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San Diego Supercomputer Center. Semantic Extensions for Scientific Workflows on the Grid. Bertram Ludäscher ([email protected]). UC DAVIS Department of Computer Science. Associate Professor Dept. of Computer Science & Genome Center University of California, Davis Fellow - PowerPoint PPT Presentation
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Semantic Extensions for Scientific Workflows on the GridBertram Ludscher([email protected])Associate ProfessorDept. of Computer Science & Genome CenterUniversity of California, Davis
FellowSan Diego Supercomputer CenterUniversity of California, San DiegoUC DAVISDepartment ofComputer Science
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
OverviewScience Environment for Ecological Knowledge (SEEK)
Scientific Workflows What are they?Why do we need them?
The Kepler Scientific Workflow System
Adding Semantics to Scientific Workflows
Science Environment for Ecological KnowledgeLarge collaborative NSF/ITR (2002-2007)
Bringing together ecologists, IT experts, CS researchers,
SEEK.ecoinformatics.org
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
SEEK: Multidisciplinary research to facilitate
Access to ecological, environmental, and biodiversity dataEnable data sharing & re-useEnhance data discovery at global scales
Scalable analysis and synthesis Taxonomic, Spatial, Temporal, Conceptual integration of data, addressing data heterogeneity issuesEnable communication and collaboration for analysisEnable re-use of analytical components
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
SEEK Main Components KeplerProblem-solving environment for scientific data analysis and visualization scientific workflows
EcoGrid* Distributed data network for environmental, ecological, and systematics dataMaking diverse environmental data systems interoperate
Semantic Mediation SystemSmart data discovery and integration
Knowledge Representation WGTaxon WGBEAM WGEducation, Outreach, Training*name-clash: cf. other Eco-Grid project!
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
OverviewScience Environment for Ecological Knowledge (SEEK)
Scientific Workflows What are they?Why do we need them?
The Kepler Scientific Workflow System
Adding Semantics to Scientific Workflows
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Ecology Scientific Workflow: Invasive Species PredictionSource: NSF SEEK (Deana Pennington et. al, UNM)
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Scientific WorkflowsModel the way scientists work with their data and toolsMentally coordinate export and import of data among software systemsScientific workflows emphasize data flow ( business workflows)Metadata (incl. provenance info, semantic types etc.) is crucial for automated data ingestion, data analysis, Goals: SWF automation, SWF & component reuse, SWF design & documentationmaking scientists data analysis and management easier!
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Commercial & Open Source Scientific Workflow (Dataflow) SystemsKensington Discovery Edition from InforSenseTavernaTriana
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
OverviewScience Environment for Ecological Knowledge (SEEK)
Scientific Workflows What are they?Why do we need them?
The Kepler Scientific Workflow System
Adding Semantics to Scientific Workflows
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Kepler Starting Point: UC Berkeleys Ptolemy II Large, polymorphic component (Actors) and Directors libraries (drag & drop)Directors define the component interaction & execution semantics
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Kepler Scientific Workflows e.g. from Web Services1234 Minute-made (MM) WS-based application integrationSimilarly: MM workflow design & sharing w/o implemented components
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Job Management (here: with NIMROD) Job management infrastructure in place Results database: under development Goal: 1000s of GAMESS jobs (quantum mechanics)
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Some Kepler Actor Additions
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Ecological Niche Model in Kepler(200 to 500 runs per speciesx2000 mammal speciesx3 minutes/run)
=833 to 2083 days
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Grid-enabled KeplerUtilize distributed computing resourcesExecute single steps or sub-workflows on distributed machinesInitially, focus on trivially parallel workflowsSupport collaboration through the formation of ad-hoc grids
ImplementationsPeer to peer using JXTATraditional HPC-based batch job submission (e.g., NIMROD, Condor)KeplerGrid for NicheModeling
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
A GEON Data Analysis Workflow
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Statistics Packages (here: R) in KeplerSource: Dan Higgins, Kepler/SEEK
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ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
KEPLER: An OPEN SOURCE, cross-project collaborationIlkay Altintas SDM, Resurgence, NLADR,Kim Baldridge Resurgence, NMI Chad Berkley SEEK Shawn Bowers SEEKTerence Critchlow SDM Tobin Fricke ROADNetJeffrey Grethe BIRNChristopher H. Brooks Ptolemy II Zhengang Cheng SDM Dan Higgins SEEKEfrat Jaeger GEON Matt Jones SEEK Werner Krebs, EOLEdward A. Lee Ptolemy II Kai Lin GEONBertram Ludaescher SDM, SEEK, GEON, BIRN, ROADNetMark Miller EOLSteve Mock NMISteve Neuendorffer Ptolemy II Jing Tao SEEK Mladen Vouk SDM Xiaowen Xin SDM Yang Zhao Ptolemy IIBing Zhu SEEK Ptolemy IIwww.kepler-project.orgYour Logos& NamesHERE!!!
