Goal Seeking has a memory. Information is a product. Knowledge is a process.
Cloud-based Knowledge Quality Farzad Sabetzadeh PhD Candidate The Hong Kong Polytechnic University
Flashback KNOWLEDGE What is the Difference ?!!!! MEASERABILITY
Pushing to the edge of envelop Example of Semantic Web And Natural Language Disambiguation
Quality Problems Objective Subjective Adopted and Developed From Eppler M.J. (2006) & Pierce et al. (2006)
What are we missing in Knowledge Quality ? Example: No one can eat just one !!!
Quality Metrics Comparison Adopted From Pierce et al. (2006)
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
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
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)
What is so-called Cloud ? It can be dubbed as the ubiquitous locus of anything that can be available by virtual means
Why can Cloud Help ? Adopted from Negnevitsky (2006)
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
Cloud and Uncertainty(Source : Tom Koulopoulos, Delphi Group @http://www.delphigroup.com/)
Boisot, M., MacMillan, I.C & Han, K.S., (2007) “Exploration in Information Space : Knowledge, Agents and Organization” Oxford University Press.
Eppler, M.J. (2006) “ Managing Information quality : Increasing the value of information in knowledge-intensive products and processes”, Springer.
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
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
Negnevitsky, M. (2005) “ Artificial Intelligence : A Guide To Intelligent Systems”, Addison Wesley, Pearson Education
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