Taverna Workbench

Information about Taverna Workbench

Published on June 15, 2007

Author: Abbott

Source: authorstream.com

Content

Taverna Workbench:  Taverna Workbench Stuart Owen University of Mancester, UK [email protected] What is a workflow:  What is a workflow Data workflows A task is invoked once its expected data has been received, and when complete passes any resulting data downstream. B starts when it receives data from A. C and D run in parallel when they receive data from B E starts once its received data from both C and D. Control workflows A task is invoked once its dependant tasks have completed. B starts when A has completed. C and D run in parallel once B has completed E starts once both C and D have completed. A B C D E F Advantages of workflows:  Advantages of workflows Advantages to workflows:  Advantages to workflows High-level abstraction Easier to understand and modify. Easier to describe and discuss with others. Describes what you want to do, not how to do it. Automation Sytematic Sharing and re-use Either on its own, or within other workflows! Workflows within Taverna:  Workflows within Taverna Predominantly based around the flow of data, but does allow control constraints as well. Service oriented workflows. Services may or not be grid enabled. High-level GUI approach seperated from lower level coding, you don’t have to be a coder to build a workflow. Enactment can take place separate to the GUI, allowing workflows to be executed from the command line or within other systems. Slide6:  Taverna 1.4 Workbench:  Taverna 1.4 Workbench Integral part of the myGrid project Java based, runs on Windows, Mac OS, Linux, Solaris Open source and user driven development Taverna in OMII-UK Dedicated team of developers focused on design, implementation, testing and support – leading to production quality software. Development of Taverna 2.0 Taverna 1.4 workbench:  Taverna 1.4 workbench SCUFL :  Freefluo Workflow enactor Scufl + Workflow Object Model Processor Processor Web Service Soap lab Processor Local App Processor Enactor Taverna Workbench Processor Bio MOBY Processor ? SCUFL Application data flow layer Scufl graph + service introspection Execution flow layer List management; implicit iteration mechanism; MIME andamp; semantic type decoration; fault management; service alternates Processor invocation layer Workflow Execution (Simple Conceptual Unified Flow Language) Nested workflows:  Nested workflows A processor can be a workflow itself. Encourages the reuse of workflows within a more complex scenario. Greater abstraction of an overall process making it more manageable. Slide11:  Iterations:  Iterations Scufl handles iterations implicitly i.e. Taverna handles it automagically, theres no need for the user to indicate that there is an iteration required. Taverna recognises the data mismatch and repeatedly runs the task over each data element in the list. Iteration stategy with multiple inputs can be configured. 'Cross product' - all against all 'Dot product' – first against first, second against second ….. etc What about when a service fails?:  What about when a service fails? Most services are owned by other people No control over service failure Some are research level Workflows are only as good as the services they connect! To help - Taverna can: Notify failures Instigate retries Set criticality Substitute alternative services Provenance Data?:  Provenance Data? Supports scientific method and best practice Metadata about the origin of a resource (workflow , service, data , experiment hypothesis etc) and the process of how a resource was generated. The Who? , What? , When? ,Where? and Why? about resources. Stored as RDF triples Also available as OWL, opening it up to complex reasoning Typed Workflow Run:  Typed Workflow Run urn:lsid:..:wfInstance:8 runs launchedBy Experimenter belongsTo Organization urn:lsid:…:org:HY7 ProcessRun WorkflowRun Workflow Provenance Ontology runs launchedBy belongsTo executed urn:lsid:…:person:4 urn:lsid:…:workflow:6 urn:lsid:…:processRun:84 urn:lsid:…:processRun:51 executed executed Provenance Browser:  Provenance Browser New plans for Taverna 2.0:  New plans for Taverna 2.0 Evolving challenges:  Evolving challenges Long running data intensive workflows Manipulation of confidential or otherwise protected information Use with classical grid systems Publishing and sharing of workflows Better use of provenance Runtime Service Binding:  Runtime Service Binding Service definition consists of an abstract description Resolved at workflow runtime to one or more concrete resources by a broker Allows load balancing or economic model based service selection over grid environments Processor Dispatch Stack:  Processor Dispatch Stack 3rd party data transfers:  3rd party data transfers Allows ‘in place’ referencing of data Large data sets no longer round-trip between workflow engine and data provider Allows restricted access to sensitive data Automatic de-reference when a reference type is linked to a value type within a workflow. Streaming Data:  Streaming Data Allow execution of downstream workflow stages on partially complete results from upstream. Service 1 Service 2 Service 3 Non streaming (Taverna 1), entire iteration must complete at each stage Streamed data, Service 2 starts operating on partial results from Service 1 Conclusions:  Conclusions Taverna and its source code is free to download. http://taverna.sourceforge.net Taverna is being adopted by a number of different disciplines outside its bio-science origins, including chemoinformatics, social science, astronomy. Open architecture and support for plugins to cope with open world – allows expansion into other areas User driven development Taverna users mailing list Taverna hackers mailing list Production quality software within OMII-UK Acknowledgements:  Acknowledgements The myGrid group, past and present. OMII-UK All our users Carole Goble Katy Wolstencroft Daniele Turi Matthew Gamble Tom Oinn Paul Fisher

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