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
GEON Dataset Generation & Registration (a co-development in KEPLER)Xiaowen (SDM)Edward et al.(Ptolemy)Yang (Ptolemy)Efrat(GEON)Ilkay(SDM)SQL database access (JDBC)Matt,Chad, Dan et al. (SEEK)% Makefile$> ant run
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Kepler todaySupports scientific workflowsEcology, molecular bio, geology, Variety of analytical components (including spatial data transformations)Support for R scripts and Matlab scriptsReal-time data access via Antelope ORBEcoGrid access to heterogeneous dataEML Data supportExperimental data, survey data, spatial raster and vector data, etc.DarwinCore Data supportMuseum collectionsEcoGrid registry to discover data sourcesOntology-based browsing for analytical componentsExploit semantics to improve the user experienceDemonstration workflowsEcology: Ecological Niche Modeling, Biodiversity Analysis, Genomics: Promoter Identification WorkflowGeology: Geologic Map Integration, Rock-type distribution analysisOceanography: Real-time Revelle example of data access
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Kepler soon (this year mostly )Usability engineeringFull evaluation and user-oriented customization of all UI componentsDistributed computing/grid computingLarge jobs, lots of machinesDetached executionSmart data and component discoverySupport annotating data sourcesComponent repository / downloadable componentsAutomated data and service integration and transformation using ontologiesComplete EcoGrid accessFull EML supportSupport for large data and 3rd-party transferMore data sources and types of data sources (e.g., JDBC, GEON data)Provenance and metadata propagation
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Joint Ptolemy/Kepler Meeting (in eigener Sache ;-)
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
OverviewScience Environment for Ecological Knowledge (SEEK)
Scientific Workflows What are they?Why do we need them?
