© 2001 franz j. kurfess knowledge management techniques 1 cpe/csc 580: knowledge management dr....

© 2001 Franz J. Kurfess Knowledge Management Techniques 1

CPE/CSC 580: Knowledge Management

CPE/CSC 580: Knowledge Management

Dr. Franz J. Kurfess

Computer Science Department

Cal Poly


Course OverviewCourse 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


Overview Knowledge Management Techniques

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



Important Concepts and Terms

Chapter Summary


LogisticsLogistics

Introductions Course Materials

textbook handouts Web page CourseInfo/Blackboard System and Alternatives

Term Project Lab and Homework Assignments Exams Grading


Knowledge RepositoriesKnowledge Repositories

[KPMG 1998]


KM InfrastructureKM Infrastructure


KM InitiativesKM Initiatives


Pre-TestPre-Test


MotivationMotivation


ObjectivesObjectives


Corporate Memory (CM)Corporate Memory (CM)

definition attemptspurposeconceptsimplementation


Definition Attempts Corporate Memory

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]


Purpose Corporate MemoryPurpose Corporate Memory

capitalization of knowledgeintegration of resources and know-howcooperation 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]


Links in the Knowledge ChainLinks in the Knowledge Chain

list existing knowledgedetermine required knowledgedevelop new knowledgeallocate new and existing knowledgeapply knowledgemaintain knowledgedispose of knowledge

[Dieng et al. 1999]


Corporate Memory ManagementCorporate Memory Management

detection of needsconstruction of the corporate memorydiffusion of the corporate memoryuse of the corporate memoryevaluationmaintenance and evolution

[Dieng et al. 1999]


Corporate Memory Management Overview

Corporate Memory Management Overview

[Dieng et al. 1999]


Multidisciplinary Perspective on CMMultidisciplinary 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]


Corporate Memory TechniquesCorporate Memory Techniques

[Dieng et al. 1999]


Corporate Memory ExampleCorporate Memory Example

[Dieng et al. 1999]


Motivations for Establishing a CMMotivations 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]


Knowledge in OrganizationsKnowledge in Organizationsexplicit 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]


Types of Corporate MemoriesTypes 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]


CM NeedsCM 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]


Determination of CM NeedsDetermination 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]


CM ConstructionCM Construction

sourcesnon-computational CMdocument-based CMknowledge-based CMcase-based CMdistributed CMproject-centered CMcombinations of several techniques

[Dieng et al. 1999]


SourcesSources

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]


Non-computational CMNon-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]


Document-based CMDocument-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]


Knowledge-based CMKnowledge-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]


Case-based CMCase-based CM

utilizes case-based reasoningpast 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]


Distributed CMDistributed 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]


Project-centered CMProject-centered CMcaptures 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]


Combinations of Several TechniquesCombinations of Several Techniques

informal and formal knowledge representation methods

combination of paper-based and digital documentssemi-automatic extraction of knowledgecollaborative construction of “community knowledge”integration of existing components

libraries, data bases, case bases, document collections, multi-media collections, etc.

[Dieng et al. 1999]


Diffusion and Use of CMDiffusion 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]


Diffusion via Intranet/InternetDiffusion via Intranet/Internet

frequently centered around Web servershas some conceptual and technical limitations, but

substantial benefits confidentiality, security, reliability, distraction, etc.

[Dieng et al. 1999]


Knowledge and Information Retrieval

Knowledge and Information Retrieval

traditional index-based techniques are integrated in most approaches to CM

enhancements through advanced techniques ontologies collaborative filtering intelligent agents


EvaluationEvaluation

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]


Maintenance and EvolutionMaintenance and Evolution

should be based on the evaluation of the current situation

addition of new knowledgeremoval or modification of obsolete knowledgecoherence problemsscalabilityuser acceptance

should become a continuous activity

[Dieng et al. 1999]


Examples of CM MethodsExamples of CM Methods

CYGMAREXMKSMKAMM

[Dieng et al. 1999]


