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Exploring Workflow Interoperability for Neuroimage Analysis on the SHIWA Platform

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Abstract

Neuroimaging is a field that benefits from distributed computing infrastructures (DCIs) to perform data processing and analysis, which is often achieved using Grid workflow systems. Collaborative research in neuroimaging requires ways to facilitate exchange between different groups, in particular to enable sharing, re-use and interoperability of applications implemented as workflows. The SHIWA project provides solutions to facilitate sharing and exchange of workflows between workflow systems and DCI resources. In this paper we present and analyse how the SHIWA Platform was used to implement various cases in which workflow exchange supports collaboration in neuroscience. The SHIWA Platform and the implemented solutions are described and analysed from a “user” perspective, in this case workflow developers and neuroscientists. We conclude that the platform in its current form is valuable for these cases, and we identify remaining challenges.

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References

  1. Belloum, A., Inda, M.A., Vasunin, D., Korkhov, V., Zhao, Z., H.Rauwerda, Breit, T.M., Bubak, M., Hertzberger, L.O.: Collaborative e-Science Experiments and Scientific Workflows. IEEE Internet Comput. 15(4), 39–47 (2011)

    Article  Google Scholar 

  2. Baduel, L., Baude, F., Caromel, D., Contes, A., Huet, F., Morel, M., Quilici, R.: Grid Computing: Software Environments and Tools, chapter Programming, Deploying, Composing, for the Grid. Springer-Verlag (2006)

  3. Barga, R., Gannon, D.: Scientific versus business workflows. In: Taylor, I. et al. (eds.) Workflows for e-Science, pp. 9–18. Springer London (2007)

  4. Basney, J., Humphrey, M., Welch, V.: The MyProxy online credential repository. Softw. Pract. Ex. 35(9), 801–816 (2005)

    Article  Google Scholar 

  5. Behrens, T.E.J., Johansen, H., Berg, Jbabdi, S., Rushworth, M.F.S., Woolrich, M.W.: Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? Neuroimage 34(1), 144–155 (2007)

    Article  Google Scholar 

  6. Deelman, E., Singh, G., hui Su, M., Blythe, J., Gil, Y., Kesselman, C., Mehta, G., Vahi, K., Berriman, G.B., Good, J., Laity, A., Jacob, J.C., Katz, D.S.: Pegasus: a framework for mapping complex scientific workflows onto distributed systems. Sci. Program. J. 13, 219–237 (2005)

    Google Scholar 

  7. Delaitre, T., Kiss, T., Goyeneche, A., Terstyanszky, G., Winter, S., and Kacsuk, P.: Gemlca: running legacy code applications as Grid services. J. Grid Comput. 3(1–2), 75–90 (2005)

    Article  Google Scholar 

  8. Riedel, M. (ed.): International Grid Interoperability and Interoperation Workshop. IEEE: Indianapolis, USA (2008)

  9. Elmroth, E., Hernández, F., Tordsson, J.: Three fundamental dimensions of scientific workflow interoperability: model of computation, language, and execution environment. Future Gener. Comput. Syst. 26(2), 245–256 (2010)

    Article  Google Scholar 

  10. Redolfi, A., et al.: Grid infrastructures for computational neuroscience: the neuGRID example. Future Neurol. 4(6), 703–722 (2009)

    Article  Google Scholar 

  11. Fernando, S.D.I., Creager, D.A., Simpson, A.C.: Towards build-time interoperability of workflow definition languages. In: Negru, V. et al. (eds.) SYNASC 2007, 9th International Symposium on Symbolic and Numberic Algorithms for Scientific Computing, pp. 525–532 (2007)

  12. Glatard, T., Montagnat, J., Lingrand, D., Pennec, X.: Flexible and efficient workflow deployement of data-intensive applications on Grids with MOTEUR. Int. J. High Perform. Comput. Appl. 22(3), 347–360 (2008)

    Article  Google Scholar 

  13. Goecks, J., Nekrutenko, A., Taylor, J., The Galaxy Team: Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 11(8), R86 (2010)

    Article  Google Scholar 

  14. Hoheisel, A.: Grid workflow execution service – dynamic and interactive execution and visualization of distributed workflows. In: Proceedings of the Cracow Grid Workshop 2006, Academic Computer Center CYFRONET AGH, vol. II, pp. 13–24 (2007)

