CPE/CSC 580: Knowledge Management

1. CPE/CSC 580: Knowledge Management Dr. Franz J. Kurfess Computer Science Department Cal Poly

2. Introduction Knowledge Processing Knowledge Acquisition, Representation and Manipulation Knowledge Organization Classification, Categorization Ontologies, Taxonomies, Thesauri Knowledge Retrieval Information Retrieval Knowledge Navigation Knowledge Presentation Knowledge Visualization Knowledge Exchange Knowledge Capture, Transfer, and Distribution Usage of Knowledge Access Patterns, User Feedback Knowledge Management Techniques Topic Maps, Agents Knowledge Management Tools Knowledge Management in Organizations Course Overview

3. Motivation Why do we need to know all this stuff? Objectives What you should know afterwards Evaluation Criteria How I can find out if you know what you should know Warm-Up Review of relevant concepts Overview new topics Terminology Case Study: My Personal Need for KM Finding and organizing materials for this class Tools to support this Case Study: KM at an Organization like Cal Poly Important Concepts and Terms all the old and new terms Chapter Summary If you know this, you may be able to survive the class Overview Introduction

4. Logistics • Introductions • Course Materials • textbook: none • handouts: some • Web pages: tons • CourseInfo/Blackboard System and Alternatives • Term Project • Knowlets and Knowledge Management • Lab and Homework Assignments • Exams • Grading

5. 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 • “energy brokers” • companies that don’t own any physical facilities, but buy and sell energy • made the biggest profits during the current energy crisis

6. Background • How much knowledge do you manage? • as a student • in your job • in your private life

7. 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

8. 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 • discuss the role of computer-based tools and technologies for knowledge management

9. 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?

10. Knowledge Management in Perspective [Sveiby 2000]

11. Knowledge Management Definitions • Karl-Erik Sveiby (Organization Theorist)Knowledge Management is the art of creating value from an organizations intangible assets. • John Gundy, Knowledge Ability (KM Company)Knowledge Management is the process of placing knowledge under management remit. [Sveiby 2000]

12. 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 - ?: interaction • interactive Web pages, e-commerce [Sveiby 2000]

13. KM is Like Building a House...…First the Foundation, Then the Structure • The fundament of KM represents a set of Behavioural/Structural Conditions • The walls of KM represent a set of Operational Conditions • The roof of KM represents the corporate knowledge by which learning, innovation, speed and productivity will be enhanced [KPMG 1999]

14. Open, sharing culture COMMITMENT TEAMWORK KNOWLEDGE SHARING ORGANISATION STRUCTURE & PROCESSES Non-sharing culture From a Non-Sharing to aSharing Environment through Incentives • HOW? • Performance metrics • Science workshops • Technology exchange networks • Extra budget [KPMG 1999]

15. Integrated Information System UPGRADING OF EXISTING KNOWLEDGE ENABLING TECHNOLOGIES INFORMATION RESEARCH PROCESS GENERATION OF NEW IDEAS Separate information systems From Non-Integrated Information Systemsto Integrated Systems • HOW? • Database technology • Groupware • Web technology • User-interface technology • Intranet [KPMG 1999]

16. not in place advanced realised starting 1 2 3 4 • Preparing initiative • Initiative in place No understanding of KM Top management commitment Focus on group success 1,9 Open & sharing culture Focus onindividual success 2,0 2,1 Power culture 2,3 Process-orientedorganisation Hierarchical organisation The Score on KM Behaviouraland Structural Components • On the behavioural/structural axis, there is still enough improvement potential. [KPMG 1999]

17. not in place advanced realised starting 1 2 3 4 • Preparing initiative • Initiative in place The Score on KM Operational Components Integrated databases linked with workflow Professional research methods Structured, strategic knowledge creation Knowledge supporting decision- making 2,1 2,1 Knowledge stored mentally and physically Ad-hoc data collection 1,9 2,0 Ad-hoc knowledge creation Non-customiseddata • A quick fix is not possible with regard to the implementation of KM. • Step by step, the KM performance should be improved. [KPMG 1999]

18. Industrial vs. Knowledge Company

19. 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

20. 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

21. Tools for Course Preparation • course outline brain, paper, editor, spreadsheet • identification of material brain, search engines, library catalog/DBs • organization of material brain, folders, labels, directories, files • extraction of knowledge brain, paper, text editor, helpers • integration of pieces brain, presentation program, helpers • presentation of knowledge brain, presentation program • evaluation criteria brain, text editor • development of exercises brain, text editor,helpers • 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

22. Knowledge Management at Cal Poly • what kind of knowledge is essential for such an organization • what are the tools in common use

23. Knowledge Management for Students • what are important KM needs • what KM tasks do you perform • which tools and techniques do you use • what can be improved through smarter computers

24. Post-Test

25. Important Concepts and Terms • presentation of knowledge • tools • extraction of knowledge • identification of knowledge • information • integration of knowledge • knowledge • knowledge management

26. Summary Introduction • 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