1. 1 Computer Science Department California Polytechnic State University San Luis Obispo, CA, U.S.A. Franz J. Kurfess Computers and Knowledge 1

2. 2 Some of the material in these slides were developed for a lecture series sponsored by the European Community under the BPD program with Vilnius University as host institution Acknowledgements 2

3. 3 Franz Kurfess: Computers and Knowledge Use and Distribution of these Slides These slides are primarily intended for the students in classes I teach. In some cases, I only make PDF versions publicly available. If you would like to get a copy of the originals (Apple KeyNote or Microsoft PowerPoint), please contact me via email at fkurfess@calpoly.edu. I hereby grant permission to use them in educational settings. If you do so, it would be nice to send me an email about it. If you’re considering using them in a commercial environment, please contact me first.fkurfess@calpoly.edu 3

4. 4 Franz Kurfess: Computers and Knowledge Overview Computers and Knowledge ❖ Motivation ❖ Objectives ❖ Evaluation Criteria ❖ Chapter Introduction ❖ Bridge-In ❖ Review of relevant concepts ❖ Overview new topics ❖ Terminology ❖ Data, Information, Knowledge ❖ Knowledge Management ❖ Computer Support ❖ Example: Great Pyramids ❖ Case Study: KM for Course Preparation ❖ Important Concepts and Terms ❖ Chapter Summary 4

5. 5 Franz Kurfess: Computers and Knowledge Logistics 5

6. 6 Franz Kurfess: Computers and Knowledge Logistics ❖ Introductions ❖ Course Materials ❖ textbook ❖ handouts ❖ Web page ❖ CourseInfo/Blackboard System and Alternatives ❖ Term Project ❖ Lab and Homework Assignments ❖ Exams ❖ Grading 6

7. 7 Franz Kurfess: Computers and Knowledge Preliminaries 7

8. 8 Franz Kurfess: Computers and Knowledge Bridge-In 8

9. 9 Franz Kurfess: Computers and Knowledge The Proliferation of Knowledge ❖ Wall street ❖ no physical assets ❖ make money by utilizing knowledge about investment opportunities ❖ consultants ❖ have knowledge about some specialized tasks ❖ tell customers what to do ❖ may be gone by the time their solutions are found to be flawed ❖ “energy brokers” ❖ companies that don’t own any physical facilities, but buy and sell energy ❖ made enormous profits during the 2000/2001 energy crisis 9

10. 10 Franz Kurfess: Computers and Knowledge Background ❖ How much knowledge do you manage? ❖ in your job ❖ student ❖ instructor ❖ researcher ❖ in your private life ❖ What are your roles concerning knowledge? ❖ consumer ❖ facilitator ❖ producer 10

11. 11 Franz Kurfess: Computers and Knowledge Pre-Test 11

12. 12 Franz Kurfess: Computers and Knowledge Motivation ❖ the amount of information and knowledge available increases steadily ❖ it becomes difficult to keep track of relevant knowledge ❖ the demands for applying knowledge to a particular task also become stronger ❖ job expectations ❖ competitive pressure ❖ the benefits from utilizing knowledge become greater ❖ higher profits ❖ better products ❖ more knowledgeable people 12

13. 13 Franz Kurfess: Computers and Knowledge Objectives ❖ be aware of the role of knowledge in professional and private life ❖ understand the impact of knowledge (or lack of it) for important decisions ❖ understand the necessity for knowledge management to deal with the large amount of knowledge and information ❖ explore the role of computer-based tools and technologies for knowledge management 13

14. 14 Franz Kurfess: Computers and Knowledge Evaluation Criteria 14

15. 15 Franz Kurfess: Computers and Knowledge Terminology ❖ Data ❖ Information ❖ Knowledge ❖ Wisdom 15

16. 16 Franz Kurfess: Computers and Knowledge Data, Information, and Knowledge (DIK) q good overview: ❖ Liew, A. (June 2007). Understanding Data, Information, Knowledge And Their Inter- Relationships. Journal of Knowledge Management Practice, Vol. 8, No. 2. http://www.tlainc.com/articl134.htm http://www.tlainc.com/articl134.htm q often visualized as “knowledge pyramid”knowledge pyramid 16

17. 17 Franz Kurfess: Computers and Knowledge Data ❖ described by schematic arrangements ❖ e.g. data bases, tables, spreadsheets ❖ contents of fields (slots cells) are the data values ❖ values are meaningless without the schema 17

18. 18 Franz Kurfess: Computers and Knowledge Information ❖ data together with the relevant context ❖ context may be explicit or implicit ❖ examples: ❖ train schedule ❖ addresses, phone numbers ❖ instructions for preparing a recipe 18