The Kepler Scientific Workflow System
Adding Semantics to Scientific Workflows
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Kepler Actor-Library w/ Concept IndexHow do you find the right component (actor)? Ontology-based actor organization / browsing Simple text-based and concept-based searchingNext: ontology-based workflow designWorkflowComponents(MoML)Ontologies(OWL)Default + OtherSemanticAnnotationsurn idsinstanceexpressions
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Ecological ontologiesWhat was measured (e.g., biomass)Type of measurement (e.g., Energy)Context of measurement (e.g., Psychotria limonensis)How it was measured (e.g., dry weight)
SEEK intends to enable community-created ecological ontologies using OWLRepresents a controlled vocabulary for ecological metadata
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Ontology O (in Description Logic cf. OWL-DL)
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SEEK KR (Knowledge Representation) Working GroupCurrent OntologiesEcological Concepts, Models, NetworksMeasurementsPropertiesStatistical AnalysesTime and SpaceTaxonomic IdentifiersUnitsSymbiosisRecent DevelopmentsBiodiversity (measured traits, computation of traits)Descriptive Terminology for Plant CommunitiesOntology documentationFuture GoalsFill-in existing concepts, evolve the ontology frameworkMore domains
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Need for Semantic Annotations of data & actorsLabel data with semantic types (concept expressions from an ontology)Label inputs and outputs of analytical components with semantic types
Example: Data has COUNT and AREA; workflow wants DENSITY via ontology, system knows that data can still be used (because DENSITY := COUNT/AREA)Use reasoning engines to generate transformation stepsUse reasoning engine to discover relevant componentsDataOntologyWorkflow Components
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
A Scientists Semantic View of ActorsS1 (life stage property)S2 (mortality rate for period)P1P2P4P3P5PhaseObservedPeriodPhasesEggsInstar IInstar IIInstar IIIInstar IVAdults44,0003,5132,5291,9221,4611,300Nymphal{Instar I, Instar II, Instar III, Instar IV}Population samples for life stages of the common field grasshopper [Begon et al, 1996]Periods of development in terms of phaseslife stage periodsk-value for each period of observation[(nymphal, 0.44)]observationsSource: [Bowers-Ludaescher, DILS04]
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Structural Type (XML DTD) AnnotationsS1 (life stage property)S2 (mortality rate for period)P1P2P4P3P5
44,000 0.95 Eggs
root cohortTable= (measurement)*elem measuremnt= (phase, obs)elem phase= xsd:stringelem obs= xsd:integer
Eggs 44,000
structType(P2)structType(P3)Source: [Bowers-Ludaescher, DILS04]
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Semantic Type AnnotationsTake concepts and relationships from an ontology to semantically type the data-in/out ports
Application: e.g., design support: smart/semi-automatic wiring, generation of adaptor actors
Actor(normalize)pinpoutTakes Abundance Count Measurements for Life StagesReturns Mortality Rate DerivedMeasurements for Life StagesSource: [Bowers-Ludaescher, DILS04]
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
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A KR+DI+Scientific Workflow ProblemServices can be semantically compatible, but structurally incompatibleSourceServiceTargetServicePsPtSemantic Type PsSemantic Type PtStructural Type PtStructural Type PsDesired ConnectionIncompatibleCompatible()()(Ps)Ontologies (OWL)Source: [Bowers-Ludaescher, DILS04]
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
The Ontology-Driven FrameworkSourceServiceTargetServicePsPtSemantic Type PsSemantic Type PtStructural Type PtStructural Type PsDesired ConnectionCompatible()RegistrationMapping (Output)RegistrationMapping (Input)CorrespondenceOntologies (OWL)
