Transcript Document 7311333

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?
 What is the Knowledge Grid ?
 What is the Semantic Grid ?
Knowledge
Knowledge in nature is a product of society
 Internet offers great social opportunities for
knowledge generation and sharing
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Professional
Knowledge
Commonsense
Expert
Knowledge
Recognizing the nature, source and principles of knowledge is
essential to realizing effective machine-enabled knowledge services
The Knowledge Grid
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Worldwide knowledge creation, evolution,
inheritance, and sharing in a world of
humans, roles and machines
Semantics, Knowledge and Grid
Knowledge
Knowledge Grid
Basis for
knowledge
sharing
Computing
Internet
Semantics
Semantic Web
Grid
Semantic Grid
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
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

Semantic feature
– It works on a interconnection semantic
overlay
Interconnection
Semantics
– Self-adaptive like ecosystem
Advanced Applications
Applications
Reasoning
RIF OWL
RDF, RDFS
XML, XMLS
Distinctive Characteristics of the
Knowledge Grid

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Single semantic entry point access to
worldwide knowledge
Intelligently clustered, fused distributed
knowledge
Single semantic image
Worldwide complete knowledge service
Dynamic evolution of knowledge
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
Understand each other？
Epistemology
Epistemology
Synergy Normalization and
Autonomy

Normalization
– Correctness
Knowledge Grid Applications
Normalized Semantic Model
– Accuracy
– e.g., Relational Data Model

RSM
Autonomy
– Equality
– Scalability
P2P networking
RSM
H.Zhuge, Resource Space Grid: Model, Method and Platform, Concurrency and
Computation: Practice and Experience, 16(14) (2004)1385-1413
Adopt System Methodology

Create a dissipative structure to selfupgrading
– 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
Knowledge Flow

Self-organizes virtual teams
Knowledge
Information
Knowledge
Flows through Semantic, Trust, Selfish and
Unselfish Spaces
Knowledge Space
Selfish Space
Unselfish Space
Trust Space
Semantic space
Link network
Principle
Integrity and uniformity
 Hierarchical principle
 Open principle
 Self-organization principle
 Competition and
cooperation
 Optimization principle
 Sustainable development

Research Issues

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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
Technologies
New Software Methodology
Principles of Relevant Disciplines
New Organization Model
AI
New Computing Model
The Knowledge Grid
Information Processing Technologies
Data Model
Grid
System Methodology
Semantic Web
Internet Technologies
Web Services
From Micro to Macro

Micro Knowledge Grid
– For personal knowledge management
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Team Knowledge Grid
– For team knowledge management and sharing
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Macro Knowledge Grid
– For global knowledge sharing
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A macro Knowledge Grid is more powerful
than the sum of micro Knowledge Grids
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
Dunhuang Culture Grid
More than 900 caves
Over 1500 years’ history
Wall-paintings, Statues, Calligraphies
Cave Content Space
Content
Links
Link
semantics
Semantic
Link
Dynasty
Cave
Resource
Type
Classification
semantics
Artifact
Type
Visitors
Cave Makers
Researchers
Information / Knowledge Grid
CaveGrid
CaveGrid
2
3
Natural Cave Semantic Grid
CaveGrid
CaveGrid
1
4
CaveGrid400
Thank You