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The Knowledge Grid Methodology  Concepts, Principles and Practice

The Knowledge Grid Methodology  Concepts, Principles and Practice. Hai Zhuge China Knowledge Grid Research Group Chinese Academy of Sciences. Questions. What is the semantics in the future interconnection environment? What is the knowledge in the future interconnection environment?

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The Knowledge Grid Methodology  Concepts, Principles and Practice

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  1. The Knowledge Grid MethodologyConcepts,Principles and Practice Hai Zhuge China Knowledge Grid Research Group Chinese Academy of Sciences

  2. Questions • What is the semantics in the future interconnection environment? • What is the knowledge in the future interconnection environment? • What is the Knowledge Grid ? • What is the Semantic Grid ?

  3. Knowledge • Knowledge in nature is a product of society • Internet offers great social opportunities for knowledge generation and sharing Professional Knowledge Expert Knowledge Commonsense Recognizing the nature, source and principles of knowledge is essential to realizing effective machine-enabled knowledge services

  4. The Knowledge Grid • Worldwide knowledge creation, evolution, inheritance, and sharing in a world of humans, roles and machines

  5. Knowledge Grid Internet Semantic Web Semantic Grid Semantics, Knowledge and Grid Knowledge Basis for knowledge sharing Computing Grid Semantics

  6. What is the Knowledge Grid? • An intelligent and sustainable Internet application environment that enables people or roles to effectively capture, publish, share and manage explicit knowledge resources. It • provides on-demand services to support innovation, teamwork, problem-solving and decision making • incorporates epistemology and ontology to reflect human cognition characteristics • exploits social, ecological and economic principles • adopts the techniques and standards developed during work toward the next-generation web

  7. Features of Knowledge Grid • Virtual feature • The Grid is not the unique underlying infrastructure • Social feature • An artificial environment can only be effective when it works harmoniously with its society • Adaptive feature • Self-adaptive like ecosystem • Semantic feature • It works on a interconnection semantic overlay Advanced Applications Interconnection Semantics Applications Reasoning RIF OWL RDF, RDFS XML, XMLS

  8. Distinctive Characteristics of the Knowledge Grid • Single semantic entry point access to worldwide knowledge • Intelligently clustered, fused distributed knowledge • Single semantic image • Worldwide complete knowledge service • Dynamic evolution of knowledge

  9. Ontology Understand each other？ Epistemology Epistemology Synergy Epistemology and Ontology • Ontology • Concerns: what is, and the kinds and structures of the objects, properties and relations in every area of reality • Reflects consensus • Epistemology • Reflects differences

  10. P2P networking RSM Synergy Normalization and Autonomy • Normalization • Correctness • Accuracy • e.g., Relational Data Model • Autonomy • Equality • Scalability Knowledge Grid Applications Normalized Semantic Model RSM H.Zhuge, Resource Space Grid: Model, Method and Platform, Concurrency and Computation: Practice and Experience, 16(14) (2004)1385-1413

  11. Adopt System Methodology • Create a dissipative structure to self-upgrading • H.Zhuge, Eco-Grid: A Harmoniously Evolved Interconnection Environment, Communications of the ACM, Sept. 2004 • Hypercycle: a natural self-organization • knowledge are processed by and flows through individuals to organize and self-evolve • H.Zhuge, Discovery of Knowledge Flow in Science, Communications of the ACM, 2006

  12. Knowledge Information Knowledge Flow • Self-organizes virtual teams

  13. Knowledge Space Selfish Space UnselfishSpace Trust Space Semantic space KnowledgeFlows through Semantic, Trust, Selfish and Unselfish Spaces Link network

  14. Principle • Integrity and uniformity • Hierarchical principle • Open principle • Self-organization principle • Competition and cooperation • Optimization principle • Sustainable development

  15. Research Issues • Theories, models, methods and mechanisms for knowledge capture and representation • Knowledge display and creation • Propagation and management of knowledge within virtual organization • Knowledge organization, evaluation, refinement and derivation • Knowledge integration • Abstraction • Scalable network platform

  16. Technologies New Software Methodology Principles of Relevant Disciplines New Organization Model New Computing Model AI The Knowledge Grid Information Processing Technologies System Methodology Data Model Grid Web Services Semantic Web Internet Technologies

  17. From Micro to Macro • Micro Knowledge Grid • For personal knowledge management • Team Knowledge Grid • For team knowledge management and sharing • Macro Knowledge Grid • For global knowledge sharing • A macro Knowledge Grid is more powerful than the sum of micro Knowledge Grids

  18. Test Criteria • Effective knowledge service • e.g., response time • Quality of knowledge services • Self-evolution ability • whether services could be improved during use • On average, a Knowledge Grid should perform better than other systems in 70% of tests

  19. Dunhuang Culture Grid More than 900 cavesOver 1500 years’ historyWall-paintings, Statues, Calligraphies

  20. Semantic Link Cave Resource Type Cave Content Space Content Links Link semantics Dynasty Classification semantics Artifact Type

  21. Visitors Information / Knowledge Grid Cave Makers Researchers CaveGrid2 CaveGrid3 CaveGrid1 Natural Cave Semantic Grid CaveGrid4 CaveGrid400

  22. Thank You

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