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Knowledge Management in Geodise

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Concept mark-up in Protocol Editor. Concept hierarchy in ... Prot g & OilEd Editor. Representation. DAML OIL & CLIPS. Deliverables. EDSO domain ontology ... – PowerPoint PPT presentation

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Title: Knowledge Management in Geodise


1
Knowledge Managementin Geodise
Geodise Knowledge Management Team Liming Chen,
Barry Tao, Colin Puleston, Paul Smart University
of Southampton University of Manchester
Epistemics Ltd.

2
Overview
  • Geodise needs knowledge management
  • Knowledge acquisition and modelling
  • Grid-oriented knowledge management
  • Knowledge applications in Geodise
  • Creating semantic content
  • Workflow management
  • Knowledge-based advice
  • EDSO component management
  • Summary and future work

3
Geodise MeetsKnowledge Management (KM)- put KM
in context -
4
GEODISE
Geodise will provide grid-based seamless access
to an intelligent knowledge repository, a
state-of-the-art collection of optimisation and
search tools, industrial strength analysis codes,
and distributed computing data resources
5
The Problems the Solutions
  • Geodise Flexible and secure sharing of
    resources on the Grid to carry out Engineering
    Design Search and Optimisation (EDSO)
  • Component level - EDSO tasks such as problem
    setup, mesh generation, code analysis, DOE, RSM,
    Optimisation, etc.
  • Process level EDSO workflow for problem-solving
  • Grid level - resource accessibility, sharing,
    reuse, interoperability, etc.
  • The problems
  • From infosmog to shared, semantically enriched,
    well-structured knowledge repositories
  • From standalone KBSs to knowledge services on the
    Grid
  • The solutions
  • Ontology conceptual backbone for resource
    sharing and creating semantic content
  • Knowledge management knowledge delivery, reuse
    and decision-making support

6
The Approach to Knowledge Management
Knowledge Acquisition
Validation
Knowledge Modelling
Knowledge Publishing
Application Domain
Application Systems
Knowledge Use Re-use
Knowledge Support Via KBSs
Knowledge Maintenance
Application Scenarios User Requirements
7
Knowledge Acquisition and Modelling- what we
need how to get them -
8
Knowledge Acquisition (KA)
  • Knowledge sources
  • Domain experts, software manuals textbooks.
  • KA techniques
  • Interview, protocol analysis, concept sorting
    etc.
  • Tools used
  • PC-PACK integrated knowledge engineering toolkit
  • Knowledge acquired
  • EDSO domain knowledge, EDSO processes and problem
    definition

Concept hierarchy in Laddering Tool
Concept mark-up in Protocol Editor
9
Knowledge Modelling
  • Techniques
  • CommonKADS knowledge engineering
    methodologies.
  • Knowledge models
  • Organization, agent task templates, domain
    schema inference rules.
  • Tools used
  • PC-PACK integrated knowledge engineering toolkit
  • Deliverables
  • Knowledge web in HTML, XML and UML, Conceptual
    task model, EDSO process flowchart

10
Ontology Development (1)
  • Tools
  • Protégé OilEd Editor
  • Representation
  • DAMLOIL CLIPS
  • Deliverables
  • EDSO domain ontology
  • EDSO task ontology
  • Mesh generation tool (Gambit software) ontology
  • User-profile ontology

Protégé Editor
OilEd Editor
DAMLOIL
11
Ontology Development (2)
  • Ontology Views
  • DL ontologies (DAML/OWL)
  • Simplified views
  • Tailored to specific domains
  • Ontology Views
  • Underlying complexity hidden
  • Ontology editing by
  • Knowledge engineers
  • Domain experts

12
Grid-oriented Knowledge Management- From
local, standalone KBSs to distributed,
shared knowledge services -
13
The KM Architecture for the Grid
  • Features
  • Service-oriented approach
  • Ontologies as a conceptual backbone
  • Integrated KM framework
  • Layered modular structure
  • Distributed knowledge reuse sharing
  • Flexible extensible
  • Robust easy maintenance

14
Knowledge Portal
  • Functions
  • Make knowledge available accessible
  • Provide tools for knowledge reuse and exchange
  • Security infrastructure
  • Knowledge resources management
  • Techniques
  • Microsoft .Net framework

video demo
live demo
15
Ontology Services
  • Facilitating ontology sharing reuse
  • Ontology service APIs
  • Domain independence
  • DAMLOIL/OWL standards
  • Soap-based web services -WSDL
  • Java, Apache Tomcat Axis technologies

