Understanding Knowledge

1. Understanding Knowledge • Prepared by : • A.Alzubair Hassan • KassalaUniversity • Dept. Computer Science Lecture One – Part II

2. Review of Last Lecture • What is Knowledge Management (KM)? • What are the driving forces? • Role of KM in today’s organization • What is Knowledge Management System (KMS)? • Classification of Knowledge Management Systems • Effective Knowledge Management

3. Knowledge Management

4. In this Lecture • Basic Knowledge-related Definitions • Data, Information and Knowledge • Data Processing versus Knowledge-based Systems • Types of Knowledge • What makes someone an expert (knowledge worker)?

5. Basic Knowledge-Related Definitions

6. Basic Knowledge-Related Definitions

7. Basic Knowledge-Related Definitions

8. Basic Knowledge-Related Definitions

9. Basic Knowledge-Related Definitions

10. Basic Knowledge-Related Definitions

11. Data, Information, and Knowledge • Data: Unorganized and unprocessed facts; static; a set of discrete facts about events • Information: Aggregation of data that makes decision making easier • Knowledgeis derived from information in the same way information is derived from data; it is a person’s range of information

12. Knowledge Value Zero Low High Medium Very High Information Data Relationship between data, information and Knowledge

13. Knowledge pH = 0.40 pT = 0.60 RH = +$10 RT = -$8 nH = 40 nT = 60 pH = nH/(nH+nT) pT = nT/(nH+nT) EV=pH RH+ pT RT Counting H T H T T H H H T H … T T T H T EV = -$0.80 Information Data Value Zero Low Medium High Very High An illustration

14. Knowledge Information System Data Information Knowledge Use of information Decision Events Relating Data, Information, and Knowledge to Events

15. Sources of knowledge • People • Books • Experience • Experimentation and observation • Thinking and pondering

17. Types (Categorization) of Knowledge • Shallow(readily recalled) and deep(acquired through years of experience) • Explicit (already codified) and tacit (embedded in the mind) • Procedural(repetitive, stepwise) versus Episodical(grouped by episodes or cases)

18. Knowledge Categories Procedural Explicit General Declarative Tacit Specific

19. Explicit and Tacit Knowledge • Explicit(knowing-that) knowledge: knowledge codified and digitized in books, documents, reports, memos, etc. • Tacit (knowing-how) knowledge: knowledge embedded in the human mind through experience and jobs

20. Illustrations of the Different Types of Knowledge

21. What makes someone an expert? • An expert in a specialized area masters the requisite knowledge • The unique performance of a knowledgeable expert is clearly noticeable in decision-making quality • Knowledgeable experts are more selective in the information they acquire • Experts are beneficiaries of the knowledge that comes from experience

22. Expert’s Reasoning Methods • Reasoning by analogy: relating one concept to another • Formal reasoning: using deductive or inductive methods • Case-based reasoning: reasoning from relevant past cases

23. Deductive and inductive reasoning • Deductive reasoning: exact reasoning. It deals with exact facts and exact conclusions • Inductive reasoning: reasoning from a set of facts or individual cases to a general conclusion

24. Human’s Learning Models • Learning by experience: a function of time and talent • Learning by example: more efficient than learning by experience • Learning by discovery: undirected approach in which humans explore a problem area with no advance knowledge of what their objective is.

25. Questions ???!!

26. I hope this was entertaining .