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 byGabrielle Holland
Modified over 3 years ago
© 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
© 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
© 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
© 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
© 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
© 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
© 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
© 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
© 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
© 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
© Geodise Project, University of Southampton, 2001-2004. http://www.geodise.org/ 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, 2001-2004. http://www.geodise.org/ Towards Service Oriented Paradigm Server (in the middle) –Semantic layer –Interfaces at different level Web service Java APIs
© 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?
© 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 …
© 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
© Geodise Project, University of Southampton, 2001-2004. http://www.geodise.org/ Function Query GUI
© 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
© 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
© 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
© 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
© 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
© 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 engineers favorite PSE)
© 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
© Geodise Project, University of Southampton, Applying the Semantic Web to Manage Knowledge on the Grid Feng Tao, Colin.
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, Knowledge Management in Geodise Geodise Knowledge Management Team Barry Tao, Colin Puleston, Liming.
© Geodise Project, University of Southampton, Workflow Support for Advanced Grid-Enabled Computing Fenglian Xu *, M.
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, Grid middleware for engineering design search and optimisation Graeme Pound.
Semantic Web based Collaborative Knowledge Management LSL, ECS Feng (Barry) Tao A generic SOA for managing semantics driven domain knowledge.
BiodiversityWorld GRID Workshop NeSC, Edinburgh – 30 June and 1 July 2005 Metadata Agents and Semantic Mediation Mikhaila Burgess Cardiff University.
© Geodise Project, University of Southampton, Integrating Data Management into Engineering Applications Zhuoan Jiao, Jasmin.
Grid Enabled Optimisation and Design Search for Engineering (G EODISE ) Prof Simon Cox Southampton University 3 rd Annual Workshop on Linux Clusters for.
© Geodise Project, University of Southampton, Geodise: A Grid-enabled PSE for design search and optimisation Graeme Pound.
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,
AHM2006, RSSM: A Rough Sets based Service Matchmaking Algorithm Bin Yu and Maozhen Li School of Engineering and Design.
Ontology-derived Activity Components for Composing Travel Web Services Matthias Flügge Diana Tourtchaninova
1 Schema Registries Steven Hughes, Lou Reich, Dan Crichton NASA 21 October 2015.
SKOS. Ontologies Metadata –Resources marked-up with descriptions of their content. No good unless everyone speaks the same language; Terminologies –Provide.
User Profiling using Semantic Web Group members: Ashwin Somaiah Asha Stephen Charlie Sudharshan Reddy.
Grid Technologies for Engineering Applications Marc Molinari e-Science Centre University of Southampton.
A Portrait of the Semantic Web in Action Jeff Heflin and James Hendler IEEE Intelligent Systems December 6, 2010 Hyewon Lim.
IPAS project: Providing a Knowledge Desktop Gary Wills, Richard Crowder, Nigel Shadbolt and Sylvia Wong July2008.
TU e technische universiteit eindhoven / department of mathematics and computer science Modeling User Input and Hypermedia Dynamics in Hera Databases and.
Grid programming with components: an advanced COMPonent platform for an effective invisible grid © 2006 GridCOMP Grids Programming with components. An.
Interoperability of Distributed Component Systems Bryan Bentz, Jason Hayden, Upsorn Praphamontripong, Paul Vandal.
Semantic Rich Internet Application (RIA) Modeling, Deployment and Integration Zoran Balkić, Marina Pešut, Franjo Jović Faculty of Electrical Engineering,
Object-Oriented Application Frameworks Much of the cost and effort stems from the continuous re- discovery and re-invention of core concepts and components.
From Ontology Design to Deployment Semantic Application Development with TopBraid Holger Knublauch
Editing Description Logic Ontologies with the Protege OWL Plugin.
1 Geospatial and Business Intelligence Jean-Sébastien Turcotte Executive VP San Francisco - April 2007 Streamlining web mapping applications.
Semantic Interoperability in GIS N. L. Sarda Suman Somavarapu.
1 Foundations V: Infrastructure and Architecture, Middleware Deborah McGuinness TA Weijing Chen Semantic eScience Week 10, November 7, 2011.
Using the Open Metadata Registry (openMDR) to create Data Sharing Interfaces October 14 th, 2010 David Ervin & Rakesh Dhaval, Center for IT Innovations.
WonderWeb. Ontology Infrastructure for the Semantic Web. IST Project Review Meeting, 11 th March, WP2: Tools Raphael Volz Universität.
Teranode Tools and Platform for Pathway Analysis Michael Kellen, Solution Manager June 16, 2006.
11 CORE Architecture Mauro Bruno, Monica Scannapieco, Carlo Vaccari, Giulia Vaste Antonino Virgillito, Diego Zardetto (Istat)
Jena a introduction Semantic Web Tools. Originally devised by HP Labs in Bristol, it was developed by Brian McBride of Hewlett-Packard and was derived.
© Geodise Project, University of Southampton, Geodise Middleware Graeme Pound, Gang Xue & Matthew Fairman Summer 2003.
© Geodise Project, University of Southampton, Data Management in Geodise Zhuoan Jiao, Jasmin Wason and Marc Molinari
Andrew S. Budarevsky Adaptive Application Data Management Overview.
Preface IIntroduction Objectives I-2 Course Overview I-3 1Oracle Application Development Framework Objectives 1-2 J2EE Platform 1-3 Benefits of the J2EE.
Designing Services for Grid-based Knowledge Discovery A. Congiusta, A. Pugliese, Domenico Talia, P. Trunfio DEIS University of Calabria ITALY
March 23, 2006M.I.T., Anna Univ, Chennai 1 Development of Front End tools for Semantic Grid Services Dr.S.Thamarai Selvi, Professor & Head, Dept of Information.
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.
© Geodise Project, Scenario: Design optimisation v Model device, discretize, solve, postprocess, optimise Scripting.
26/02/ WSMO – UDDI Semantics Review Taxonomies and Value Sets Discussion Paper Max Voskob – February 2004 UDDI Spec TC V4 Requirements.
Ontology Servers and Metadata Vocabulary Repositories Dr. Manjula Patel Technical Research and Development
Enabling complex queries to drug information sources through functional composition Olivier Bodenreider Lister Hill National Center for Biomedical Communications.
Efficient RDF Storage and Retrieval in Jena2 Written by: Kevin Wilkinson, Craig Sayers, Harumi Kuno, Dave Reynolds Presented by: Umer Fareed 파리드.
Using DAML+OIL Ontologies for Service Discovery in myGrid Chris Wroe, Robert Stevens, Carole Goble, Angus Roberts, Mark Greenwood
© 2017 SlidePlayer.com Inc. All rights reserved.