  15. Jordan, D., Evdemon, J. (chairs): Web Services Business Process Execution Language version 2.0. http://docs.oasis-open.org/wsbpel/2.0/wsbpel-v2.0.pdf (2013)

  16. Plankensteiner, K., Montagnat, J., Prodan, R.: IWIR: a language enabling portability across Grid workflow systems. In: Proceedings of 6th Workshop on Workflows in Support of Large-Scale Science (WORKS’11) as a part of Supercomputing’11 Conference. Seattle, USA (2011). doi:10.1145/2110497.2110509

  17. Kacsuk, P., Sipos, G.: Multi-Grid, multi-user workflows in the P-GRADE Grid portal. J Grid Comput. 3, 221–238 (2005)

    Article  Google Scholar 

  18. Krefting, D. et al.: MediGRID: towards a user friendly secured Grid infrastructure. Future Gener. Comput. Syst. 25, 326–336 (2009)

    Article  Google Scholar 

  19. Krefting, D., Glatard, T., Korkhov, V., Montagnat, J., Olabarriaga, S.: Enabling Grid interoperability at workflow level. In: Proceedings of Grid Workflow Workshop’11. Cologne, Germany (2011)

  20. Krefting, D., Luetzkendorf, R., Peter, K., Bernarding, J.: Performance analysis of diffusion tensor imaging in an academic production Grid. In: Proceedings of 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, pp. 751–756. Melbourne, VIC, Australia IEEE Computer Society Conference Publishing Services (CPS) (2010)

  21. Kukla, T., Kiss, T., Terstyanszky, G., Kacsuk, P.: A general and scalable solution for heterogeneous workflow invocation and nesting. In: Proceedings of 3rd Workshop on Workflows in Support of Large-Scale Science (WORKS’08), pp. 1–8 (2008)

  22. Ludäscher, B., Altintas, I., Berkley, C., Higgins, D., Jaeger, E., Jones, M., Lee, E.A., Tao, J., Zhao, Y.: Scientific workflow management and the kepler system. Concurr. Comput. Pract. Ex. 18(10), 1039–1065 (2006)

    Article  Google Scholar 

  23. Luetzkendorf, R., Bernarding, J., Hertel, F., Viezens, F., Thiel, A., Krefting, D.: Enabling of Grid based diffusion tensor imaging using a workflow implementation of FSL. In: Proceedings of HealthGrid 2009, Studies in Health Technology and Informatics, vol. 147, pp. 72–81 (2009)

  24. Oinn, T., Greenwood, M., Addis, M., et al.: Taverna: lessons in creating a workflow environment for the life sciences. J. Concur. Comput. Pract. Ex. 18(10), 1067–1100 (2006). Special Issue on Workflow in Grid Systems

    Article  Google Scholar 

  25. Olabarriaga, S., Glatard, T., Hoheisel, A., Nederveen, A., Krefting, D.: Crossing healthGrid borders: early results in medical imaging. In: Proceedings of HealthGrid’09, Studies in Health Technology and Informatics, vol. 147, pp. 62–71. Berlin (2009)

  26. Olabarriaga, S.D., Glatard, T., de Boer, P.T., A virtual laboratory for medical image analysis. IEEE Trans. Inf. Technol. Biomed. 14(4), 979–985 (2010)

    Article  Google Scholar 

  27. Klingenstein, K., Gannon, D., et al.: Improving interoperability, sustainability and platform convergence in scientific and scholarly workflow. NSF/Mellon Workshop on Scientific and Scholarly Workflow. https://spaces.internet2.edu/display/SciSchWorkflow/Home (2007)

  28. Rex, D., Ma, J., Toga, A.: The LONI pipeline processing environment. Neuroimage 19(3), 1033–1048 (2003)

    Article  Google Scholar 

  29. De Roure, D., Goble, C., Stevens, R.: The design and realisation of the myexperiment virtual research environment for social sharing of workflows. Future Gener. Comput. Syst. 25(5), 561–567 (2009)

