1. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 1 CPE/CSC 580: Knowledge Management Dr. Franz J. Kurfess Computer Science Department Cal Poly

2. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 2 Course Overview  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

3. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 3 Overview Knowledge Management Techniques  Motivation  Objectives  Evaluation Criteria  Chapter Introduction  Review of relevant concepts  Overview new topics  Terminology  Topic 1  Subtopic 1.1  Subtopic 1.2  Topic 2  Subtopic 2.1  Subtopic 2.2  Topic 3  Subtopic 3.1  Subtopic 3.2  Important Concepts and Terms  Chapter Summary

4. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 4 Logistics  Introductions  Course Materials  textbook  handouts  Web page  CourseInfo/Blackboard System and Alternatives  Term Project  Lab and Homework Assignments  Exams  Grading

5. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 5 Knowledge Repositories [KPMG 1998]

6. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 6 KM Infrastructure

7. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 7 KM Initiatives

8. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 8 Pre-Test

9. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 9 Motivation

10. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 10 Objectives

11. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 11 Evaluation Criteria

12. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 12 Corporate Memory (CM)  definition attempts  purpose  concepts  implementation

13. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 13 Definition Attempts Corporate Memory  explicit, disembodied, persistent representation of knowledge and information in an organization [Van Heijst, van der Spek and Kruizinga 1996]  may include knowledge on products, production processes, clients, marketing strategies, plans, strategic goals, etc.  the collective data and knowledge resources of a company [Nagendra Prasad and Plaza 1996]  may include project experiences, problem-solving expertise, design rationale, etc. [Dieng et al. 1999]

14. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 14 Purpose Corporate Memory  capitalization of knowledge  integration of resources and know-how  cooperation through effective communication and active documentation “the right knowledge to the right person at the right time and at the right level” [Dieng et al. 1999]

15. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 15 Links in the Knowledge Chain  list existing knowledge  determine required knowledge  develop new knowledge  allocate new and existing knowledge  apply knowledge  maintain knowledge  dispose of knowledge [Dieng et al. 1999]

16. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 16 Corporate Memory Management  detection of needs  construction of the corporate memory  diffusion of the corporate memory  use of the corporate memory  evaluation  maintenance and evolution [Dieng et al. 1999]

17. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 17 Corporate Memory Management Overview [Dieng et al. 1999]

18. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 18 Multidisciplinary Perspective on CM  technological (computer science, information technology)  concentrate on technical and implementation aspects  may neglect requirements and constraints of systems in practical use  organizational (CKO)  emphasize the role of CM in an organization  may overlook technological problems, or underestimate efforts needed for implementation [Dieng et al. 1999]

19. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 19 Corporate Memory Techniques [Dieng et al. 1999]

20. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 20 Corporate Memory Example [Dieng et al. 1999]

21. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 21 Motivations for Establishing a CM  avoid knowledge loss  departure, retirement, change of roles of employees  exploit past experience  cumulative technical know-how  successful and failed projects  utilize collective knowledge for strategic purposes  detection of new opportunities  reaction to changes  improve knowledge exchange and communication  establish venues for sharing information  improve learning  integrate knowledge from different areas  cross-disciplinary knowledge exchange [Dieng et al. 1999]

22. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 22 Knowledge in Organizations  explicit knowledge  specific know-how to design, build, sell and support products and services  tacit knowledge  individual and collective skills enabling the organization to act, adapt, and evolve  tangible knowledge components  data, procedures, plans, models, algorithms, documents of analysis and synthesis  intangible knowledge components  abilities, professional skills, private knowledge, organizational culture, history of the organization, contexts of decisions, etc. [Dieng et al. 1999]

23. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 23 Types of Corporate Memories  technical memory  know-how of the employees about technical aspects  organizational memory  knowledge about the internal structure of an organization  project memories  lessons and experiences from past projects  individual memories  status, know-how, activities, relationships of individual employees  internal vs. external memory  indicates the source of relevant knowledge and information [Dieng et al. 1999]

24. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 24 CM Needs  organization is also a knowledge production unit  not necessarily as primary purpose  depends on size, type, and organizational scheme of the organization  e.g. distributed network of consultants  needs of individual users vs. organizational needs  detecting the “right” needs can be difficult  target users, domains, tasks, situations, knowledge [Dieng et al. 1999]

25. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 25 Determination of CM Needs  stakeholder-centered  influenced by the members of the community of people affected by or invested in the system  requirements analysis  early involvement of stakeholders is critical and feasible  most stakeholders are internal to the organization, and many are motivated most solutions are adaptations or evolutions of previous systems  CSCW, KBMS, MIS,... [Dieng et al. 1999]

26. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 26 CM Construction  sources  non-computational CM  document-based CM  knowledge-based CM  case-based CM  distributed CM  project-centered CM  combinations of several techniques [Dieng et al. 1999]

27. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 27 Sources  human sources  domain experts, experienced specialists, people with organizational memories  physical documents  printed documents, notes, design artifacts, products, tools, etc.  digital documents  reports, technical documentation, design artifacts, email, case libraries, dictionaries, sketches, etc. [Dieng et al. 1999]

28. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 28 Non-computational CM  establishment of paper-based knowledge repository  existing documents  generation of new documents  synthesis of knowledge not explicit in reports, technical documentation, etc.  improve strategies and structural aspects of the organization  systematic generation of knowledge in an organization  may be the predecessor to a digital CM [Dieng et al. 1999]

29. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 29 Document-based CM  comprises all existing documents in an organization  may be in paper-based or digital form  organizes the collection in a systematic way  indexing  interface to manage documents  preparation, storage, retrieval, processing, evaluation, distribution [Dieng et al. 1999]

30. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 30 Knowledge-based CM  based on the elicitation and explicit modeling of knowledge from experts  may use a formal knowledge representation framework  this is often quite expensive  serves as an assistant to human “knowledge workers”  different from traditional expert systems  their goal is the automation of a particular task [Dieng et al. 1999]

31. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 31 Case-based CM  utilizes case-based reasoning  past experiences are collected in a (semi-)formal representation mechanism  allows the comparison of “cases”  the assumption is that new problems can often be solved by looking up solutions to previous problems  helps with the concentration of expertise around specific cases  continuous evolution of the CM through the continuous addition of new cases [Dieng et al. 1999]

32. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 32 Distributed CM  emphasis on collaboration and knowledge-sharing across traditional boundaries  geographically distributed persons/groups  structurally separated entities  common tasks, domains  essential for virtual organizations  teams or people collaborate on-line [Dieng et al. 1999]

33. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 33 Project-centered CM  captures the relevant knowledge accumulated while working on a project  discussions, arguments, decisions, compromises, etc.  important aspects  represent and reconcile perspectives of different stakeholders  changes of priorities in the project  communication of decision rationales  recovery of insights and solutions from past scenarios  “re-inventing the wheel”  example  issue-based information system (IBIS) [Rittel 1972] [Dieng et al. 1999]

34. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 34 Combinations of Several Techniques  informal and formal knowledge representation methods  combination of paper-based and digital documents  semi-automatic extraction of knowledge  collaborative construction of “community knowledge”  integration of existing components  libraries, data bases, case bases, document collections, multi-media collections, etc. [Dieng et al. 1999]

35. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 35 Diffusion and Use of CM  diffusion modes  knowledge attic  archive that can be consulted when needed  collection and diffusion are passive  knowledge sponge  active collection, passive diffusion  knowledge publisher  relevant elements are distributed to users  passive collection, active distribution  knowledge pump  specific roles or methods for collection of relevant knowledge  active collection and active diffusion [Dieng et al. 1999]

36. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 36 Diffusion via Intranet/Internet  frequently centered around Web servers  has some conceptual and technical limitations, but substantial benefits  confidentiality, security, reliability, distraction, etc. [Dieng et al. 1999]

37. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 37 Knowledge and Information Retrieval  traditional index-based techniques are integrated in most approaches to CM  enhancements through advanced techniques  ontologies  collaborative filtering  intelligent agents

38. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 38 Evaluation  financial perspective  improve the bottom-line of the organization  may be difficult to measure  organizational perspective  work environment  employee satisfaction  technical perspective  transfer of know-how some effects may not be direct consequences of the CM, but side-effects of its introduction or use [Dieng et al. 1999]

39. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 39 Maintenance and Evolution  should be based on the evaluation of the current situation  addition of new knowledge  removal or modification of obsolete knowledge  coherence problems  scalability  user acceptance should become a continuous activity [Dieng et al. 1999]

40. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 40 Examples of CM Methods  CYGMA  REX  MKSM  KAMM [Dieng et al. 1999]

41. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 41 CYGMA Cycle de Vie et Gestion des Métiers et des Applications, KADE-TEX  construction of a professional memory in manufacturing  relies on six categories of industrial knowledge  singular knowledge  terminological knowledge (dictionary)  structural knowledge (ontology, factual knowledge base)  behavioral knowledge  strategic knowledge  operational knowledge [Dieng et al. 1999]

42. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 42 REX  needs analysis and identification  construction of elementary pieces of experiences  construction of a computer-based representation  implementation through a software system [Dieng et al. 1999]

43. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 43 MKSM Method for Knowledge System Management  systemic-based decision support method  views knowledge assets as a complex system  models this complex system through different perspectives  syntactical, semantic, pragmatic  different components  information (data processing)  signification (task modelling)  context (activity modelling) [Dieng et al. 1999]

44. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 44 KAMM [Knowledge Associates 2000]

45. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 45 KAMM Architecture [Knowledge Associates 2000]

46. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 46 Knowledge Technology Framework identifies key KM activities and related knowledge[oriented techniques and tools  personalization  codification  discovery  creation/innovation  capture/monitor [Milton et al. 1999]

47. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 47 Knowledge Technology (Key: P"Person, K1"Knowledge 1echnology, I1"Information 1echnology)

48. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 48 Personalization  sharing knowledge through person-to-person contacts  tools for more effective communication  email, message boards, chatrooms, personal ontologies [Milton et al. 1999]

49. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 49 Codification  capturing existing knowledge and placing it in repositories  tools and techniques for knowledge representation  generic models  rules, frames, case-based reasoning,...  specialized techniques  task- or domain-specific [Milton et al. 1999]

50. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 50 Discovery  searching and retrieving knowledge from repositories and data bases  tools and techniques from information retrieval, knowledge-based systems, natural language processing  search engines, ontologies [Milton et al. 1999]

51. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 51 Creation/innovation  generation of new knowledge  tools and techniques from cognitive science, psychology  brainstorming support, creativity assistance  mainly a human endeavor [Milton et al. 1999]

52. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 52 Capture/Monitor  capturing knowledge as people work on their normal task  tools and techniques from Human-Computer Interaction, AI  audit trails, case collections [Milton et al. 1999]

53. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 53 KM Framework [Macintosh et al. 1999]

54. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 54 KM Processes [Macintosh et al. 1999]

55. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 55 PROMOTE Architecture [Karagiannis & Telesko, 2000]

56. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 56 PROMOTE Framework [Karagiannis & Telesko, 2000]

57. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 57

58. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 58 Organizational Memory Context [Abecker et al. 1998b]

59. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 59 Context- Sensitive Knowledge Supply [Abecker et al. 1998b]

60. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 60 Integration of Ontologies [Abecker et al. 1998b]

61. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 61 Knowledge Task Support [Abecker et al. 1998b]

62. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 62 Related Research Areas [Abecker et al. 1998b]

63. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 63 Developing a Knowledge Management Technology An Encompassing View on the Projects of the Knowledge Management Group at DFKI Kaiserslautern Michael Sintek, Andreas Abecker, Ansgar Bernardi German Research Center for Artificial Intelligence Kaiserslautern, Germany [Abecker et al. 1998b]

64. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 64 Overview requirements and approaches to support KM infrastructures for organizations; related research fields KnowMoreactive knowledge supplyfinished Know-Netcollaborationongoing FRODOdistribution, frameworkcurrent MOTIVE3D accessplanned summary: we propose a rich, modular KM middleware as a solid basis for engineering intranet-based KM solutions Development of Knowledge Management technology of the Knowledge Management Group at DFKI Kaiserslautern [Abecker et al. 1998b]

65. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 65 Knowledge is an Important Productivity Factor for Organizations  besides labor, capital, and land, knowledge has been recognized as an important productivity factor  knowledge is stored in individual brains or implicitly encoded and hidden in organizational processes, documents, services, and systems KM is concerned with discovery, acquisition, creation, dissemination, and utilization of knowledge. [Abecker et al. 1998b]

66. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 66 Organizations Have Serious Problems in Managing Their Corporate Knowledge Various fields of computer science tackle some of these knowledge problems. Knowledge Problems Documentation Availability Awareness Distribution Resources Multiple Formats Multiple Views Accessibility Discovery Acquisition [Abecker et al. 1998b]

67. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 67 Resarch Fields Related to KM  Groupware, Workflow, CSCW  collaboration of individuals and departments  Document management, retrieval, and filtering systems  most of the available abstract, strategic knowledge written down in text-based documents  often advertised as KM solutions  Artificial Intelligence  formal ontologies  data mining  case bases  expert systems We strive for a new quality of knowledge systems by integrating all these areas. [Abecker et al. 1998b]

68. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 68 KnowMore—Knowledge Management for Learning Organizations  basic research project funded by German government  central idea: access to multiple heterogeneous knowledge sources  enabled through comprehensive knowledge description using several formal ontologies (information, domain, enterprise ontology)  active information delivery integrated into business processes  explicit representation of context In KnowMore, knowledge can be viewed as information linked into the application context. [Abecker et al. 1998b]

69. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 69 The KnowMore System Architecture [Abecker et al. 1998b]

70. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 70 Know-Net—Knowledge Management with Intranet Technologies  funded by the European Commission within the “IT for learning and training industry” program  integrate groupware functionalities with AI methods enabling the handling of knowledge objects  based on Knowledger™ suite (Lotus Notes™ application from Knowledge Associates) and intelligent agents (DFKI)  intranet- and agent-based knowledge platform:  codification, mapping, sharing, and reuse of explicit knowledge in multimedia content  corporate knowledge ontologies  intelligent navigation, searching, filtering In addition to a KnowMore-like knowledge platform, collaborative aspects play an important role. [Abecker et al. 1998b]

71. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 71 Know-Net: Collaborative Aspects  collaborative tools supporting communities of practice at the team level to facilitate the creation of shared memories and interpretative context  real-time group discussions/meetings  project-based bulletin boards and forums  on-line topical conferences with threading features and interactive expertise databases  Know-Net mainly exploits the collaboration and coordination technology provided by Lotus Notes and add-on products like Sametime [Abecker et al. 1998b]

72. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 72 The Know-Net Intranet- and Agent- Based System Architecture [Abecker et al. 1998b]

73. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 73 FRODO—A Scalable OM Framework for Evolutionary Growth (future work)  basic research project funded by German government, successor project of KnowMore  KnowMore: global set of ontologies, centralized inference  FRODO: conjointly use knowledge from several independent knowledge sources  legacy databases  independently introduced partial OMs based on specific ontologies  external knowledge sources (with own ontologies)  ontology mapping problem  communicating and cooperating services We propose a rich, modular KM middleware as a solid basis for engineering intranet-based KM solutions. [Abecker et al. 1998b]

74. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 74 The FRODO KM Middleware Will Exploit Various Notions of Agents  digital reference and acquisition librarians  know their respective knowledge source and organization principles  know how to effectively access, search, maintain the knowledge  wrappers, mediators, ontologists, knowledge brokers  add intelligent interfaces to legacy systems  make sources accessible to higher-level inferences  document analysis and information extraction specialists  allow transition between informal and formal representations  task/process agents, knowledge push/pull mechanisms  manage workflow enactment  realize context-sensitive information supply [Abecker et al. 1998b]

75. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 75 A Sample Instantiation of the FRODO OM Framework [Abecker et al. 1998b]

76. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 76 MOTIVE—Fostering Individual Users’ Motivation for Accessing Online Learning & Training Resources (planned)  will be submitted to the EU 5th framework  online front-end to electronic learning and training (L&T) systems  addresses users’ motivation; important driving factor is social interaction  MOTIVE proposes an environment that wraps L&T tools and content together with people’s interactions  virtual representation of the L&T environment:  workspace with 3D representation of the organization and of knowledge assets  avatars associated to users  wizard agents with specific roles for promoting available material  support for social processes: events organization, social places (café) etc. [Abecker et al. 1998b]

77. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 77 MOTIVE Adds Access to L&T OMs Through 3D Knowledge Portal  the L&T contents is accompanied by a KnowMore/FRODO-like knowledge meta-level based upon various ontologies  XML as upcoming standard will be used for this knowledge representation task  a 3D knowledge portal wraps these ontologies to provide a highly motivating access to the L&T resources  thus, the MOTIVE 3D knowledge access can be viewed as an additional, but highly user- friendly information retrieval aspect of the general KM scenario In general, 3D spaces can be used to replace legacy information retrieval, knowledge acquisition, and workflow frontends of OM systems. [Abecker et al. 1998b]

78. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 78 Summary In our view, KM technology is a combination of:  distributed, heterogeneous knowledge sources  various formal ontologies (information, domain, enterprise)  knowledge meta-descriptions  informal-formal transitions  workflow, active support, context  collaboration  framework, middleware, agents  user-friendly access through 3D spaces [Abecker et al. 1998b]

79. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 79 Post-Test

80. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 80 Evaluation  Criteria

81. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 81 References

82. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 82 Important Concepts and Terms  natural language processing  neural network  predicate logic  propositional logic  rational agent  rationality  Turing test  agent  automated reasoning  belief network  cognitive science  computer science  hidden Markov model  intelligence  knowledge representation  linguistics  Lisp  logic  machine learning  microworlds

83. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 83 Summary KM Techniques

84. © 2001-2005 Franz J. Kurfess Knowledge Management Techniques 84