19. 19 Franz Kurfess: Computers and Knowledge Knowledge ❖ knowledge characteristics ❖ meaningful only with respect to humans ❖ context-sensitive ❖ may be elaborate ❖ may be explicit or tacit ❖ explicit knowledge consists of documented facts ❖ frequently objective ❖ can be “spelled out” ❖ tacit knowledge is in people’s heads ❖ frequently subjective ❖ surfaces through interaction [Knowledge Ability 1998] 19

20. 20 Franz Kurfess: Computers and Knowledge Wisdom ❖ requires aspects beyond knowledge ❖ factors relevant for wisdom [Etzold 2008] ❖ social competence ❖ openness ❖ intensive learning and practical experiences ❖ education ❖ talent for mentoring 20

21. 21 Franz Kurfess: Computers and Knowledge DIK Pyramid 21 http://healeylibrary.wikispaces.com/space/showimage/knowledge_pyramid.jpg

22. 22 Franz Kurfess: Computers and Knowledge DIK: RDF Perspective 22 http://rdfer.com/media/2006/12/12/data_info_knowledge.gif http://rdfer.com/swk/data-information-knowledge

23. 23 Franz Kurfess: Computers and Knowledge DIK as Graph 23 http://delarue.net/blog/wp-content/uploads/2007/08/kmmodel.JPG

24. 24 Franz Kurfess: Computers and Knowledge DIK Variation: Innovation Pyramid 24 http://www.theinnovationroadmap.com/Travelogue/InformationPyramid.gif

25. 25 Franz Kurfess: Computers and Knowledge DIK: Layers, Characteristics, Systems 25

26. 26 Franz Kurfess: Computers and Knowledge End Data, Information, Knowledge 26

27. 27 Franz Kurfess: Computers and Knowledge What is Knowledge Management? ❖ information technology perspective ❖ computers as support tools for dealing with large quantities of knowledge and information ❖ business perspective ❖ benefits for organizations ❖ philosophical perspective ❖ epistemology: what is knowledge? 27

28. 28 Franz Kurfess: Computers and Knowledge Knowledge Management Definitions ❖ Karl-Erik Sveiby (Organization Theorist) Knowledge Management is the art of creating value from an organization’s intangible assets. ❖ John Gundy, Knowledge Ability (KM Company) Knowledge Management is the process of placing knowledge under management remit. [Sveiby 2000] 28

29. 29 Franz Kurfess: Computers and Knowledge KM Phases ❖ 1992 - 1995: productivity enhancement ❖ how can information technology used to share knowledge across organizations ❖ Lotus Notes, Web pages, project databases, best practices,... ❖ 1995 - 2000: customer relations ❖ how can information about customers be utilized ❖ data warehousing, data mining ❖ 2000 - 2003: interaction ❖ interactive Web pages, e-commerce ❖ 2002 - ??? ❖ interoperability (XML, Web services and related technologies) ❖ interpretation (ontologies, Semantic Web) [Sveiby 2000] 29

30. 30 Franz Kurfess: Computers and Knowledge End Knowledge Management 30

31. 31 Franz Kurfess: Computers and Knowledge Computer Support ❖ capabilities ❖ limitations ❖ human-computer interaction aspects 31

32. 32 Franz Kurfess: Computers and Knowledge Capabilities ❖ speed ❖ lots of simple operations at extremely high speeds ❖ storage capacity ❖ approaching Terabytes for personal computers ❖ methods ❖ algorithms to perform specified functions ❖ limited errors ❖ objective ❖ no fatigue 32

33. 33 Franz Kurfess: Computers and Knowledge Limitations ❖ semantic gap ❖ very limited learning ❖ no “common sense” ❖ effective use of computational power ❖ speed ❖ storage capacity 33

34. 34 Franz Kurfess: Computers and Knowledge Semantic Gap ❖ practically all computer operations performed at the syntactic level ❖ “symbol manipulation” ❖ no consideration of (intended) meaning ❖ humans automatically interpret items under examination ❖ “parasitic interpretation” of symbols (names) 34

35. 35 Franz Kurfess: Computers and Knowledge Human-Computer Interaction ❖ computers are essential tools when humans deal with knowledge ❖ the current support to let humans utilize knowledge effectively is very limited ❖ syntax-oriented search (strings/key words) ❖ storage ❖ organization largely done by humans ❖ tool limitations ❖ only suitable for professionals ❖ limited capabilities 35

36. 36 Franz Kurfess: Computers and Knowledge End Computer Support 36

37. 37 Franz Kurfess: Computers and Knowledge Example Computers and Knowledge: The Great Pyramids ❖ using computers to explore potential solutions to the mystery of how the Egyptian pyramids were built ❖ information storage ❖ documents, facts,... ❖ interpretation of information ❖ knowledge organization ❖ knowledge presentation and visualization ❖ knowledge verification 37

