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 Recognizing the nature, source and principles of knowledge is essential to realizing effective machine-enabled knowledge services Professional Knowledge Commonsense Expert Knowledge

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

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

6. What is the Knowledge Grid? the Knowledge Gridthe 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 XML, XMLS RDF, RDFS OWLRIF Reasoning Applications Interconnection Semantics Advanced Applications

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. 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 Ontology Epistemology Understand each other ？

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

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 Flow Self-organizes virtual teams Knowledge Information

13. Knowledge Flows through Semantic, Trust, Selfish and Unselfish Spaces Link network Trust Space Selfish SpaceUnselfish Space Knowledge Space Semantic space

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 Internet Technologies Data ModelGrid Semantic Web Web Services Information Processing TechnologiesSystem Methodology AIThe Knowledge Grid New Organization ModelNew Computing Model Principles of Relevant Disciplines New Software Methodology

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. More than 900 caves Over 1500 years ’ history Wall-paintings, Statues, Calligraphies Dunhuang Culture Grid Dunhuang Culture Grid

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

21. CaveGrid400 CaveGrid 2 CaveGrid 3 CaveGrid 4 CaveGrid 1 Researchers Visitors Cave Makers Information / Knowledge Grid Natural Cave Semantic Grid

22. Thank You