16
Knowledge Advice Service
  • Application Side
  • Ontologies
  • Knowledge bases
  • Problems being solved
  • Knowledge Service Side
  • Inference layer the reasoning process of a KBS
    in domain-independent terms
  • Communication layer XML-based messaging
  • Application layer provide common terms for
    knowledge bases, inference layer and
    communication schema
  • Standalone knowledge advice system implemented
  • Not wrapped as web/Grid service yet

17
Exploiting Knowledge in Geodise- Make
differences for EDSO
through the use of knowledge -
18
Knowledge Application 1 Create Semantic Content
  • Goals
  • Machine understandable information
  • Facilitate sharing reuse
  • Technique tool
  • OntMat-annotizer
  • Geodise Ontologies
  • Example
  • OPTIONS log-files annotation

video demo
19
Knowledge Application 2Ontology-assisted
Workflow Management
  • Features
  • Function selection
  • Function instantiation
  • Database schema
  • Semantic instances
  • Semantic workflow
  • Technologies
  • EDSO ontologies ontology services
  • Java JAX-RPC, DOM/SAX

20
Knowledge Application 3Knowledge-based Design
Advisor
  • Features
  • Context-sensitive advice
  • Advice at multi-levels of granularity (process,
    task )
  • KBSs as knowledge services
  • Technologies
  • Knowledge engineering
  • EDSO ontologies
  • Rule-based reasoning techniques

21
Knowledge Application Prototype
Knowledge-based Ontology-assisted Workflow
Construction Environment
video demo
22
Knowledge Application 4 EDSO Component
Management for the Grid
  • Aim to make EDSO components (which could be a
    problem definition, an algorithm, a solution or a
    task) available on the Grid, easy of use and
    reusable to other users.
  • Problems involved
  • Describe or model components in a way
  • Create instances and repositories
  • Discovery and retrieval mechanisms
  • Query and inference mechanisms
  • Semantics on the use and re-use of the components

23
Knowledge Application 4 Component Management
(1) XML-based Template-oriented Approach
  • Use XML XML Schema
  • Java/JAXFront technology
  • Access via knowledge APIs
  • Potential ontology support

24
Example Use Arcadia Problem Setup
Knowledge API called in MatLab
25
Knowledge Application 4 Component Management
(2) Semantic Service-oriented Approach
  • Semantic description for components using
    DAMLOIL /OWL ontologies
  • Automated form generation for creating instances
  • RDF as the representation formalism
  • Semantic knowledge repository using RDF triple
    store
  • Semantics-based query inference technologies

26
Summary
  • EDSO knowledge
  • EDSO domain, process, problem definition,
    (partial) optimisation algorithms
  • EDSO ontologies
  • Domain ontology, task ontology, Gambit user
    profile ontology
  • Grid-oriented knowledge management architecture
  • Ontology service infrastructure
  • Knowledge publishing mechanism
  • Service-oriented KBS paradigm
  • Application prototypes
  • Knowledge portal workflow construction
    environment knowledge-based advice system,
    XML-based templates-oriented description for EDSO
    components ontology-assisted Gambit Journal file
    editor
  • A semantic description framework for EDSO
    components

27
Future Work
  • Component management
  • Knowledge repositories for EDSO functions,
    problems in CFD workflows
  • Storage, query inference mechanisms
  • Service-oriented KBSs reuse infrastructure
  • Reasoning services - problem-solving methods
    (PSM)
  • Brokering services - a paradigm for manipulating
    reasoning services on the Web
  • Knowledge-based decision-making support systems
  • Knowledge intensive points (need to be clarified
    from domain users)
  • Further KAs
  • Semantics-based, case-based reasoning mechanisms
  • Geodise knowledge toolkit in Matlab
  • Where when it fits in, what knowledge is
    needed, in which form? We need application
    scenarios user requirements.

28
Thank you! Q/A
29
Knowledge Application 2Ontology-assisted
Workflow Management
  • Features
  • Ontology-assisted function selection
  • Ontology-assisted function instantiation
  • Database schema
  • Semantic instances workflow
  • Technologies
  • EDSO ontologies ontology services
  • Java JAX-RPC, DOM/SAX

30
Knowledge-based Systems for EDSO
  • Process-level design advisor
  • Service-oriented paradigm
  • Ontology as common terms
  • Knowledge APIs
  • XML-based messaging
  • Task-level design tools
  • Ontology-assisted Gambit journal file editor
  • Critique on commands workflow

Knowledge-based advisor
Design advice
Gambit journal file editor
Add a task
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