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Correspondence Example/population/sample == semType(P2) /population/sample/meas/cnt == semType(P2).itemMeasured /population/sample/meas/cnt/text() == semType(P2).itemMeasured.hasCount /population/sample/meas/acc == semType(P2).hasProperty /population/sample/meas/acc/text() == semType(P2).hasProperty.hasValue /population/sample/lsp/text() == semType(P2).hasContext.appliesTo /cohortTable/measurement == semType(P3) /cohortTable/measurement/obs == semType(P3).itemMeasured /cohortTable/measurement/obs/text() == semType(P3).itemMeasured.hasCount /cohortTable/measurement/phase/text() == semType(P3).hasContext.appliesToSourceTarget populationsample *meascntxsd:doublexsd:stringlspxsd:integeracccohortTablemeasurement *obsxsd:integerphasexsd:stringWe want to exploit the semantic information to obtain structural correspondences
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Correspondence Example/population/sample == semType(P2) /population/sample/meas/cnt == semType(P2).itemMeasured /population/sample/meas/cnt/text() == semType(P2).itemMeasured.hasCount /population/sample/meas/acc == semType(P2).hasProperty /population/sample/meas/acc/text() == semType(P2).hasProperty.hasValue /population/sample/lsp/text() == semType(P2).hasContext.appliesTo /cohortTable/measurement == semType(P3) /cohortTable/measurement/obs == semType(P3).itemMeasured /cohortTable/measurement/obs/text() == semType(P3).itemMeasured.hasCount /cohortTable/measurement/phase/text() == semType(P3).hasContext.appliesToSourceTarget populationsample *meascntxsd:doublexsd:stringlspxsd:integeracccohortTablemeasurement *obsxsd:integerphasexsd:string/population/sample == semType(P2)/cohortTable/measurement == semType(P3)These fragments correspond
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Correspondence Example/population/sample == semType(P2) /population/sample/meas/cnt == semType(P2).itemMeasured /population/sample/meas/cnt/text() == semType(P2).itemMeasured.hasCount /population/sample/meas/acc == semType(P2).hasProperty /population/sample/meas/acc/text() == semType(P2).hasProperty.hasValue /population/sample/lsp/text() == semType(P2).hasContext.appliesTo /cohortTable/measurement == semType(P3) /cohortTable/measurement/obs == semType(P3).itemMeasured /cohortTable/measurement/obs/text() == semType(P3).itemMeasured.hasCount /cohortTable/measurement/phase/text() == semType(P3).hasContext.appliesToSourceTarget populationsample *meascntxsd:doublexsd:stringlspxsd:integeracccohortTablemeasurement *obsxsd:integerphasexsd:string/population/sample/meas/cnt == semType(P2).itemMeasured/cohortTable/measurement/obs == semType(P3).itemMeasuredThese fragments correspond
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Correspondence Example/population/sample == semType(P2) /population/sample/meas/cnt == semType(P2).itemMeasured /population/sample/meas/cnt/text() == semType(P2).itemMeasured.hasCount /population/sample/meas/acc == semType(P2).hasProperty /population/sample/meas/acc/text() == semType(P2).hasProperty.hasValue /population/sample/lsp/text() == semType(P2).hasContext.appliesTo /cohortTable/measurement == semType(P3) /cohortTable/measurement/obs == semType(P3).itemMeasured /cohortTable/measurement/obs/text() == semType(P3).itemMeasured.hasCount /cohortTable/measurement/phase/text() == semType(P3).hasContext.appliesToSourceTarget populationsample *meascntxsd:doublexsd:stringlspxsd:integeracccohortTablemeasurement *obsxsd:integerphasexsd:string/population/sample/meas/cnt/text() == semType(P2).itemMeasured.hasCount/cohortTable/measurement/obs/text() == semType(P3).itemMeasured.hasCountThese fragments correspond
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Correspondence Example/population/sample == semType(P2) /population/sample/meas/cnt == semType(P2).itemMeasured /population/sample/meas/cnt/text() == semType(P2).itemMeasured.hasCount /population/sample/meas/acc == semType(P2).hasProperty /population/sample/meas/acc/text() == semType(P2).hasProperty.hasValue /population/sample/lsp/text() == semType(P2).hasContext.appliesTo /cohortTable/measurement == semType(P3) /cohortTable/measurement/obs == semType(P3).itemMeasured /cohortTable/measurement/obs/text() == semType(P3).itemMeasured.hasCount /cohortTable/measurement/phase/text() == semType(P3).hasContext.appliesToSourceTarget populationsample *meascntxsd:doublexsd:stringlspxsd:integeracccohortTablemeasurement *obsxsd:integerphasexsd:string/population/sample/lsp/text() == semType(P2).hasContext.appliesTo/cohortTable/measurement/phase/text() == semType(P3).hasContext.appliesToThese fragments correspond
