12国外大学研究所收集谷歌ngs pipeline的iaai04deroure

1、e-Science and theDavid De RoureUniversity of SouthamptonJuly 2004IAAI Panel2Outline1.e-Science and e-Research2.Enabling TechnologiesnGridnSemantic Web3.Semantic Grid4.Building BridgesJuly 2004IAAI Panel3Vision: e-Sciencee-Science is about global collaboration in key areas of science and the next gen

2、eration of computing infrastructure that will enable it. e-Science will change the dynamic of the way science is undertakenJohn Taylor, Director General of UK Research CouncilsJuly 2004IAAI Panel4 The Grid intends to make access to computing power, scientific data repositories and experimental facil

3、ities as easy as the Web makes access to information. Tony Blair, 2002Vision: e-ScienceJuly 2004IAAI Panel5UniversityR & DJoint Information Systems CommitteeUK funding contextResearch CouncilsParticle Physics and AstronomyEngineering and Physical SciencesNatural EnvironmentEconomic and SocialMedical

4、Biotechnology and Biological SciencesCCLRC(Arts and Humanities)Dept of Tradeand IndustryEuropeanCommissionCompaniesJuly 2004IAAI Panel6UK e-Science FundingFirst Phase: 2001 2004nApplication Projectsn74MnAll areas of science and engineeringnCore Programmen15M Research infrastructuren20M Collaborative

5、 industrial projectsSecond Phase: 2003 2006nApplication Projectsn96MnAll areas of science and engineeringnCore Programmen16M Research Infrastructuren10M DTI Technology FundAcross all areasApplication-ledCore programJuly 2004IAAI Panel7e-Science Core ProgramFour major functions:nAssist development of

6、 essential, well-engineered, generic, Grid middleware nProvide necessary infrastructure support for UK e-Science Research Council projectsnCollaborate with the international e-Science and Grid communitiesnWork with UK industry to develop industrial-strength Grid middlewareJuly 2004IAAI Panel8myGrid

7、pilot projectnBioinformaticsnImminent deluge of datanHighly heterogeneousnHighly complex and inter-relatednConvergence of data and literature archivesJuly 2004IAAI Panel9X-Raye-LabAnalysisPropertiesPropertiese-LabSimulationVideoDiffractometerGrid MiddlewareStructuresDatabaseCombe Chem pilot projectJ

8、uly 2004IAAI Panel10CambridgeNewcastleEdinburghOxfordGlasgowManchesterCardiffSouthamptonLondonBelfastDLRALHinxtonUK e-Science Grid July 2004IAAI Panel11UK e-Science: Phase 2Three major new activities:1.National Grid Service and Grid Operation Centre2.Open Middleware Infrastructure Institute for test

9、ing, software engineering and UK repository3.Digital Curation Centre to look at long-term data preservation issuesJuly 2004IAAI Panel12Grid Operation Support Centre Deploy production National Grid Service based on four dedicated compute and data nodes plus two UK Supercomputers Develop operational p

10、olicies, security, Gain experience with genuine users Develop Web Services based e-Science Grid Work with EU EGEE project, the NSF Cyberinfrastructure Program and A-P Grid activitiesJuly 2004IAAI Panel13Open Middleware Infrastructure InstitutenRepository for UK-developed Open Source e-Science/Cyber-

11、infrastructure MiddlewarenDocumentation, specification, QA and standardsnFund work to bring research project software up to production strengthnFund Middleware projects for identified gapsnWork with US NSF, EU Projects and othersnSupported by major IT companiesnSouthampton selected as the OMII siteJ

12、uly 2004IAAI Panel14Digital Curation CentrenIn next 5 years e-Science projects will produce more scientific data than has been collected in the whole of human historynIn 20 years can guarantee that the OS and spreadsheet program and the hardware used to store data will not existResearch curation tec

13、hnologies and best practice Need to liaise closely with individual research communities, data archives and librariesEdinburgh with Glasgow, CLRC and UKOLN selected as site of DCCJuly 2004IAAI Panel15 Education GridTeacher EducatorGridsInformal Education(Museum) GridStudent/Parent Community GridScien

14、ce GridsBioinformaticsEarth Science .Typical Science GridService such as ResearchDatabase or simulationTransformed by Grid Filterto form suitable for educationLearning ManagementGridPublisher GridCampus orEnterpriseAdministrativeGridEducation as a Grid of Grids (thanks to Geoffrey Fox)DigitalLibrary