CYGMACYGMA

Cycle de Vie et Gestion des Métiers et des Applications, KADE-TEX

construction of a professional memory in manufacturingrelies 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]


REXREX

needs analysis and identificationconstruction of elementary pieces of experiencesconstruction of a computer-based representationimplementation through a software system

[Dieng et al. 1999]


MKSMMKSM

Method for Knowledge System Managementsystemic-based decision support methodviews knowledge assets as a complex systemmodels this complex system through different

perspectives syntactical, semantic, pragmatic

different components information (data processing) signification (task modelling) context (activity modelling)

[Dieng et al. 1999]


KAMMKAMM

[Knowledge Associates 2000]


KAMM ArchitectureKAMM Architecture

[Knowledge Associates 2000]


Knowledge Technology FrameworkKnowledge Technology Framework

identifies key KM activities and related knowledge[oriented techniques and tools

personalizationcodificationdiscoverycreation/innovationcapture/monitor

[Milton et al. 1999]


Knowledge TechnologyKnowledge Technology

(Key: P"Person, K1"Knowledge 1echnology, I1"Information 1echnology)


PersonalizationPersonalization

sharing knowledge through person-to-person contacts

tools for more effective communication email, message boards, chatrooms, personal ontologies



CodificationCodification

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



DiscoveryDiscovery

searching and retrieving knowledge from repositories and data bases

tools and techniques from information retrieval, knowledge-based systems, natural language processing search engines, ontologies



Creation/innovationCreation/innovation

generation of new knowledgetools and techniques from cognitive science,

psychology brainstorming support, creativity assistance

mainly a human endeavor



Capture/MonitorCapture/Monitor

capturing knowledge as people work on their normal task

tools and techniques from Human-Computer Interaction, AI audit trails, case collections



KM FrameworkKM Framework

[Macintosh et al. 1999]


KM ProcessesKM Processes

[Macintosh et al. 1999]


PROMOTE ArchitecturePROMOTE Architecture

[Karagiannis & Telesko, 2000]


PROMOTE FrameworkPROMOTE Framework

[Karagiannis & Telesko, 2000]


Organizational Memory ContextOrganizational Memory Context

[Abecker et al. 1998b]


Context-Sensitive

Knowledge Supply

Context-Sensitive

Knowledge Supply



Integration of OntologiesIntegration of Ontologies



Knowledge Task SupportKnowledge Task Support



Related Research AreasRelated Research Areas



Developing a KnowledgeManagement Technology

An Encompassing View on the Projects of the

Knowledge Management Group at DFKI Kaiserslautern

Developing a KnowledgeManagement Technology

An Encompassing View on the Projects of the

Knowledge Management Group at DFKI KaiserslauternMichael Sintek, Andreas Abecker, Ansgar Bernardi

German Research Center for Artificial Intelligence

Kaiserslautern, Germany[Abecker et al. 1998b]


OverviewOverview

requirements and approaches to support KM infrastructures for organizations; related research fields

KnowMore active knowledge supply finished

Know-Net collaboration ongoing

FRODO distribution, framework current

MOTIVE 3D access planned

summary: we propose a rich, modular KM middleware as a solid basis for engineering intranet-based KM solutions

Development of Knowledge Management technology of theKnowledge Management Group at DFKI Kaiserslautern



Knowledge is an Important Productivity Factor for Organizations

Knowledge is an Important Productivity Factor for Organizationsbesides 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.



Organizations Have Serious Problems in Managing Their

Corporate Knowledge

Organizations Have Serious Problems in Managing Their

Corporate Knowledge

Various fields of computer science tackle some of these knowledge problems.

KnowledgeProblemsDocumentation

AvailabilityAwareness

Distribution

Resources

Multiple Formats

Multiple Views

Accessibility Discovery

Acquisition



Resarch Fields Related to KMResarch Fields Related to KMGroupware, Workflow, CSCW

collaboration of individuals and departmentsDocument management, retrieval, and filtering systems

most of the available abstract, strategic knowledge written down in text-based documents

often advertised as KM solutionsArtificial Intelligence

formal ontologies data mining case bases expert systems

We strive for a new quality of knowledge systems by integrating all these areas.



