Building Scientific Workflow with Taverna and BPEL: A Comparative Study in caGrid

  • Wei Tan
  • Paolo Missier
  • Ravi Madduri
  • Ian Foster
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5472)


With the emergence of “service oriented science,” the need arises to orchestrate various services to facilitate scientific investigation – that is, to create “science workflows.” In this paper we summarize our findings in providing a workflow solution for the caGrid service-based grid infrastructure. We choose BPEL and Taverna as candidate solutions, and compare their usability in the full lifecycle of a scientific workflow, including service discovery, service composition, workflow execution, and workflow result analysis. We determine that BPEL offers a comprehensive set of primitives for modeling processes of all flavors, while Taverna provides a more compact set of primitives and a functional programming model that eases data flow modeling. We hope that our analysis not only helps researchers choose a tool that meets their needs, but also provides some insight on how a workflow language and tool can fulfill the requirement of scientists.


Service Composition Service Discovery Purchase Order Globus Toolkit Implicit Iteration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Krishnan, S., Bhatia, K.: SOAs for Scientific Applications: Experiences and Challenges. In: Proc. IEEE International Conference on e-Science and Grid Computing (2007)Google Scholar
  2. 2.
    Foster, I.: Service-Oriented Science. Science 308(5723), 814–817 (2005)CrossRefGoogle Scholar
  3. 3.
    Tan, W., et al.: Workflow in a Service Oriented Cyberinfrastructure Environment. In: Cao, J. (ed.) Cyberinfrastructure Technologies and Applications. Nova Science Publishers (2008)Google Scholar
  4. 4.
    Saltz, J., et al.: caGrid: design and implementation of the core architecture of the cancer biomedical informatics grid. Bioinformatics 22(15), 1910–1916 (2006)CrossRefGoogle Scholar
  5. 5.
    Foster, I.: Globus Toolkit Version 4: Software for Service-Oriented Systems. Journal of Computer Science and Technology, 2006 21(4), 513–520 (2006)CrossRefGoogle Scholar
  6. 6.
    Taylor, I.J., et al.: Workflows for e-Science: Scientific Workflows for Grids. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  7. 7.
  8. 8.
    Oinn, T., et al.: Taverna/myGrid: aligning a workflow system with the life sciences community. In: Taylor, I.J., et al. (eds.) Workflows for E-science: Scientific Workflows for Grids, pp. 300–319. Springer, Guildford (2007)CrossRefGoogle Scholar
  9. 9.
    OASIS, Web Services Business Process Execution Language Version 2.0 (2007),
  10. 10.
    Turi, D., et al.: Taverna Workflows: Syntax and Semantics. In: Proc. 3rd e-Science Conference, Bangalore, India (2007)Google Scholar
  11. 11.
    Tan, W., et al.: Orchestrating caGrid Services in Taverna. In: Proc. IEEE International Conference on Web Services (ICWS 2008), Beijing, China (2008)Google Scholar
  12. 12.
    Lord, P., et al.: Feta: A light-weight architecture for user oriented semantic service discovery. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 17–31. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  13. 13.
    Wolstencroft, K., et al.: The myGrid ontology: bioinformatics service discovery. International Journal of Bioinformatics Resesearch and Applications 3(3), 303–325 (2007)CrossRefGoogle Scholar
  14. 14.
    Shields, M.: Control- Versus Data-Driven Workflows in Workflows for E-science: Scientific Workflows for Grids. In: Taylor, I.J., et al. (eds.), pp. 167–173. Springer, Heidelberg (2007)Google Scholar
  15. 15.
    Simmhan, Y., Plale, B., Gannon, D.: A survey of data provenance in e-science. SIGMOD Record 34(3), 31–36 (2005)CrossRefGoogle Scholar
  16. 16.
    Missier, P., et al.: Data lineage model for Taverna workflows with lightweight annotation requirements. In: Proc. Second International Provenance and Annotation Workshop, University of Utah, Salt Lake City, Utah (2008)Google Scholar
  17. 17.
    Zhao, J., et al.: Using semantic web technologies for representing E-science provenance. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 92–106. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  18. 18.
    Tan, W., Fong, L., Bobroff, N.: BPEL4Job: A fault-handling design for job flow management. In: Krämer, B.J., Lin, K.-J., Narasimhan, P. (eds.) ICSOC 2007. LNCS, vol. 4749, pp. 27–42. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Wei Tan
    • 1
  • Paolo Missier
    • 2
  • Ravi Madduri
    • 3
  • Ian Foster
    • 1
  1. 1.Computation InstituteUniversity of Chicago and Argonne National LaboratoryChicagoUSA
  2. 2.School of Computer ScienceUniversity of ManchesterManchesterUK
  3. 3.Mathematics and Computer Science Division, Argonne National LaboratoryArgonneUSA

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