      Info
      Info
      Knowledge
      Info
      I’m alyawsinspried by the morinig sun
    • 9. Quality Knowledge Perspective
      Ontology Quality
      Sharing Quality
      Knowledge Item Quality
      Knowledge Retainer Quality
      Knowledge Usage Quality
    • 10. Knowledge Quality Pathway
      LinearityNon-linearity
      We can’t do much by direct corroborative reasoning on subjective matters like knowledge but we can get a better approximation for subjectivity through Scalable intersubjectivity (Social Cloud)
    • 11. What is so-called Cloud ?
      It can be dubbed as the ubiquitous locus of anything that can be available by virtual means
    • 12. Why can Cloud Help ?
      Adopted from Negnevitsky (2006)
    • 13. Cloud Logic
      Crowd Logic
      Cloud Logic
      Rule-based Reasoning
      Case-based Reasoning
    • 14. Quality & Uncertainty(Source : Maxim & Sluijs, 2011)
      Location of Uncertainty
      Uncertainty about process of knowledge production
      Uncertainty about process of knowledge context
      Source of Uncertainty
      Lack of Knowledge
      Variability
      Expert Subjectivity
      Communication Patterns
    • 15. Cloud and Uncertainty(Source : Tom Koulopoulos, Delphi Group @http://www.delphigroup.com/)
    • 16. Cloud, Quality & Uncertainty(Source : Maxim & Sluijs, 2011)
    • 17. The Big Picture(Source : Nova Spivack @ http://mindingtheplanet.net)
    • 18. The Crowd To Cloud Journey
      Co-Evolution (MetaWeb)
      Co-Creation (e.g Cloud Apps)
      Collaboration (e.g. Web 2.0)
      Cooperation (e.g Crowdsourcing)
    • 19. Published References
      • Boisot, M., MacMillan, I.C & Han, K.S., (2007) “Exploration in Information Space : Knowledge, Agents and Organization” Oxford University Press.
      • 20. Eppler, M.J. (2006) “ Managing Information quality : Increasing the value of information in knowledge-intensive products and processes”, Springer.
      • 21. Maxim, L. & Sluijs J. P. (2011) “Quality in environmental science for policy: Assessing uncertainty as a component of policy analysis” Journal of Environmental Policy and Science, Article in Press
      • 22. Melkas, H. & Harmaakorpi, V. ((2008) “Data, information and knowledge in regional innovation networks Quality considerations and brokerage functions”, European Journal of Innovation Management, Vol.11, No.1, pp.103-124
      • 23. Negnevitsky, M. (2005) “ Artificial Intelligence : A Guide To Intelligent Systems”, Addison Wesley, Pearson Education
      • 24. Pierce, E., Kahn, B. & Melkas, H. (2006) “A Comparison of Quality Issues for Data Information and Knowledge”, IRMA International conference Proceeding, IGI group, pp. 60-62

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