15、GridJuly 2004IAAI Panel16Vision: e-ResearchnNot just new Sciencene-Social Sciencene-Humanitiesne-Artsne-Researchne-Businessne-AnythingnnAnd new disciplines!nResearchers working in all disciplines are faced daily with a wide variety of tasks necessary to sustain and progress their research activitynT

16、hese involve the analytical aspects of their work, access to resources, collaboration with fellow researchers, and project management and adminnThese tasks rapidly increase in scale and complexity as collaborations grow larger, become more geographically distributed and involve a wider range of disc

17、iplinesJISCJuly 2004IAAI Panel17Vision: HASTACHASTAC is an international, interdisciplinary consortium which seeks to create, develop, advance and utilize a broad range of leading computing and information systems while contributing to an understanding of the interconnections between the human scien

18、ces, natural sciences, arts, and technology in a complex global societyHumanities, Arts, Science and Technology Advanced Collaboratory July 2004IAAI Panel18Vision: CollaboratoryA collaboratory isa center without walls, in which the nations researchers can perform their research without regard to geo

19、graphical location, interacting with colleagues, accessing instrumentation, sharing data and computational resources, and accessing information in digital librariesWilliam Wulf, 1989U.S. National Science FoundationJuly 2004IAAI Panel19Vision: Joining upnThese visions are all about joining resources

20、and people together in new ways in order to create new thingsnResearchers can focus on the real researchnThe research process is acceleratednNew research results are possiblenNew research areas are possiblenNB s/research/business/July 2004IAAI Panel20Vision: The GridCourtesy of Ian FosterJuly 2004IA

21、AI Panel21Vision: The GridGrid computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high-performance orientation.we define the Grid problem”as flexible, secure

22、, coordinated resource sharing among dynamic collections of individuals, institutions, and resources - what we refer to as virtual organizationsFrom The Anatomy of the Grid: Enabling Scalable Virtual Organizations by Foster, Kesselman and TueckeJuly 2004IAAI Panel22Challenges: Unanticipated Re-usenW

23、ish to reusenDatanServicesnSoftwarenKnowledgemyGridCombechemJuly 2004IAAI Panel23Registries organizeservices of interestto a community RRRRRegistries organizeservices of interestto a community Registries organizeservices of interestto a community Challenges: Data IntegrationMany sourcesof data, serv

24、ices,computationAccessData integration activitiesmay require access to, &exploration of, data at many locationsExploration & analysismay involve complex,multi-step workflowsSecurityserviceSecurityservicePolicyservicePolicyserviceSecurity & policymust underlie access& managementdecisionsDiscoveryAcce

25、ssData integration activitiesmay require access to, &exploration of, data at many locationsExploration & analysismay involve complex,multi-step workflowsRMRMRMRMRMResource managementis needed to ensureprogress & arbitrate competing demandsRMRMRMRMRMResource managementis needed to ensureprogress & ar

26、bitrate competing demandsMany sourcesof data, services,computationDiscoveryCourtesy of Ian FosterJuly 2004IAAI Panel24Challenges: Virtual OrgsnResource configurations are transient, dynamic and volatile as services (databases, sensors, compute servers) switched in and outnThey are ad-hoc as service

27、consortia have no central location or control, and no existing trust relationshipsnThey may be large, with hundreds of services orchestrated at any timenThey may be long-lived, for example a protein folding simulation could take weeks nScale of data and compute resources is largenQuality of Service

28、and performance criteria are severenPlatform must be scalable, able to evolve, fault-tolerant, robust, persistent and reliablenIt should work seamlessly, and transparently the user might not know or care where their calculation is done using how many machines, or where data is actually held July 200

29、4IAAI Panel25Challenges: Comp ScinDynamic formation and management of virtual organisationsnOnline negotiation of access to services: who, what, why, when, hownConfiguration of applications and systems able to deliver multiple qualities of servicenAutonomic management of distributed infrastructures,

30、 services, and applicationsnManagement of distributed state as a fundamental issuenJuly 2004IAAI Panel26Outline1.The e-Vision and its challenges2.Enabling TechnologiesnGridnSemantic Web3.Semantic Grid4.Building BridgesJuly 2004IAAI Panel27Two infrastructure enablersnOn demand transparently construct

31、ed multi-organisational federations of distributed servicesnDistributed computing middlewarenComputational IntegrationnAn automatically processable, machine understandable webnDistributed knowledge and information managementnInformation integrationGrid ComputingSemantic WebJuly 2004IAAI Panel28July

