We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byJasmine Craig
Modified over 2 years ago
© Geodise Project, University of Southampton, Applying the Semantic Web to Manage Knowledge on the Grid Feng Tao, Colin Puleston, Carole Goble, Nigel Shadbolt, Liming Chen, Graeme Pound, Fenglian Xu, Simon Cox University of Southampton University of Manchester Presenter: Barry
© Geodise Project, University of Southampton, Overview Background and purpose –EDSO, Resource, knowledge support A layered semantic infrastructure –DL Ontology + Instance store, Ontoview, annotator and advisor Life cycle of semantic web base KM –Knowledge capture, binding and reuse Demonstrations of various tools –Ontoview, annotator, advisor, knowledge toolbox, etc. Summary and future work
© Geodise Project, University of Southampton, Background and purposes 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 –Web services, distributed and service oriented architecture
© Geodise Project, University of Southampton, Layered Semantic Web Infrastructure EDSO Domain Ontology –Concepts and relations in a domain –Obtained through KA –Represented in DAML+OIL Generic Ontology manipulation and storing mechanism –Ontoview API and editors –Ontology further refined and populated in Ontoview 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
© Geodise Project, University of Southampton, Knowledge Life cycle Knowledge Capturing –Knowledge Acquisition, building Ontologies Knowledge Binding –Annotation : Creating instances of ontological concepts –Ontoview 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
© Geodise Project, University of Southampton, Knowledge Capturing Knowledge Acquisition –From Domain experts and domain documents. –Build in OilEd and maintain in Ontoview) Ontology –Concepts Node Type –Relationships Hierarchy Link Type & Data Field Result –DAML+OIL format
© Geodise Project, University of Southampton, Function Annotation (Knowledge Binding) Generating semantic instances –Binding ontology with semantics content –Populating the semantic web based knowledge base Supporting Tools –Through Ontoview 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
© Geodise Project, University of Southampton, Ontoview Editor Creating + maintaining the ontology Generating Concrete nodes (semantic instances) –Instantiating abstract nodes defined in ontology –Filling ontology driven forms with semantic content
© Geodise Project, University of Southampton, 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
© Geodise Project, University of Southampton, Knowledge Reuse Function Query –Identify functions based on their semantics criteria (Semantics Functions) Advice –Retrieve semantics (Entity Semantics) –Function assembly (Service composition) –Function configuration Service Oriented Architecture
© Geodise Project, University of Southampton, Function/workflow Repository (Archive) Service-oriented Semantics Application Scenario Geodise Functions Function Ontology Function Annotator Grid Fabrics Semantic/Knowledge support middleware Ontology Services Advisor Services Instance Services …. Engineering Design Community The Proposed Browser-based Function/workflow Explorer Geodise Matlab EnvWCE Other applications 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!
© Geodise Project, University of Southampton, Towards Service Oriented Paradigm Server (in the middle) –Semantic layer –Interfaces at different level Web service Java APIs
© Geodise Project, University of Southampton, 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?
© Geodise Project, University of Southampton, Towards Service Orientated Paradigm Client (to the right) –Matlab PSE –Knowledge Toolbox Matlab Java Web service consumer Illustrations follows …
© Geodise Project, University of Southampton, 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
© Geodise Project, University of Southampton, 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
© Geodise Project, University of Southampton, Advice on Function Assembly (Integrated in WCE – workflow advisor) Select a function and request advice Function assembly advice
© Geodise Project, University of Southampton, Advice on Function Assembly (Integrated in Domain Script Editor) Function configuration advice Function assembly advice Ontology and semantics Domain script editing area
© Geodise Project, University of Southampton, DL-Based Function Query GUI
© Geodise Project, University of Southampton, Summary & Conclusions Purpose and background of KM in EDSO A layered semantic infrastructure –DL Ontology + Instance store, Ontoview, 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 engineers favorite PSE)
© Geodise Project, University of Southampton, 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
© Geodise Project, University of Southampton, Semantic Web based Content Enrichment and Knowledge Reuse in e-Science.
© Geodise Project, University of Southampton, Knowledge Management in Geodise Geodise Knowledge Management Team Barry Tao, Colin Puleston, Liming.
Knowledge Management in Geodise Geodise Knowledge Management Team Liming Chen, Barry Tao, Colin Puleston, Paul Smart University of Southampton University.
© Geodise Project, University of Southampton, Workflow Support for Advanced Grid-Enabled Computing Fenglian Xu *, M.
© Geodise Project, University of Southampton, Grid middleware for engineering design search and optimisation Graeme Pound.
Grid Enabled Optimisation and Design Search for Engineering (G EODISE ) Prof Simon Cox Southampton University 3 rd Annual Workshop on Linux Clusters for.
Knowledge based Learning Experience Management on the Semantic Web Feng (Barry) TAO, Hugh Davis Learning Society Lab University of Southampton.
Grid Enabled Optimisation and Design Search for Engineering (GEODISE)
© Geodise Project, University of Southampton, Geodise: A Grid-enabled PSE for design search and optimisation Graeme Pound.
© Geodise Project, University of Southampton, Geodise Middleware Graeme Pound, Gang Xue & Matthew Fairman Summer 2003.
