Knowledge Managementin Geodise

Geodise Knowledge Management Team

Liming Chen, Barry Tao, Colin Puleston, Paul Smart

University of SouthamptonUniversity of Manchester

Epistemics Ltd.

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

Geodise MeetsKnowledge Management (KM)

- put KM in context -

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

GEODISE

APPLICATION SERVICE

PROVIDERCOMPUTATION

GEODISE PORTAL

OPTIMISATION

Engineer

Parallel machinesClusters

Internet Resource ProvidersPay-per-use

Optimisation archive

Intelligent Application Manager

Intelligent Resource Provider

Licenses and code

Session database

Design archive

OPTIONSSystem

Knowledge repository

Traceability

Visualization

Globus, Condor, OGSA

Ontology for Engineering,

Computation, &Optimisation and Design Search

CAD SystemCADDSIDEASProE

CATIA, ICAD

AnalysisCFDFEMCEM

ReliabilitySecurity

QoS

The Problems & the SolutionsGeodise: “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

The Approach to Knowledge Management

Domain Users

Knowledge Engineers

Domain Experts

ApplicationDomain

Application Scenarios & User Requirements

Knowledge Acquisition

Knowledge Publishing

Knowledge Modelling

Knowledge Use & Re-use

Knowledge Maintenance

Validation

Knowledge SupportVia KBSs

ApplicationSystems

Knowledge Acquisition and Modelling

- what we need & how to get them -

Knowledge Acquisition (KA)

Knowledge sourcesDomain experts, software manuals & textbooks.

KA techniquesInterview, protocol analysis, concept sorting etc.

Tools usedPC-PACK integrated knowledge engineering toolkit

Knowledge acquiredEDSO domain knowledge, EDSO processes and problem definition

Concept mark-up in Protocol Editor

Concept hierarchy in Laddering Tool

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

DeliverablesKnowledge web in HTML, XML and UML, Conceptual task model, EDSO process flowchart

Ontology Development (1)

ToolsProtégé & OilEd Editor

Representation DAML+OIL & CLIPS

Deliverables EDSO domain ontology EDSO task ontology Mesh generation tool

(Gambit software) ontology

User-profile ontology

Protégé Editor

OilEd Editor

DAML+OIL

Ontology Development (2)Ontology Views

DL ontologies (DAML/OWL) Simplified views Tailored to specific domains

OtherViews

Other Views??

Ontology Client

Ontology Server

WEB

Semantic Network View (Configurable)

DAML+OIL/OWL Ontology

Instance Store (Database)

GeodiseTasks

Geodise Concept

s

FaCTReasoner

GONGConcept

s

Concept Query View

Ontology Views Underlying complexity hidden Ontology editing by…

Knowledge engineers Domain experts

Grid-oriented Knowledge Management

- From local, standalone KBSs to distributed, shared knowledge services -

Features:Service-oriented approach

Ontologies as a conceptual backbone

Integrated KM framework

Layered modular structure

Distributed knowledge reuse & sharing

Flexible & extensible

Robust & easy maintenance

The KM Architecture for the Grid

Knowledge Portal

Functions Make knowledge available

& accessible Provide tools for knowledge

reuse and exchange Security infrastructure Knowledge resources

management

Techniques Microsoft .Net framework

Ontology Services

Facilitating ontology sharing & reuse

Ontology service APIs

Domain independence DAML+OIL/OWL standards

Soap-based web services -WSDLJava, Apache Tomcat & Axis technologies

Knowledge Advice ServiceApplication 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

Exploiting Knowledge in Geodise

- Make differences for EDSO through the use of knowledge -

Knowledge Application 1: Create Semantic Content

Goals Machine understandable information Facilitate sharing & reuse

Technique & tool OntMat-annotizer Geodise Ontologies

Example OPTIONS log-files annotation

Knowledge Application 2:

Ontology-assisted Workflow Management

Features: Function selection Function instantiation Database schema Semantic instances Semantic workflow

Technologies: EDSO ontologies &

ontology services Java JAX-RPC,

DOM/SAX

Knowledge Application 3:

Knowledge-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

Knowledge Application PrototypeKnowledge-based Ontology-assisted Workflow Construction Environment

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

Knowledge Application 4: Component Management (1)

XML-based Template-oriented ApproachUse XML & XML Schema

Java/JAXFront technology

Access via knowledge APIs

Potential ontology support

Example Use – Arcadia Problem Setup

<ProblemProfile description="Arcadia5 design problem" dg_id="" lastTimeUsed="2003-03-04T11:21:36" timeCreated="2002-11-23T09:20:23"user="barry" xmlns="http://www.geodise.org/knowledge" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.geodise.org/knowledgeD:\geodise\XML_Templates\problem_mo.xsd">

