1. For example, someone with common sense would know not to touch a red stove eye.
2. Procedural (repetitive, stepwise) versus Episodical (grouped by episodes or cases)
2.1. Data Processing versus Knowledge-based Systems
3. Understanding Knowledge
3.1. Basic Knowledge-related Definitions
3.1.1. Common Sense
3.1.1.1. The knowledge and experience which most people already have, or which the person using the term believes that they do or should have
3.1.1.2. Some related concepts include intuitions, pre-theoretic belief, ordinary language, foundational beliefs, axioms, wisdom, folk wisdom, folklore, and public opinion.
3.1.1.3. "the basic level of practical knowledge and judgment that we all need to help us live in a reasonable and safe way“.
3.1.1.4. Common-sense ideas tend to relate to events within human experience and appear commensurate with human scale.
3.1.2. Fact
3.1.2.1. A fact (derived from the Latin factum) is something that has really occurred or is actually the case.
3.1.2.2. The usual test for a statement of fact is verifiability, which is whether it can be proven to correspond to experience.
3.1.2.3. Standard reference works are often used to check facts.
3.1.2.4. The most fundamental heuristic is trial and error, which can be used in everything from matching nuts and bolts to finding the values of variables in algebra problems.
3.1.2.5. Scientific facts are verified by repeatable experiments.:Sunrise and sunset.
3.1.2.6. Examples of this method include using a rule of thumb, an educated guess, an intuitive judgment, or common sense.
3.1.3. Heuristic
3.1.3.1. Where the exhaustive search is impractical, heuristic methods are used to speed up the process of finding a satisfactory solution.
3.1.3.2. Heuristic ("find" or "discover") refers to experience-based techniques for problem solving, learning, and discovery.
3.1.3.3. If you are having difficulty understanding a problem, try drawing a picture.
3.1.3.4. Heuristic Virus.
3.1.4. Knowledge
3.1.4.1. Understanding gained through experience; familiarity with the way to perform a task; an accumulation of facts, procedural rules, or heuristics
3.1.5. Intelligence
3.1.5.1. If you can't find a solution, try assuming that you have a solution and seeing what you can derive from that ("working backward").
3.2. Data, Information and Knowledge
3.2.1. Data: Unorganized and unprocessed facts; static; a set of discrete facts about events
3.2.1.1. Information: Aggregation of data that makes decision making easier
3.3. Types of Knowledge
3.3.1. Shallow (readily recalled) and deep (acquired through years of experience)
3.3.2. Explicit (already codified) and tacit (embedded in the mind)
3.3.2.1. Explicit (knowing-that) knowledge: knowledge codified and digitized in books, documents, reports, memos, etc.
3.3.2.1.1. The capacity to acquire and apply knowledge
3.3.2.2. Tacit (knowing-how) knowledge: knowledge embedded in the human mind through experience and jobs
3.4. What makes someone an expert (knowledge worker)?
3.4.1. An expert in a specialized area masters the requisite knowledge
3.4.2. The unique performance of a knowledgeable expert is clearly noticeable in decision-making quality
3.4.2.1. Knowledge is derived from information in the same way information is derived from data; it is a person’s range of information
3.4.3. Knowledgeable experts are more selective in the information they acquire
3.5. Expert’s Reasoning Methods
3.5.1. Experts are beneficiaries of the knowledge that comes from experience
3.5.2. Reasoning by analogy: relating one concept to another
3.5.3. Case-based reasoning: reasoning from relevant past cases
3.5.4. Formal reasoning: using deductive or inductive methods
3.5.4.1. Inductive reasoning: reasoning from a set of facts or individual cases to a general conclusion
3.5.4.2. Deductive reasoning: exact reasoning. It deals with exact facts and exact conclusions
4. “Knowledge has become the key resource, …we need systematic work on the quality of knowledge and the productivity of knowledge
5. KM is important for organizations that continually face downsizing or a high turnover percentage due to the nature of the industry
6. Knowledge Sharing Systems
7. Knowledge Discovery Systems
8. Related to the concept of intellectual capital (both human and structural).
9. KM methodologies and technologies must enable effective ways to elicit, represent, organize, re-use, and renew this knowledge
10. Knowledge management (KM) may be defined simply as doing what is needed to get the most out of knowledge resources.
11. Social/Structural mechanisms (e.g., mentoring and retreats, etc.) for promoting knowledge sharing.
12. Leading-edge information technologies (e.g., Web-based conferencing) to support KM mechanisms.
13. Knowledge management systems (KMS): the synergy between social/structural mechanisms and latest technologies
14. KM should not distance itself from the knowledge owners, but instead celebrate and recognize their position as experts in the organization
14.1. Learning by discovery: undirected approach in which humans explore a problem area with no advance knowledge of what their objective is
15. Knowledge as Key Resource
16. What is Knowledge Management (KM)?
16.1. KM focuses on organizing and making available important knowledge, wherever and whenever it is needed.
17. driving forces
17.1. Diminishing Individual Experience
17.2. Increasing Domain Complexity
17.3. Accelerating Market Volatility
18. Role of KM in today’s organization
19. Knowledge Management System (KMS)?
20. Classification of Knowledge Management Systems
20.1. Knowledge Capture Systems
20.1.1. Knowledge Application Systems