38. 38 Franz Kurfess: Computers and Knowledge Knowledge and the Great Pyramids ❖ How did the Egyptians build these monumental edifices? ❖ technology available at the time ❖ theories about building pyramids ❖ plausibility of these theories 38

39. 39 Franz Kurfess: Computers and Knowledge Available Technologies ❖ soft metals, mostly copper ❖ no iron ❖ logs, beams ❖ apparently no wheels ❖ sculpted blocks of stone ❖ maybe early forms of concrete 39

40. 40 Franz Kurfess: Computers and Knowledge Pyramid Theories ❖ over time, a number of different theories (hypotheses) have bee proposed ❖ outer ramp ❖ long ramp leading to the current level ❖ increased as the pyramid grows ❖ inner ramp ❖ outer ramp for the lower levels, used up for higher levels ❖ spiral inner ramp, together with levers and counterbalances ❖ lifting mechanisms ❖ machines that allow the lifting of the large blocks to higher levels ❖ extraterrestrials, … 40

41. 41 Franz Kurfess: Computers and Knowledge Convincing Arguments ❖ What does it take to convince you about the plausibility of a theory? ❖ common-sense explanations: may sound good, but gloss over important issues ❖ diagrams: illustration of essential methods ❖ models: computer-based, small-scale ❖ scientific papers: peer reviewed, calculations, incomprehensible to ordinary mortals ❖ simulations: 3D CAD, animated, physics engines ❖ reconstruction: building (parts of) the real thing 41

42. 42 Franz Kurfess: Computers and Knowledge Case Study: KM for Course Preparation ❖ easy case: re-use existing material ❖ text book, presentation material, student assignments, exams, projects ❖ difficult case: brand-new course ❖ no existing material suitable for teaching purposes ❖ existing sources ❖ research monographs, edited volumes, related text books, conference proceedings, journal special issues, articles, technical reports, white papers, company brochures, Web pages 42

43. 43 Franz Kurfess: Computers and Knowledge Course Development as KM Application ❖ problem ❖ development of a course outline ❖ identification of relevant material ❖ extraction of relevant knowledge ❖ integration of various knowledge pieces ❖ different representation media ❖ paper (books, journals) ❖ microfilm ❖ digital (electronic versions of books, journals, etc; Web pages; data bases, computer programs) ❖ presentation of knowledge ❖ presentation medium ❖ identification of evaluation criteria ❖ development of exercises 43

44. 44 Franz Kurfess: Computers and Knowledge Tools for Course Preparation ❖ course outlinebrain, paper, editor, spreadsheet ❖ identification of materialbrain, paper (printed material), search engines, library catalog/DBs ❖ organization of materialbrain, folders, labels, directories, files ❖ extraction of knowledgebrain, paper, text editor, helpers ❖ integration of pieces brain, presentation program, helpers ❖ presentation of knowledgebrain, presentation program ❖ evaluation criteria brain, text editor ❖ development of exercisesbrain, text editor, helpers ❖ color scheme ❖ red: braingreen: paperyellow: computer support 44

45. 45 Franz Kurfess: Computers and Knowledge Deficiencies of tools ❖ much of the tedious work is left to the instructor ❖ little support for important knowledge management activities ❖ primitive tools are used for high-level tasks ❖ directories, file names for the categorization of knowledge items 45

46. 46 Franz Kurfess: Computers and Knowledge End Case Study 46

47. 47 Franz Kurfess: Computers and Knowledge References 47

48. 48 Franz Kurfess: Computers and Knowledge References [Etzold 2008] Sabine Etzold, Alte an die Arbeit. Zeit, 6. März 2008, S. 34. (Article on the work of Prof. Ursula Staudinger on aging and wisdom). Liew, A. (June 2007). Understanding Data, Information, Knowledge And Their Inter-Relationships. Journal of Knowledge Management Practice, Vol. 8, No. 2. http://www.tlainc.com/articl134.htm http://www.tlainc.com/articl134.htm 48

49. 49 Franz Kurfess: Computers and Knowledge Ausklang 49

50. 50 Franz Kurfess: Computers and Knowledge Post-Test 50

51. 51 Franz Kurfess: Computers and Knowledge Evaluation ❖ Criteria 51

52. 52 Franz Kurfess: Computers and Knowledge Important Concepts and Terms cognitive science computer science data information interpretation knowledge knowledge management knowledge pyramid learning semantics syntax wisdom 52

53. 53 Franz Kurfess: Computers and Knowledge Summary Computers and Knowledge ❖ with the increase in the amount of information and knowledge, knowledge management will play a very important role in our professional and personal lives ❖ although a lot of knowledge is available in digital form, computer support for KM is mediocre ❖ many basic techniques and methods have been developed, but their integration into easily usable systems and tools is still missing 53

54. 54 Franz Kurfess: Computers and Knowledge 54