    Article  Google Scholar 

  30. SHIWA Portal: http://ssp.shiwa-workflow.eu/ (2013)

  31. SHIWA project: http://www.shiwa-workflow.eu/ (2013)

  32. SHIWA Repository: http://repo.shiwa-workflow.eu/ (2013)

  33. SHIWA Simulation Platform: http://www.shiwa-workflow.eu/wiki/-/wiki/Main/SHIWA+Simulation+Platform (2013)

  34. Smith, S.M., et al.: Advances in functional and structural mr image analysis and implementation as fsl. Neuroimage 23(S1), 208–219 (2004)

    Article  Google Scholar 

  35. Fahringer, T., Jugravu, A., Pllana, S., Prodan, R., Seragiotto, Jr., C., Truong, H.-L.: ASKALON: a tool set for cluster and Grid computing. Concurr. Comput. Pract. Ex. 17(2–4), 143–169 (2005)

    Article  Google Scholar 

  36. Taylor, I., Shields, M., Wang, I., Harrison, A.: The triana workflow environment: architecture and applications. In: Taylor, I., Deelman, E., Gannon, D., Shields, M. (eds.) Workflows for e-Science, pp. 320–339. Springer, New York, Secaucus, NJ, USA (2007)

  37. Korkhov, V., Krefting, D., Kukla, T., Terstyanszky, G., Caan, M., Olabarriaga, S.: Exploring workflow interoperability tools for neuroimaging data analysis. In: Proceedings of 6th Workshop on Workflows in Support of Large-Scale Science (WORKS’11) as a part of Supercomputing’11 Conference, pp. 87–96. Seattle, USA (2011). doi:10.1145/2110497.2110508

  38. Korkhov, V., Vasyunin, D., Wibisono, A., Guevara-Masis, V., Belloum, A., de Laat, C., Adriaans, P., Hertzberger, L.O.: WS-VLAM: towards a scalable workflow system on the Grid. In: Proceedings of the 2nd workshop on Workflows in Support of Large-Scale Science (WORKS07), 16th IEEE International Symposium on High Performance Distributed Computing, pp. 63–68 (2007)

  39. Wibisono, A., Vasyunin, D., Korkhov, V., Zhao, Z., Belloum, A., Laat, C., Adriaans, P., Hertzberger, B.: WS-VLAM: A GT4 based workflow management system. In: Shi, Y., van Albada, D., Dongarra, J., Sloot, P.M.A. (eds.) Computational Science ICCS 2007. Lecture Notes in Computer Science, vol. 4489, pp. 191–198. Springer Berlin Heidelberg (2007)

  40. Zhao, Z., Belloum, A., de Laat, C., Adriaans, P., Hertzberger, B.: Using Jade agent framework to prototype an e-Science workflow bus. In: CCGrid, Rio de Janeiro, Brazil, pp. 655–660. IEEE (2007)

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Authors and Affiliations

  1. Faculty of Applied Mathematics and Control Processes, St. Petersburg State University, Universitetskii prospekt 35, Petergof, 198504, St. Petersburg, Russia

    Vladimir Korkhov

  2. Academic Medical Center, University of Amsterdam, PO Box 22700, 1100 DE, Amsterdam, The Netherlands

    Vladimir Korkhov, Matthan W. A. Caan & Silvia D. Olabarriaga

  3. University of Applied Sciences Berlin, Wilhelminenhofstraße 75A, 12459, Berlin, Germany

    Dagmar Krefting

  4. Centre for Parallel Computing, University of Westminster, 115 New Cavendish St, W1W 6UAW, London, UK

    Tamas Kukla & Gabor Z. Terstyanszky

Authors
  1. Vladimir Korkhov
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  2. Dagmar Krefting
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  3. Tamas Kukla
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  4. Gabor Z. Terstyanszky
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  5. Matthan W. A. Caan
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  6. Silvia D. Olabarriaga
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Correspondence to Vladimir Korkhov.

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Korkhov, V., Krefting, D., Kukla, T. et al. Exploring Workflow Interoperability for Neuroimage Analysis on the SHIWA Platform. J Grid Computing 11, 505–522 (2013). https://doi.org/10.1007/s10723-013-9262-7

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  • DOI: https://doi.org/10.1007/s10723-013-9262-7

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