32、2004IAAI Panel29Five Myths busted!1.Isnt it just for Physics?nNo Grids for Life Science and Medicine will dominate Grid applicationsnThink of the range and scale of data and the community!2.Isnt it just High Performance computing?nNo its a generic mechanism for forming, managing and disbanding dynam

33、ic federations of servicesnData integration, data access, data transport will dominatenApplication integration is the keyJuly 2004IAAI Panel30Five Myths busted!3.Isnt it just a bag of protocols glued together?nNo the Open Grid Service Architecture gives a well specified middleware stack built on ind

34、ustry standard web services4.Isnt it just Globus toolkit?nNo that is one reference implementation.5.Isnt it just a bunch of academic physicists?nNo all the commercial vendors are making serious investment. IBM DB2 and Oracle 10g will be grid-compliantJuly 2004IAAI Panel31Standard mechanisms for desc

35、ribing and invoking services: WSDL, SOAP, WS-Security etcStandard interfaces and behaviours for distributed systems: naming, service state, lifetime management, notificationStandard services: agreement, data access and integration, workflow, security, policy, brokeringSpecific services: drug discove

36、ry pipeline, sky surveysOpen Grid Service ArchitectureWeb Service Resource FrameworkWeb Service-NotificationWeb ServicesGrid ApplicationsGrid ServicesJuly 2004IAAI Panel32July 2004IAAI Panel33Origins of the Semantic WebThe Semantic Web is an extension of the current Web in which information is given

37、 a well-defined meaning, better enabling computers and people to work in cooperation. It is the idea of having data on the Web defined and linked in a way that it can be used for more effective discovery, automation, integration and reuse across various applications. The Web can reach its full poten

38、tial if it becomes a place where data can be processed by automated tools as well as people.W3C Activity StatementJuly 2004IAAI Panel34Layers of LanguagesWe are here!IdentityStandard SyntaxMetadata annotationsOntologiesRules & InferenceExplanationAttributionJuly 2004IAAI Panel35Resource Description

39、FrameworknCommon model for metadatanA graph of triplesnQuery over and link togethernRDQL, repositories, integration tools, presentation toolsnThe Network EffectGraphic courtesy of Tim Berners-LeeJuly 2004IAAI Panel36RDFOWL Web Ontology LanguageDAML+OILDARPA Agent Markup LanguageA W3C RecommendationO

40、ILOWLAll influenced by RDFOntology Inference LayerEU/NSF Joint Ad hoc CommitteeThe most popular ontology language in the world ever!DAMLOWL Lite (thesaurus)OWL DL (reason-able)OWL Full (anything goes)July 2004IAAI Panel375 More Myths Busted!1.Isnt it just AI and distributed agents (again)?nNo It is

41、primarily metadata integration and querying2.Dont you need all that reasoning stuff?nNo A little bit of semantics goes a long way! (Hendler)3.It only applies to the Web?nNo the technologies are being used for Enterprise integration, exposing data in a common model, common ontology languages, represe

42、nting terminologies. 4.One big ontology of everything never works!nNo multiple ontologies; multiple everything!5.One big Semantic Web! nNo lots of Semantic Web-lets, and expect it to break!July 2004IAAI Panel38Outline1.The e-Vision and its challenges2.Enabling TechnologiesnGridnSemantic Web3.Semanti

43、c Grid4.Building BridgesJuly 2004IAAI Panel39The Semantic Grid Report 2001nAt this time, there are a number of grid applications being developed and there is a whole raft of computer technologies that provide fragments of the necessary functionality. nHowever there is currently a major gap between t

44、hese endeavours and the vision of e-Science in which there is a high degree of easy-to-use and seamless automation and in which there are flexible collaborations and computations on a global July 2004IAAI Panel40Semantic GridScale of data and computationScale of Interoperab

45、ilitySemanticWebClassicalWebSemanticGridClassicalGridBased on an idea by Norman PatonJuly 2004IAAI Panel41Semantics in and on the GridThe Semantic Grid is an extension of the current Grid in which information and services are given well-defined meaning, better enabling computers and peopleto work in

46、 cooperationJuly 2004IAAI Panel42Underpinnings of e-ScienceGrid ComputingThe Semantic WebThe Semantic GridWeb ServicesContrast withJuly 2004IAAI Panel43Knowledge GridKnowledge ServicesKnowledge-based data/computation servicesKnowledge-based information servicesComputation servicesInformation service

