Top Banner
© Geodise Project, University of Southampton, 2001-2004. http://www.geodise.org/ Semantic Web based Content Enrichment and Knowledge Reuse in e-Science Feng Tao, Liming Chen, Nigel Shadbolt, Fenglian Xu, Simon Cox, Colin Puleston, Carole Goble University of Southampton University of Manchester U.K. Presenter: Barry TAO
23

© Geodise Project, University of Southampton, 2001-2004. Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

Mar 28, 2015

Download

Documents

Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Page 1: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Semantic Web based Content Enrichment and Knowledge Reuse

in e-ScienceFeng Tao, Liming Chen, Nigel Shadbolt, Fenglian Xu, Simon

Cox, Colin Puleston, Carole Goble

University of SouthamptonUniversity of Manchester

U.K.

Presenter: Barry TAO

Page 2: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Overview

• Background and purpose – EDSO, Resource, knowledge support

• A layered semantic infrastructure– Protégé + OWL, Ontology, Jena, Annotator and Advisor

• Life cycle of semantic web base KM– Knowledge capture, binding and reuse

• Illustration of various tools– Generic Protégé tool, Function Annotator, Knowledge advising

service, knowledge toolbox in Matlab, etc.

• Summary

Page 3: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Background and purposes

• e-Science – Large scale science– Distributed global collaboration on data, computation and knowledge

• Grid based EDSO– Engineering Design Search & Optimisation– Resources of distributed computation, distributed storage and distributed knowledge– Toolbox of Grid enabled Matlab functions

• Describe and share resources using Ontology and Semantic Grid technologies– Components: Matlab functions – the toolbox, – Domain knowledge: optimisation methods, valid configurations, etc.

• Provide knowledge through reusing the semantics– Retrieval of the semantics (direct use)– Advice (more advanced usage)

On function configuration On workflow composition (driven by semantic matching)

– Web services, distributed and service oriented architecture

Page 4: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Layered Semantic Web Infrastructure

• EDSO Domain Ontology– Concepts and relations in a domain– Obtained through KA– Represented in OWL

• Generic Ontology/Semantics manipulation

– Protégé with Owl plug-in– Ontology further refined and populated in

protégé

• Geodise knowledge services/demonstrators

– Function Annotator– Semantic Retrieval GUI– Knowledge advisor service

• Geodise Apps integrated with knowledge

– Knowledge toolbox in Matlab– WCE standalone tool– DSE standalone tool

Applicationswith integratedKnowledge support

ProtégéOWL plug-inEditing GUI

SemanticDriven GUI

FunctionAnnotator

KnowledgeAdvisor/Service

HP Jena Ontology API

Jena normal model Jena +DIG reasoner

Domain ontology of EDSO in OWL(OWL-Lite, OWL-DL or OWL-full)

Geodise Components Generic ComponentsKeys

KnowledgeToolbox

Workflow CompositionEnvironment (WCE)

Domain ScriptEditor (DSE)

Page 5: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Knowledge Life cycle

• Knowledge Capturing– Knowledge Acquisition, building

Ontologies

• Knowledge Binding– Annotation : Creating instances of

ontological concepts– Protégé editor, function annotator

• Knowledge Modeling – Specification of useful knowledge:

Semantic retrieval, advice on function configuration and assembly

• Knowledge Reusing– Semantic based function query and

knowledge advisor

• Illustration follows

Protégé with OWL Plug-in Function annotator

BuildingOntologies

Generatinginstances

Inst

ance

Sto

ring

OW

L file

Reuse over the OWL ontology model

Ontology drivenDL-based query

Semantic matchingbased knowledge advisor

Jena API

Page 6: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Knowledge Capturing

• Knowledge Acquisition– From Domain experts and

domain documents.– Build in Protégé with OWL

Plug-in– Concepts

Classes

– Relationships Hierarchy Property slots

• Result– OWL format ontology

Page 7: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Function Annotation (Knowledge Binding)

• Generating semantic instances– Binding ontology with semantics content– Populating the semantic web based knowledge base

• Supporting Tools– Through Protégé editor

High flexibility (can generate instances of any ontology concept) sometimes tedious

– Through a customized function annotator Automatic parsing Lack of flexibility (only deal with functions at the moment)

– We use both

Page 8: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

With Protégé

• Creating + maintaining the ontology

• Generating semantic instances

– Instantiating abstract nodes defined in ontology

– Filling ontology driven forms with semantic content

Page 9: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

With Function Annotator

• Customised for Matlab functions

– Automatic parsing Matlab function source

• Instantiating abstract nodes defined in ontology

• Semi-automatic filling of the ontology driven forms

Panel 5

Panel 4

Panel 3

Panel 2

Panel 1

Panel 6

Panel 5

Panel 4

Panel 3

Panel 2

Panel 1

Panel 6

Page 10: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Knowledge Reuse

• Semantic retrieval – Retrieve semantics from the knowledge repository (Entity Semantics)

• Inference– Direct – “a subClassOf b” , “b subClassOf c”– Inferred – “a subClassOf c”

• Advice– Function assembly (Service composition)– Function configuration (Parameter tuning)

• Service Oriented Architecture – Service side: Semantics processing and domain specific knowledge

generation mechanisms with web service interfaces– Client side: light weight, generic web service invoking, returns XML

Page 11: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Function/workflowRepository (Archive)

Service-oriented Semantics Application Scenario

Geodise Functions

Function Ontology

Function Annotator

Grid Fabrics

Semantic/Knowledge support middleware

OntologyServices

AdvisorServices

InstanceServices ….