<designVariables><name>a_l</name><meaning>The maximum bump height of the Hicks-Henne bump function on the lower surface of the nacelle</meaning><unit>mm</unit><limit>

<continousLimit><lower_bound>-0.15</lower_bound><default_value>0.05</default_value><upper_bound>0.04</upper_bound>

</continousLimit></limit><fixed>true</fixed>

</designVariables><designVariables>

<name>xp_l</name><meaning>The bump peak location (on the x-axis) of the Hicks-Henne bump function on the lower surface of the nacelle</meaning><unit>mm</unit><limit>

<continousLimit><lower_bound>0.40</lower_bound><default_value>0.5</default_value><upper_bound>0.80</upper_bound>

</continousLimit></limit><fixed>true</fixed>

</designVariables><designVariables>

<name>t_l</name><meaning>The bump width parameter of the Hicks-Henne bump function on the lower surface of the nacelle</meaning><unit>mm</unit><limit>

<continousLimit><lower_bound>2.00</lower_bound><default_value>3</default_value><upper_bound>10.00</upper_bound>

</continousLimit></limit><fixed>false</fixed>

</designVariables><designVariables>

<name>a_u</name><meaning>The maximum bump height of the Hicks-Henne bump function on the upper surface of the nacelle</meaning><unit>mm</unit><limit>

<continousLimit><lower_bound>0.00</lower_bound>

% Query and locate the instance fileresult=gd_query('standard.archiveDate > 2003-03-16');ProblemID=result{1}.standard.ID;local_file_path=gd_retrieve(ProblemID,'d:\'); %local_file_path=’D:/geodise/XML_Templates/problem_mo_arcadia5.xml’

% Specify the local path of the problem profile instance.problem_profile_instance=local_file_path;

% get information about design variablesxp=knowledgeapi.XMLParser(problem_profile_instance);% get information about design variablesdvs=knowledgeapi.DesignVariables1(xp.getDoc);%get information about objective functionof=knowledgeapi.ObjectiveFunction(xp.getDoc);% The recommented boundaries for the design parameters, useful as% allows the user to use a constrained optimisation.% design parameter boundsdsgnmin = rot90(dvs.getLowerBounds);%[ -0.15 0.40 2.00 0.00 0.50 2.00];dsgnmax = rot90(dvs.getUpperBounds);%[ 0.05 0.80 10.00 0.15 0.85 5.00];defaultValues=rot90(dvs.getDefaultValues);% design parameters selected to be design variablesselect = rot90(dvs.getSelected);%[3,5];selectedObjName=char(of.getSelectedObjName);

% Create a setup file for the optimisation% [setup_struct,setupFileID] = arcadia5_setup( [3,5],'peakvel2','',[0.04,0.5,3,0.02,0.6,3],1.4,1.5,0.1,4.6,[ -0.75,1.5,0,0.95],[0.05,0.0125,0.05,0.0125])[setup_struct,setupFileID] = arcadia5_setup( select,selectedObjName,'',defaultValues,1.4,1.5,0.1,4.6,[ -0.75,1.5,0,0.95],[0.05,0.0125,0.05,0.0125])

% Example use of the programDesignVariables= rot90(dvs.getSelectedDefaults) %[2.0, 0.85];

Knowledge API called in MatLab

Semantic description for components using DAML+OIL /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

EDSO Ontologies (service/function)

Ontology Services

Service/FunctionForm or Templates

Semantics-based Query &

Inference

Semantics-based Query &

Inference

RDF Triple Store& Permanent Storage (DBS)

Concept Java Classes

RDF Generator

Jena

RD

F A

PIs

Geodise Users

Create

Re-use

Geodise toolkit in Matlab

Knowledge Application 4: Component Management (2)

Semantic Service-oriented Approach

SummaryEDSO 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

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.

Thank you!

Q/A …

Knowledge Application 2:

Ontology-assisted Workflow ManagementFeatures

Ontology-assisted function selection Ontology-assisted function instantiation Database schema Semantic instances & workflow

Ontology service

Task ontology

Technologies EDSO ontologies & ontology

services Java JAX-RPC, DOM/SAX

Knowledge-based Systems for EDSO

Gambit journal file

editor

Knowledge-based advisor

Design advice

Add a task

Process-level design advisor Service-oriented paradigm Ontology as common terms

Task-level design tools Ontology-assisted Gambit journal file editor Critique on commands & workflow

Knowledge APIs XML-based messaging