Source: MS

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Developing a KnowledgeManagement TechnologyAn
Encompassing View on the Projects of
theKnowledge Management Group at DFKI
Kaiserslautern

• Michael Sintek, Andreas Abecker, Ansgar Bernardi
• German Research Center for Artificial
  Intelligence
• Kaiserslautern, Germany

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Overview
Development of Knowledge Management technology of
the Knowledge Management Group at DFKI
Kaiserslautern
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
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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.
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Organizations Have Serious Problems in Managing
Their Corporate Knowledge
Distribution
Discovery
Accessibility
Acquisition
Resources
KnowledgeProblems
Multiple Views
Documentation
Multiple Formats
Awareness
Availability
Various fields of computer science tackle some of
these knowledge problems.
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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.
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KnowMoreKnowledge 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.
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The KnowMore System Architecture
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Know-NetKnowledge 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.
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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

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

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A Sample Instantiation of the FRODO OM Framework
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MOTIVEFostering 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 (LT) systems
• addresses users motivation important driving
  factor is social interaction
• MOTIVE proposes an environment that wraps LT
  tools and content together with peoples
  interactions
• virtual representation of the LT 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.

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MOTIVE Adds Access to LT OMs Through 3D
Knowledge Portal

• the LT 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 LT
  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.
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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