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Ontology-Guided Data TransformationSourceServiceTargetServicePsPtSemantic Type PsSemantic Type PtStructural Type PtStructural Type PsDesired ConnectionCompatible()Structural/SemanticAssociationStructural/SemanticAssociationCorrespondenceGenerate(Ps)Ontologies (OWL)TransformationSource: [Bowers-Ludaescher, DILS04]
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Linking Structural and Semantic Types : S OSchema elements/Structural type SOntology /Semantic type O
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Propagating Semantic Annotations Given: structural schemas S (input) and S (output), and an ontology Oa semantic annotation : S Oa query annotation q: S SProblem: compute
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
ApplicationsWF design time:Actor Actor connectionsData binding time:Actor Data connections (data binding)WF runtime:semantic tagging of derived data products
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Semantic PropagationInfer annotations for derived products:When a (partial) specification of an actor is given (e.g., as a query q), then exploit this to propagate semantic annotations from S to Tminimize costly semantic annotationcheck for consistencyqTruSannotatedannotatedTraditional LAV query answeringChase & Backchase, e.g., via MARS maps tosource annotationnew targetannotationnquery
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Biodiversity Workflow w/ Query Annotations q
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Annotation Constraint : S O = x (s(x) c(x)) y o(z) % z = x y
s links the variables x to schema elements of Sc is conjunction of comparisons over x and constantso populates the ontology structure O
X : biom[seas=S], S = w X : observation[temporalContext = S : WinterSeason]s(x)c(x)o(z)
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Example (Biodiversity Workflow)
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Scientific Workflow (SWF) Design MethodologySupport SWF design & reuse, via:Structural data types Semantic typesAssociations (=constraints) between them Type checking, inference, propagationSeparation of concerns:structure, semantics, WF orchestration, etc.
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Data IntegrationKnowledgeRepresentationProcess Integration(Scientific Workflows)Src: ECS-289 Scientific Data Management WQ05Data FederationEcoGrid
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Q & A
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KEPLER: An Open CollaborationInitiated by members from DOE SDM/SPA and NSF SEEK; now several other projects (GEON, Ptolemy II, EOL, Resurgence/NMI, )Open Source (BSD-style license)Intensive Communications: Web-archived mailing listsIRC (!)Meetings, HackathonsCo-development: via shared CVS repositoryjoining as a new co-developer (currently):get a CVS account (read-only)local development + contribution via existing KEPLER memberbe voted in as a member/co-developer
Software & social engineeringHow to better accommodate new groups/communities?How to better accommodate different usage/contribution models (core dev special purpose extender user)?
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
GrOWLGraphical Ontology Editing and Browsing Krivov and Villa (UVM)
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Data Procurement using SemanticsFind all datasets that contain abundance measurements of Manica bradleyi inter-ant parasites observed within California
SEEK AHM 2004
SWDBAug 29, 2004
November, 2004
Our Initial Data-Procurement Prototype
Support external services for incorporating information not easily or conveniently expressed using conceptual modeling languages (description logic)
SMS Dataset Discovery
Dataset Repository
Dataset Query Expression
Semantic Descriptions
External Services
Semantic Conversions
Ontology Repository
Relevant Datasets/Data
ConversionRules
SEEK AHM 2004
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Results
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Ontologies
Expressed in OWL, shown here graphicallyThis is a simple OWL ontology (in terms of formulas)
