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Provenance Aware Service Oriented Architecture (1 year on) Professor Luc Moreau University of Southampton

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Presentation on theme: "Provenance Aware Service Oriented Architecture (1 year on) Professor Luc Moreau University of Southampton"— Presentation transcript:

1 Provenance Aware Service Oriented Architecture (1 year on) www.pasoa.org Professor Luc Moreau University of Southampton L.Moreau@ecs.soton.ac.uk

2 The PASOA Team  PASOA Southampton  Simon Miles, Paul Groth, Miguel Branco, Luc Moreau  PASOA Cardiff  Ian Wootten, Shrija Rajbhandari, Omer Rana, David Walker

3 Provenance Definition  Merriam-Webster Online dictionary:  the origin, source;  the history of ownership of a valued object or work of art or literature  The provenance of a piece of data is the process that led to the data  Our aim is to conceive a computer-based representation of provenance that allows us to perform useful analysis and reasoning to support our use cases

4 Provenance Use Cases (1) High Energy Physics: tracking, analysing, verifying data sets in the ATLAS Experiment of the Large Hadron Collider (CERN) Bioinformatics: verification of “experiment validity”.

5 Provenance Use Cases (2) Aerospace engineering: maintain a historical record of design processes, up to 99 years. Organ transplant management: tracking of previous decisions, crucial to maximise the efficiency in matching and recovery rate of patients

6 The Provenance Problem Given a set of services in an open grid environment that are composed in order to produce a given result; How can we determine the process that generated the result? (especially after their composition, i.e., virtual organisation, has been disbanded)

7 Provenance “Lifecycle” Application Results Provenance Store Record Documentation of Execution Query Provenance of Data Manage Store and its contents Core Interfaces to Provenance Store

8  Logical Architecture  Adopted by EU Provenance as strawman [Miles et al. 05]

9 Recording & Querying PReP [Groth et al. 04]  Protocol adopted by application components  Allow for multiple provenance stores (scalability) Query Interface [Miles et al.05]  Purpose  Obtain the provenance of some specific data  Allow for “navigation” of the data structure representing provenance  Abstract interface  Allows us to view the provenance store as if containing XML data structures  Based on XPath and XQuery clientservice invocation result invocation and result recording Provenance Store Provenance Store invocation and result recording

10 Assertions about Performance and Availability  A taxonomy of gathered information about performance  Recorded (invocation start/end time and counts)  Derived from Recorded Information (averages)  Queried against other actor owned metrics  Compilation of assertions in a measure of trust (both from service and client perspective) [Wootten, Rana 05] Trust is a subjective probability that an actor will perform a particular action [Gambetta] [Rajbhandari, Rana 05]

11 PReServ [Groth et al. 05]  Implementation of PReP protocol and Query Interface  Provenance store implemented as a Web Service  Client side libraries for using Provenance Store  Axis Handler for automatically recording communication between Axis-based Web Services Axis Handler Axis Handler Provenance Service Backend Store Interface File System Store In- Memory Store … Backend Stores PS Client Side Library PS Client Side Library Web Service WS Client Query Actor WS PS Client Side Library WS Calls Java Calls

12 Bioinformatics Application  Bioinformatics workflow studying compressibility of biological sequences  Implemented as a VDT workflow, scheduled by Condor  Each service, script, command records provenance [HPDC’05]

13 Bioinformatics Application (2)  Use Cases  Algorithm verification  A bioinformatician, A, downloads a protein sequence from the RefSeq database and runs the compressibility experiment.  A later performs the same experiment on the same sequence data, again downloaded from RefSeq.  A compares the two experiment results and notices a difference.  A determines whether the difference was caused by the algorithms used to process the sequence data having been changed.

14 Bioinformatics Application (3)  Recording Scalability  Querying Scalability

15 Other Applications  EU Provenance project  Pre-prototype about baking cakes  e-Demand  Detect sharing of services in workflow execution to offer more resilient execution [Townend et al 05] [Xu et al 05]

16 Conclusions  Mostly unexplored area that is crucial to develop trusted systems  Current work:  System and protocol designing, architecture specification, generic support for use cases  Pursue the deployment in concrete application and performance evaluation  Download our software from www.pasoa.orgwww.pasoa.org  Tell us about your use cases: we are keen to find new collaborations in this space!

17  Talk to Paul and Simon

18 Publications 1.Paul Groth, Simon Miles, Weijian Fang, Sylvia C. Wong, Klaus-Peter Zauner, and Luc Moreau. Recording and Using Provenance in a Protein Compressibility Experiment. In Proceedings of the 14th IEEE International Symposium on High Performance Distributed Computing (HPDC'05), July 2005. 2.Paul T. Groth. Recording Provenance in Service-Oriented Architectures. 9 Month Report, University of Southampton; Faculty of Engineering, Science and Mathematics; School of Electronics and Computer Science, 2004. 3.Paul Groth, Michael Luck, and Luc Moreau. A protocol for recording provenance in service-oriented Grids. In Proceedings of the 8th International Conference on Principles of Distributed Systems (OPODIS'04), Grenoble, France, December 2004. 4.Paul Groth, Michael Luck, and Luc Moreau. Formalising a protocol for recording provenance in Grids. In Proceedings of the UK OST e-Science second All Hands Meeting 2004 (AHM'04), Nottingham, UK, September 2004. 5.Simon Miles, Paul Groth, Miguel Branco, and Luc Moreau. The requirements of recording and using provenance in e-Science experiments. Technical report, University of Southampton, 2005. 6.Luc Moreau, Syd Chapman, Andreas Schreiber, Rolf Hempel, Omer Rana, Lazslo Varga, Ulises Cortes, and Steven Willmott. Provenance-based Trust for Grid Computing --- Position Paper. In, 2003. 7.Paul Townend, Paul Groth, and Jie Xu. A Provenance-Aware Weighted Fault Tolerance Scheme for Service-Based Applications. In Proc. of the 8th IEEE International Symposium on Object-oriented Real-time distributed Computing (ISORC 2005), May 2005.


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