KnowMore—Knowledge Management for Learning

Organizations

KnowMore—Knowledge Management for Learning

Organizationsbasic 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.



The KnowMore System ArchitectureThe KnowMore System Architecture



Know-Net—Knowledge Management with Intranet

Technologies

Know-Net—Knowledge Management with Intranet

Technologiesfunded by the European Commission within the “IT for

learning and training industry” programintegrate groupware functionalities with AI methods enabling

the handling of knowledge objectsbased 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.



Know-Net: Collaborative AspectsKnow-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



The Know-Net Intranet- and Agent-Based System Architecture

The Know-Net Intranet- and Agent-Based System Architecture



FRODO—A Scalable OM Framework for Evolutionary Growth

(future work)

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 inferenceFRODO: 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 problemcommunicating and cooperating services

We propose a rich, modular KM middleware as a solid basis for engineering intranet-based KM solutions.



The FRODO KM Middleware Will Exploit Various Notions of AgentsThe FRODO KM Middleware Will Exploit Various Notions of Agentsdigital 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



A Sample Instantiation of the FRODO OM Framework

A Sample Instantiation of the FRODO OM Framework



MOTIVE—Fostering Individual Users’ Motivation for Accessing

Online Learning & Training Resources (planned)

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) systemsaddresses 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.



MOTIVE Adds Access to L&T OMs Through 3D Knowledge Portal

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.



SummarySummary

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



Reference [Kearns 00]Reference [Kearns 00]

[Dieng et al. 1999]


Reference [Sommerville 01] Reference [Sommerville 01]

[Sommerville 01]

[Sommerville 01]


Post-TestPost-Test


ReferencesReferences [Abecker et al. 1998] Andreas Abecker, Ansgar Bernardi, Knut Hinkelmann, Otto Kühn, Michael Sintek.

Techniques for Organizational Memory Systems. Technical Report D-98-02, Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI), 1998.

[Abecker et al. 1998b] Andreas Abecker, Ansgar Bernardi, Knut Hinkelmann, Otto Kühn, Michael Sintek. Toward a Technology for Organizational Memories. IEEE Intelligent Systems, vol. 13, no.3, pp. 40-48, 1998.

[Dieng et al. 1999] Rose Dieng, Olivier Corby, Alain Giboin and Myriam Ribiere, Methods and Tools for Corporate Memory. Int. J. Human-Computer Studies, no. 51, pp. 567-598, 1999.

[Karagiannis & Telesko, 2000] Dimitris Karagiannis and Rüdiger Telesko. The EU-Project PROMOTE: A Process-oriented Approach forKnowledge Management. Proc. of the Third Int. Conf. on Practical Aspects of Knowledge Management (PAKM2000) Basel, Switzerland, 30-31 Oct. 2000, (U. Reimer, ed.).

[KPMG 1998] KPMG Management Consulting Knowledge Management Research Report 1998. [Macintosh et al 1999] Ann Macintosh, Ian Filby, and John Kingston. Knowledge Management Techniques -

Teaching and Dissemination Concepts. Int. J. Human-Computer Studies, no. 51, pp. 549-566, 1999. [Milton et al. 1999] Nick Milton, Nigel Shadbolt, Hugh Cottam, and Mark Hammersly. Towards a Knowledge

Technology for Knowledge Management. Int. J. Human-Computer Studies, no. 51, pp. 615-641, 1999 [Sintek et al. 1998] Michael Sintek, Andreas Abecker, Ansgar Bernardi. Developong a Knowledge

Management Technology. Presentation at WET ICE KMN ‘99, Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI), 1999; www.dfki.uni-kl.de/~simtek/.


Important Concepts and TermsImportant 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


Summary Chapter-TopicSummary Chapter-Topic

© 2001 franz j. kurfess knowledge management techniques 1 cpe/csc 580: knowledge management dr....

Documents

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u important concepts

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