prop
Observation
SpatialContext
GeoSpatialRegion
GeoCoordPoint
LatLonPoint
UTMPoint
context
location
xsd:float
xsd:float
latDeg
lonDeg
xsd:float
xsd:float
UTMx
UTMy
xsd:int
xsd:int
zone
region
xsd:string
value
ObservableItem
item
EcoProperty
property
TaxonID
EcoEntity
Abundance
SciName
xsd:string
xsd:string
genus
species
property
SciName
Parasite
Host
InquilinismHost
InquilinismParasite
parasiteOf
inquilinismOf
parasiteOf
inquilinismOf
isa
role
Host
class
SEEK AHM 2004
SWDBAug 29, 2004
November, 2004
Results
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Related PublicationsScientific WorkflowsScientific Workflow Management and the Kepler System, B. Ludscher, I. Altintas, C. Berkley, D. Higgins, E. Jaeger-Frank, M. Jones, E. Lee, J. Tao, Y. Zhao, Concurrency and Computation: Practice & Experience, Special Issue on Scientific Workflows, to appear, 2005. A Framework for the Design and Reuse of Grid Workflows, Ilkay Altintas, Adam Birnbaum, Kim Baldridge, Wibke Sudholt, Mark Miller, Celine Amoreira, Yohann Potier, and Bertram Ludaescher, Intl. Workshop on Scientific Applications on Grid Computing (SAG'04), LNCS 3458, Springer, 2005 Kepler: An Extensible System for Design and Execution of Scientific Workflows, I. Altintas, C. Berkley, E. Jaeger, M. Jones, B. Ludscher, S. Mock, 16th International Conference on Scientific and Statistical Database Management (SSDBM'04), 21-23 June 2004, Santorini Island, Greece. Kepler: Towards a Grid-Enabled System for Scientific Workflows, Ilkay Altintas, Chad Berkley, Efrat Jaeger, Matthew Jones, Bertram Ludscher, Steve Mock, Workflow in Grid Systems (GGF10), Berlin, March 9th, 2004.An Ontology-Driven Framework for Data Transformation in Scientific Workflows, S. Bowers and B. Ludscher, Intl. Workshop on Data Integration in the Life Sciences (DILS'04), March 25-26, 2004 Leipzig, Germany, LNCS 2994. A Web Service Composition and Deployment Framework for Scientific Workflows, I. Altintas, E. Jaeger, K. Lin, B. Ludaescher, A. Memon, In the 2nd Intl. Conference on Web Services (ICWS), San Diego, California, July 2004.
ISGC2005, April 25-29, 2005SWDBAug 29, 2004http://seek.ecoinformatics.org
Related PublicationsSemantic Data Registration and IntegrationOn Integrating Scientific Resources through Semantic Registration, S. Bowers, K. Lin, and B. Ludscher, 16th International Conference on Scientific and Statistical Database Management (SSDBM'04), 21-23 June 2004, Santorini Island, Greece. A System for Semantic Integration of Geologic Maps via Ontologies, K. Lin and B. Ludscher. In Semantic Web Technologies for Searching and Retrieving Scientific Data (SCISW), Sanibel Island, Florida, 2003. Towards a Generic Framework for Semantic Registration of Scientific Data, S. Bowers and B. Ludscher. In Semantic Web Technologies for Searching and Retrieving Scientific Data (SCISW), Sanibel Island, Florida, 2003. The Role of XML in Mediated Data Integration Systems with Examples from Geological (Map) Data Interoperability, B. Brodaric, B. Ludscher, and K. Lin. In Geological Society of America (GSA) Annual Meeting, volume 35(6), November 2003. Semantic Mediation Services in Geologic Data Integration: A Case Study from the GEON Grid, K. Lin, B. Ludscher, B. Brodaric, D. Seber, C. Baru, and K. A. Sinha. In Geological Society of America (GSA) Annual Meeting, volume 35(6), November 2003. Query Planning and RewritingProcessing First-Order Queries under Limited Access Patterns, Alan Nash and B. Ludscher, Proc. 23rd ACM Symposium on Principles of Database Systems (PODS'04) Paris, France, June 2004. Processing Unions of Conjunctive Queries with Negation under Limited Access Patterns, Alan Nash and B. Ludscher., 9th Intl. Conference on Extending Database Technology (EDBT'04) Heraklion, Crete, Greece, March 2004, LNCS 2992. Web Service Composition Through Declarative Queries: The Case of Conjunctive Queries with Union and Negation, B. Ludscher and Alan Nash. Research abstract (poster), 20th Intl. Conference on Data Engineering (ICDE'04) Boston, IEEE Computer Society, April 2004.
Im going to talk about some of the work weve been doing using ontologies to help make scientific workflows easier to design and usesemType(P2) subtype_of semtype(P3)