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Workflow in Grid Systems Workshop
Dave Berry, Research ManagerUK National e-Science Centre
GGF10, Mar 2004
Outline: Welcome
WelcomeAimsProgramme
“E-Science Workflow Services”BackgroundStructureIssues arising
AimsReport on current work
Find areas of agreementIdentify open issues
Look for opportunitiesResearchDevelopmentCollaboration
OutcomesSample workflowsCP&E special issueInput to RGs and WGs ?
Morning Session
TalksArchitectureApplications
Possible panel topics:ScriptingSecurityDebuggingConstraint Modelling
DiscussionIssues
Afternoon session
TalksLanguages (esp. BPEL)Tools & Enactment
Possible panel topics:Adaptive enactmentWorkflow inferenceEvent-driven enactmentIncorporating devices & human input
DiscussionOutcomes
Outline:“E-Science Workflow Services”
WelcomeAimsProgramme
“E-Science Workflow Services”BackgroundStructureIssues arising
E-Science Workflow Services
> 90 participantsIndustryUK e-ScienceInternational e-Science
OrganisersDave Berry (NeSC)Savas Parastatidis (NEReSC)
Written report In progressUK e-Science Series
December 3-5, 2003
e-Science Institute
e-Science Institute
Speakers
IndustryWfMC, WS-Choreography
UK e-ScienceMyGrid/Taverna, GeoDise, DiscoveryNet, DAME, ICENI, Planning, RealityGrid, JIGSA, OGSA-DAI, Triana, AstroGrid
International e-ScienceChimera/Pegasus, BIRN, Kepler/Ptolemy, Thetis, Narada
ResearchOperational research, Workflow and VO’s
Breakout Sessions
Scientific Workflow Requirements
Carole Goble
Protocols in Scientific Workflows
John Brooke
Workflow Languages and Engines
Matthew Addis
User requirementsReflect the modelling paradigm of the scientist.
Varies between experiments, disciplines
Which user would that be?Creators, users, auditors, validators (I know if its right when I see it)Biologists cf. bioinformaticians, and transitioning between
Different users, different environmentsAppropriate levels of abstraction.
User models -> workflow models
Simple to use & intuitive creation, deployment, execution and debugging environments
A Scientist Writes…
“Work in my problem solving environment so that I don’t need to change the way I work.”
Scientific Workflow lifecycles
Incrementally exploratory prototypesGot the data, now get the Nature paper before the next guy
Large scale productionGot the idea, now get the data for many experiments, teams, communities
Migration from one to the otherCapture of prototype for later non-interactive replay in a parameterised fashion
Different parts of the lifecycle May use different environments and policiesDifferent sorts of users will interact
User interaction
Creation & DiscoveryBy example, plagiarism, drag and drop
Collaborative multi-user interaction in creationReusing workflows -> modularisationReusing workflows with different parameters and dataComposing workflows from different areas, disciplines and scales“eXtreme team workflow creation”
Single User interaction with workflow executionChoice between paths of execution in specific statesParameter modification mid-run
Collaborative multi-user interaction during execution?
Characterising Scientific Workflows
Very large amounts of dataFiles, streams, database queriesGridFTP, http, ftp, sockets …Sometimes it's the computation that needs to be moved to the data
Data model and typesMetadataProvenance
DriversScientific questions, outcomes and vanityMore creators than users in science?
Enactment Stack
Goals
Abstract flows
Concrete flows
Process execution
Service descriptions
Messages
Communications
Po
licies a
nd
secu
rity
On
tolo
gie
s, me
tad
ata
, de
scriptio
ns,
info
rma
tion
service
s
Workflow vs. Service“Perform” document
Transformed result of query 2
Stored procedure
Result of query 1 OGSA-DAI
Service
Questions?
Presentations from the workshop: http://www.nesc.ac.uk/action/esi/con
tribution.cfm?Title=303