47、sText miningData miningOGSABase Grid servicesOGSA Semantic GridservicesKnowledgeGridCol-laboratoryPortalDataservicesAdvanced Grid ApplicationsGrid Middleware FabricWSRFJuly 2004IAAI Panel45Grid Computing trajectoryCPU scavengingCPU intensive workload Grid as a utility, data Grids, robust infrastruct

48、ureIntra-company, intra communitye.g. Life Science GridSharing standard scientific process and data, sharing of common infrastructureBetween trusted partnersSharing of apps and know-howWith controlled set of unknown clientsVirtual organisations with dynamic access to unlimited resourcesFor alltimeco

49、stThere are SG technologies available today for immediate deploymentJuly 2004IAAI Panel46Semantics in e-ScienceOntology-aided workflow constructionRDF-based semantic mark up of results, logs, notes, data entriesnRDF-based service and data registriesnRDF-based metadata for experimental componentsnRDF

50、-based provenance graphsnOWL based controlled vocabularies for database contentnOWL based integrationJuly 2004IAAI Panel47Engineering DesignAPPLICATION SERVICE PROVIDERCOMPUTATIONGEODISE PORTALOPTIMISATIONEngineerParallel machinesClustersInternet Resource ProvidersPay-per-useOptimisation archiveInte

51、lligent Application ManagerIntelligent Resource ProviderLicenses and codeSession databaseDesign archiveOPTIONSSystemKnowledge repositoryTraceabilityVisualizationGlobus, Condor, SRBOntology for Engineering, Computation, &Optimisation and Design Search CAD SystemCADDSIDEASProECATIA, ICADAnalysisCFDFEM

52、CEMReliabilitySecurityQoSJuly 2004IAAI Panel48Ontologies for e-SciencenUser-oriented, scalable environment for domain experts to acquire, develop and use ontologies nBased on OilEd and Protg 2000nTransatlantic cooperation on the development of ontologies for e-ScienceUniversities Manchester and Sout

53、hampton, UKStanford University, USAJuly 2004IAAI Panel49Collaboration tools mapping real time discussions/group sensemakingenacting decisions/coordinating activitiessynthesising artifactsrecovering information from meetingsawareness ofcolleagues presencevirtual meetingsBuddySpaceNetMeetingAccess Gri

54、d NodeCompendiumReplayI-X ToolsJuly 2004IAAI Panel50NASA ScenarioCompendium maps from trained compendium astronautRemote Science Team (RST) on earth e.g. geologistsVideo andScience Data2. Virtual meeting of RSTusing CoAKTinG toolsPlan for nextDays EVA1. Astronauts debrief on EVAMarsJuly 2004IAAI Pan

55、el51Finding collaboratorsUsing scaleable triple store and AKT ontologyJuly 2004IAAI Panel52GGF9 Semantic Grid WorkshopnThe Role of Concepts in myGrid Carole GoblenPlanning and Metadata on the Computational Grid Jim Blythe nSemantic support for Grid-Enabled Design Search in Engineering Simon CoxnKnow

56、ledge Discovery and Ontology-based services on the Grid Mario CannataronAttaching semantic annotations to service descriptions Luc MoreaunSemantic Matching of Grid Resource Description Frameworks John BrookenInteroperability challenges in Grid for Industrial Applications Mike SurridgenSemantic Grid

57、and Pervasive Computing David De RoureJuly 2004IAAI Panel53GGF11 Semantic Grid WorkshopnEngineering semantics: Costs and Benefits Simon CoxnDesigning Ontologies and Distributed Resource Discovery Services for an Earthquake Simulation Grid Marlon PiercenExploring Williams-Beuren Syndrome Using myGrid

58、 Carole GoblenDistributed Data Management and Integration Framework: The Mobius Project Shannon HastingsneBank UK - Linking Research Data, Scholarly Communication and Learning David De RourenUsing the Semantic Grid to Build Bridges between Museums and Indigenous Communities Ronald SchroeternUsing th

59、e Semantic Grid to Build Bridges between Museums and Indigenous Communities Ronald SchroeternCollaborative Tools in the Semantic Grid David De RourenThe Integration of Peer-to-peer and the Grid to Support Scientific CollaborationnOWL-Based Resource Discovery for Inter-Cluster Resource Borrowing Hide

60、ki YOSHIDAnSemantic Annotation of Computational Components Peter VanderbiltnInteroperability and Transformability through Semantic Annotation of a Job Description Language Jeffrey HauJuly 2004IAAI Panel54E-Science Special IssuenIEEE Intelligent Issue Special Issue on E-Science, Jan-Feb 2004nDe Roure