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Peer–Mediated Distributed Knowledge Management M. Bonifacio, P. Bouquet, G. Mameli , M. Nori

Peer–Mediated Distributed Knowledge Management M. Bonifacio, P. Bouquet, G. Mameli , M. Nori. AMKM-2003 Stanford University March 24-26. KB. Traditional KM architectures: knowledge as content.

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Peer–Mediated Distributed Knowledge Management M. Bonifacio, P. Bouquet, G. Mameli , M. Nori

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  1. Peer–Mediated Distributed Knowledge Management M. Bonifacio, P. Bouquet, G. Mameli, M. Nori AMKM-2003 Stanford University March 24-26

  2. KB Traditional KM architectures: knowledge as content In the last 10 years, companies have invested huge amounts of money in order to manage knowledge adopting technological “carriers” (such as corporate knowledge portals or content management platforms). Conceptually, KM architectures are usually composed by: • Collaborative environments: in order to facilitate the generation of “raw knowledge” • Contribution workflows: in order to codify and standardize raw knowledge • KBs: in order to collect contents organized according to a corporate conceptual schema • EKP: in order to provide a single point of access for the members of different organizational units Enterprise knowledge portal Contribution WfS Assumption: Knowledge as content that can be centralized, standardized and controlled Collaborative tools

  3. Our idea: Knowledge as Context • Besides knowledge viewed as content, there are other forms of knowledge which are to be considered: • Interpretative Context: people know how to interpret what happens and generate a language to talk about things and events. Context is a mean to interpret content • Relational Context: people know who knows what and reduce complexity through trust and identity. Context as a mean to refer to other people. (People don’t believe in the paradigm of ideological sharing (all with all). They develop and use technologies if enable the sharing of knowledge within groups that evolve dynamically.) • Value emerges when content is positioned within its context: conceptual schemas, web of relations, business processes… Local “Knowledges” Global Knowledge Address to trusted experts Interpret other contexts Knowledge as content Context Interpret content Content

  4. A community internal web site Marketing Local Knowledge Context Content Communiy Communiy Sales Force Project Team 1 Communiy An individual’s file system directory or outlook folders A lotus notes team room Communiy Knowledge Network Sales R&D Complex organizations as made up of Knowledge Nodes Knowledge Nodes are social entities that “own” a local knowledge in terms of a content that has meaning within a context • Individuals • Communities • Teams

  5. Social and technological architecture of knowledge COORDINATION AUTONOMY The inconsintency of the technological architectures in current KM systems • From a technological point of view, current KM technologies are inconsistent with the very nature of knowledge and its social architecture  failure Social architecture of knowledge Technological architecture of knowledge KB Portal

  6. Organizational Actors Individual  K-Peer of a P2P network Group  K-Federation Roles Knowledge Seeker seeker module Knowledge Provider provider/federation module Broker (suggesting potential providers to seekers) brokering module From organization to the technological architecture:Actors and Roles in an Information Retrieval applications K-Peer I know! New Tool? Marketing she knows! Community K-Federation we know! Sales Force Project Team 1 Community Community KnowledgeNetwork Sales R&D

  7. Marketing Community Community Sales Force Project Team 1 Community Community Community Organization Sales R&D KEx objectives Supporting distributed and heterogeneous organizations in managing their knowledge processes, by technologically implementing the basic DKM concepts: • Autonomy by a set of document management functionalities • Coordination by a set of knowledge exchange functionalities

  8. System requirements  Our choices • We have implemented a P2P system where each peer must be able to: • Create and manage a knowledge representation • Context Markup Language • Context Editor • Context extraction tools • Declare its existence in the network • Advertisement • Discover other available / active peers on the network • Discovery module • Ping module • Discover, create and join to federation of peers • Advertisement • Discovery module • Membership module • Ask and receive information from them • Knowledge Exchange module • Provide information to them • Knowledge Exchange module • Propagation module • We characterized tools by semantic capabilities: • Semantic Matching Algorithms • Semantic Meaning Negotiation protocols

  9. Document Repository Context Normalization Context Repository Context Editor Context Enrichment Linguistic Resource K-Peer Provider Seeker Query Maker Federation Provider Communication Manager Semantic Query Solver GUI User Query Solver Matching Algorithm Query Propagation Discovery Lexical Query Solver Indexing Service P2P Services JXTA Protocols KEx high level architecture 2 1 3 0..n

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