© Geodise Project, University of Southampton, Integrating Data Management into Engineering Applications Zhuoan Jiao, Jasmin.
Grid Technologies for Engineering Applications Marc Molinari e-Science Centre University of Southampton.
© Geodise Project, University of Southampton, Geodise Middleware & Optimisation Graeme Pound, Hakki Eres, Gang Xue & Matthew Fairman Summer 2003.
IPAS project: Providing a Knowledge Desktop Gary Wills, Richard Crowder, Nigel Shadbolt and Sylvia Wong July2008.
Semantic Rich Internet Application (RIA) Modeling, Deployment and Integration Zoran Balkić, Marina Pešut, Franjo Jović Faculty of Electrical Engineering,
1 Schema Registries Steven Hughes, Lou Reich, Dan Crichton NASA 21 October 2015.
11 CORE Architecture Mauro Bruno, Monica Scannapieco, Carlo Vaccari, Giulia Vaste Antonino Virgillito, Diego Zardetto (Istat)
© Geodise Project, University of Southampton, Data Management in Geodise Zhuoan Jiao, Jasmin Wason and Marc Molinari
© Geodise Project, Scenario: Design optimisation v Model device, discretize, solve, postprocess, optimise Scripting.
An Ontology-based Framework for Radiation Oncology Patient Management DL McShan 1, ML Kessler 1 and BA Fraass 2 1 University of Michigan Medical Center,
Semantic Web based Collaborative Knowledge Management LSL, ECS Feng (Barry) Tao A generic SOA for managing semantics driven domain knowledge.
© Geodise Project, University of Southampton, Workflow Application Fenglian Xu 07/05/03.
BiodiversityWorld GRID Workshop NeSC, Edinburgh – 30 June and 1 July 2005 Metadata Agents and Semantic Mediation Mikhaila Burgess Cardiff University.
AHM2006, RSSM: A Rough Sets based Service Matchmaking Algorithm Bin Yu and Maozhen Li School of Engineering and Design.
Semantic Web and Web Mining: Networking with Industry and Academia İsmail Hakkı Toroslu IST EVENT 2006.
Flexibility and user-friendliness of grid portals: the PROGRESS approach Michal Kosiedowski
Preface IIntroduction Objectives I-2 Course Overview I-3 1Oracle Application Development Framework Objectives 1-2 J2EE Platform 1-3 Benefits of the J2EE.
COHSE Informed WWW Link Navigation Using Ontologies Prof. Carole Goble, Sean Bechhofer Dr. Leslie Carr, Prof. Wendy Hall, Prof. David De Roure, Steve Harris,
GRACE Project IST EGAAP meeting – Den Haag, 25/11/2004 Giuseppe Sisto – Telecom Italia Lab.
Andrew S. Budarevsky Adaptive Application Data Management Overview.
ModelPedia Model Driven Engineering Graphical User Interfaces for Web 2.0 Sites Centro de Informática – CIn/UFPe ORCAS Group Eclipse GMF Fábio M. Pereira.
Using the Open Metadata Registry (openMDR) to create Data Sharing Interfaces October 14 th, 2010 David Ervin & Rakesh Dhaval, Center for IT Innovations.
Providing web services to mobile users: The architecture design of an m-service portal Minder Chen - Dongsong Zhang - Lina Zhou Presented by: Juan M. Cubillos.
Developing GRID Applications GRACE Project
WaveMaker Visual AJAX Studio 4.0 Training Basics: Building Your First Application Binding Basics.
1 Benjamin Perry, Venkata Kambhampaty, Kyle Brumsted, Lars Vilhuber, William Block Crowdsourcing DDI Development: New Features from the CED 2 AR Project.
Enhance legal retrieval applications with an automatically induced knowledge base Ka Kan Lo.
Harokopio University of Athens – Department of Informatics and Telematics HAROKOPIOUNIVERSITY A Distributed Architecture for Building Federated Digital.
Design of a Search Engine for Metadata Search Based on Metalogy Ing-Xiang Chen, Che-Min Chen,and Cheng-Zen Yang Dept. of Computer Engineering and Science.
Improving Learning Object Description Mechanisms to Support an Integrated Framework for Ubiquitous Learning Scenarios María Felisa Verdejo Carlos Celorrio.
Implementing Metadata Marjorie M K Hlava, President Access Innovations, Inc. Albuquerque, NM
International Planetary Data Alliance Registry Project Update September 16, 2011.
SITools Enhanced Use of Laboratory Services and Data Romain Conseil
Pulan Yu School of Informatics Indiana University Bloomington Web service based Varuna.Net.
A Generic Software Framework for building Hybrid Ontology-Backed Models for Driving Applications Colin Puleston, James Cunningham, Alan Rector Bio-Health.
Distributed Aircraft Maintenance Environment - DAME DAME Workflow Advisor Max Ong University of Sheffield.
Presented by Scientific Annotation Middleware Software infrastructure to support rich scientific records and the processes that produce them Jens Schwidder.
© 2008 IBM Corporation ® IBM Cognos Business Viewpoint Miguel Garcia - Solutions Architect.
DANIELA KOLAROVA INSTITUTE OF INFORMATION TECHNOLOGIES, BAS Multimedia Semantics and the Semantic Web.
© 2017 SlidePlayer.com Inc. All rights reserved.