1. Knowledge and Its Attributes Bahjat Abuhadba Dillion Rath Jessica Smith

2. What is knowledge?  Defined as: the range of one’s information or understanding. From Webster’s Dictionary.  Breaking it down: If knowledge is a range of information, then: Information is knowledge Information is data Data is information

3. Usable Representations  Defined as: the knowledge as being that which is embodied in usable representation.  Two key notions: Representation  Is some arrangement in time/space  Ex. Diagrams, photographs, mental patterns, etc.

4. Usable Representations  Usability Defined as: the amount of usable information perceived by the processor. Determined by the degree of the processor’s speed, accuracy and action taken

5. Knowledge States  Six states: Data: lowest level, gathering state Information: second level, selection state Structured Information: third level, analyzing state Insight: fourth level, synthesizing state Judgment: fifth level, weighing state Decision: Final level, evaluation state

6. Stocks and Flows  Stocks: inventory of knowledge available to processors  Flows: Two types: Knowledge transferal from one stock to another Knowledge flow from a stock into itself Equated to learning

7. Knowledge Versus Information  KVI perspective: Views knowledge as a state in its own right Aimed to define knowledge by differentiating it from information or data Thus, data is turned into information and information is turned into knowledge

8. Knowledge and Technology  1990’s was the rise of Knowledge Management and at the same time tremendous advances in computing and communication technology  Extremes KM has nothing to do with technology KM is all about technology

9. Technology is Incidental  Knowledge Uniquely human, only existing in the context of human interpretation and processing  Data or Information Knowledge that can be represented and processed by humans or computers

10. What happens if technology is eliminated?  Ernst & Young vanishes  Knowledge would be face to face or faxed, not through e-mail  Knowledge repositories would be human memory or pieces of paper, not web pages or databases  Search engines, Web crawlers would be of no importance

11. Technology is Everything  Technology is not Knowledge Management Technology vendors would become the primary sources for KM solutions Technology would become an end in and of itself, without attention to its consequences People would be seen as supporting the technology, instead of the technology enabling or amplifying human knowledge processing abilities

12. The Middle Path  Knowledge management is concerned with people, technology, organizations, and the fits among them  Focuses Representations that human processors find to be usable and methods/practices for effectively managing these representations and processors to max. usability and improve outcomes in the context of organizational and technological environments.

13. The Middle Path The representations that computer- based processors can utilize in accomplishing various tasks The enterprise as a processor, custodian, and user of knowledge The alignment and coordination of the various knowledge-related elements

14. Computer-Based Technology: A Servant of KM  CBT Computer Information Systems (CIS), Management Systems (MIS)  CBT has transformed how knowledge work is done Descriptive Knowledge: data and info at the low end to problem solutions, designs and decisions at the high end

15. Computer-Based Technology: A Servant of KM Procedural Knowledge: specifying the steps for performing some task Reasoning Knowledge: specifying what conclusion is valid when a particular situation exist

16. Computer Based Technology EmergedEmphasis Data processing systems 1950’s- 1960’s Representation of low grade descriptive knowledge Recording transactions Producing transactions Management Information systems 1960’s- 1970’s Representation of low to middle grade descriptive knowledge Record keeping based on transactions Producing predefined types of reports that organize data into more usable chunks of info Decision Support Systems 1970’s- 1990’s Representation of descriptive, procedural, and/or reasoning knowledge Use of knowledge to solve (or find) problems Delivery of knowledge needed by a decision maker  in a desired format  Possibly, on the spur-of-the-moment  Possibly, in response to unanticipated or novel knowledge needs Includes modeling systems, expert systems, online analytical processing, business intelligence systems Organizational computing systems 1980’s- 1990’s Facilitates knowledge flows and reuse among multiple participants in some organizational form May involve descriptive, procedural and/or reasoning knowledge Includes groupware, collaboration systems, workflow systems, enterprise systems, inter-organizational systems, adaptive systems Ubiquitous Computing1990’s-Universal, non-stop availability of knowledge and knowledge processors Includes Web-based, mobile, and embedded computing systems

17. Computer-Based Technology: A Servant of KM 1. CBT researchers are KM researchers We do not develop and deploy technology for its own sake, but because it helps us to better deal with knowledge of various types and in various gradations enroute to better individual and organizational performance 2. Opportunities for research that improves on current CBT Human and computer-based knowledge processors Supporting and performing knowledge manipulation task Assisting in the measurement, control, coordination, and leadership of knowledge Helping ensure that the right knowledge gets to the right processor

18. Computer-Based Technology: A Servant of KM 3. We need to better understand the users and usage of CBT in KM What works and under what conditions? What does not work, and why? What CBT advances and breakthroughs are needed? 4. We need to study outcomes of using CBT in KM What are its competitive impacts? How can CBT be used to implement a knowledge chain activity? How can CBT be used to enhance productivity, agility, innovation, or reputation as a means for competitive advantage?

19. Knowledge Attributes  Attribute: a dimension in which different instances can vary.  Nature of Dimensions: 1. Mode Type: is it explicit or implicit? 2. Descriptive vs. Procedural Vs Reasoning: does it describe characterize the stare of some world? Or

20. Knowledge Attributes Nature of Dimensions: Or such as in reasoning it specifies what action to take in a specific situation 3. Domain: the subject where the knowledge is used such as marketing engineering policy manufacturing...etc 4.Orientation: this distinguishes between knowledge directed toward subjects and

21. Nature of Dimensions in Knowledge Knowledge directed toward other processes. 5. Applicability: Ranges from global to local knowledge; the knowledge applicability is determined by where can this piece of knowledge be used globally or locally. 6.Accessibility: we measure this by: - Clarity: is it easily understandable.

22. Accessibility Measuring - Meaning: must make sense - Relevance: must be useful to the situation in which we are trying to resolve. - Importance: it must be crucial for the task we are trying to accomplish.

23. Nature of Dimensions in Knowledge 7.Validity and source: the knowledge should me accurate and correct. It must be consistent and helps deliver results. 8. Immediacy, Age: Knowledge should be known to be current or was it acquired in the past. Also, knowledge will range from old established to new knowledge.

24. Conclusion - Investigation of knowledge has occupied mankind for years. - It is part of the knowledge development cycle to keep investigating knowledge and seeking new evidence - The best example of development of knowledge is the development of the scientific theory

25. Conclusion  The most reliable way to enhance the creditability of a theory is to try to prove it wrong and the more scientists and knowledge seekers fail to do so the more the scientific theory becomes accurate and widely-accepted as a dependable piece of knowledge.