Engineering Design Community

The Proposed Browser-based

Function/workflowExplorer

Geodise

Matlab EnvWCEOtherapplications

If we want to leverage and harvest the maximum benefit of Semantic web, i.e. effective discovery, machine-enabled (processible, understandable) interoperability and automation, and the Grid, i.e. resource sharing, this is one of the realisations.

The choice is up to the users!

Page 12: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Towards Service Oriented Paradigm

• Server (in the middle)– Semantic layer– Interfaces at different level

Web service Java APIs

Server side Knowledge Service Light weight client side(Applications)

Web service

OWL/Jena OntologyModel

Jena AP

Semantic MatchingEngine and Knowledge

Advisor API

KnowledgeToolbox

GD API

Matlab

Java Virtual Machine

Other java applications thatconsume the knowledge

Workflow CompositionEnvironment (WCE)

Domain Script Editor

Function Annotator

DL-based FunctionQuery GUI

Migrate to

WCE

Page 13: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Towards Service Orientated Paradigm

• Other java applications (to the left)

– Consume the service via Knowledge service APIs

– WCE, DSE, FA, DL-FQ– To be moved to client side in

the right?

Server side Knowledge Service

Web service

OWL/Jena OntologyModel

Jena AP

Semantic MatchingEngine and Knowledge

Advisor API

GD API

Light weight client side(Applications)

KnowledgeToolbox

Matlab

Java Virtual Machine

Other java applications thatconsume the knowledge

Workflow CompositionEnvironment (WCE)

Domain Script Editor

Function Annotator

DL-based FunctionQuery GUI

Migrate to

WCE

Page 14: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Towards Service Orientated Paradigm

• Client (to the right)– Matlab PSE– Knowledge Toolbox

Matlab Java Web service consumer

• Illustrations follows …

Server side Knowledge Service

Web service

OWL/Jena OntologyModel

Jena AP

Semantic MatchingEngine and Knowledge

Advisor API

GD API

Light weight client side(Applications)

KnowledgeToolbox

Matlab

Java Virtual Machine

Other java applications thatconsume the knowledge

Workflow CompositionEnvironment (WCE)

Domain Script Editor

Function Annotator

DL-based FunctionQuery GUI

Migrate to

WCE

Page 15: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Semantics Retrieval• Examples

• Get all optimisation methods (below)

• Get semantics of a particular optimisation method (right)

• Integration Support dynamic GUI generation

Page 16: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Function Query GUI

Page 17: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Advice on Function Assembly(Integrated in Matlab – Knowledge Toolbox)

• Goal– Function assembly– What can be deploy

next and before?

• Mechanism– Matlab Java

WSDL Web service

– Function semantic interface

– Semantic matching

• Pre-requirements– Function has been

annotated– Semantics available

in the instance store

Page 18: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Advice on Function Configuration

You are using #genetic algorithm search#. Additional control parameters have been added.You may need still to configure the following control parameters:.GA_NPOP GA_ALPHA GA_DMAX GA_DMIN GA_NBIN GA_NBREED GA_NCLUST GA_NRANDM GA_PBEST GA_PCROSS GA_PENAL GA_PINVRT GA_PMUTNT GA_PRPTNL GA_PSEED

% get the default beam structure

beam = createBeamStruct (4)

% analyze the OMETH and advice on its additional control parameter (with default value)

beamcontrol = gdk_options(beam)

% check semantics

gdk_semantics(‘GD_NPOP’)

% further configure these control parameters

… …

% run options

s = OptionsMatlab (beamcontrol)

1

2

3

Page 19: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Advice on Function Assembly(Integrated in WCE – workflow advisor)

Select a function and request advice

Function assembly advice

Page 20: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Advice on Function Assembly(Integrated in Domain Script Editor)

Function configuration advice

Function assembly advice

Ontology and semantics Domain script editing area

Page 21: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Related Work

• Protégé with OWL plug-in– Open source ontology editor, widely used– OWL plug-in built on Jena

• Jena, HP– Originally designed as RDF oriented– OWL support added on at the top layer– Various types of ontology modes: OWL_MEM, OWL_DL_MEM, etc.– Inference is available through graph manipulating

• OilED+Ontoview, UoM– OilEd developed for building DAML+OIL ontology– Ontoview is a simplified view/editing tool and API– Adapted for DL based reasoning over Instance Store

Page 22: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Summary & Conclusions

• Purpose and background of KM in EDSO• A layered semantic infrastructure

– Protégé + OWL, Ontology, Jena, Annotator and Advisor• Life cycle of semantic web base KM

– Knowledge capture, binding and reuse• Demonstrations of various tools

• Long process• Preparation of ontologies and semantics instances are important• Integration is not easy• Reusing in a smart way is the key (reuse in engineer’s favorite PSE)

Page 23: © Geodise Project, University of Southampton, 2001-2004.  Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.

© Geodise Project, University of Southampton, 2001-2004.http://www.geodise.org/

Future Work

• Allow engineers to curate knowledge themselves in their favorite PSE (more integration)

WSE, Matlab

• Synchronization Engineers’ need to Maintain local knowledge of their own Selectively synchronize local knowledge with centralized knowledge

• Target more resources– Workflow– Grid fabrics

• More interfaces to the knowledge repository– More advanced advice on OptionsMatlab in Matlab– Function Browser