Skip to main content

Scientific Workflows

  • Reference work entry
  • First Online:
  • 50 Accesses

Synonyms

Grid workflow; In silico experiment

Definition

A scientific workflow is the description of a process for accomplishing a scientific objective, usually expressed in terms of tasks and their dependencies. Typically, scientific workflow tasks are computational steps for scientific simulations or data analysis steps. Common elements or stages in scientific workflows are acquisition, integration, reduction, visualization, and publication (e.g., in a shared database) of scientific data. The tasks of a scientific workflow are organized (at design time) and orchestrated (at runtime) according to dataflow and possibly other dependencies as specified by the workflow designer. Workflows can be designed visually, e.g., using block diagrams, or textually using a domain-specific language.

Historical Background

Workflows have a long history in the database community and in business process modeling, in which case they are sometimes called business workflowsto distinguish them from...

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   4,499.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   6,499.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Recommended Reading

  1. Bonner AJ, Shrufi A, Rozen S. LabFlow-1: a database benchmark for high-throughput workflow management. In: Advances in Database Technology, Proceedings of the 5th International Conference on Extending Database Technology; 1996. p. 463–78.

    Chapter  Google Scholar 

  2. Fox GC, Gannon D, editors. Concurrency and computation: practice and experience. Spec Issue Workflow Grid Systems. 2006;18(10):1009–1019.

    Google Scholar 

  3. Gil Y, Deelman W, Ellisman W, Fahringer T, Fox G, Gannon D, Goble C, Livny M, Moreau L, Myers J. Examining the challenges of scientific workflows. Computer. 2007;40(12):24–32.

    Article  Google Scholar 

  4. Houstis E, Gallopoulos E, Bramley R, Rice J. Problem-solving environments for computational science. IEEE Comput Sci Eng. 1997;4(3):18–21.

    Article  Google Scholar 

  5. Ioannidis YE, Livny M. MOOSE: modeling objects in a simulation environment. In: IFIP Congress, Ritter GX, editors. North-Holland; 1989. p. 821–6.

    Google Scholar 

  6. Ioannidis YE, Livny M, Gupta S, Ponnekanti N. ZOO: a desktop experiment management environment. In: Proceedings of the 22th International Conference on Very Large Data Bases; 1996. p. 274–85.

    Google Scholar 

  7. Ludäscher B, Goble C, editors. ACM SIGMOD Rec. 2005;34(3):44–9. Special Issue on Scientific Workflows.

    Google Scholar 

  8. Medeiros CB, Vossen G, Weske M. WASA: a workflow-based architecture to support scientific database applications. In: Proceedings of the 6th International Conference on Database and Expert Systems Applications; 1995. p. 574–83.

    Google Scholar 

  9. Nakagawa AS. LIMS: implementation and management. Cambridge: The Royal Society of Chemistry, Thomas Graham House, The Science Park, CB4 4WF; 1994.

    Google Scholar 

  10. Shoshani A, Olken F, Wong HKT. Characteristics of scientific databases. In: Proceedings of the 10th International Conference on Very Large Data Bases; 1984. p. 147–60.

    Google Scholar 

  11. Taylor I, Deelman E, Gannon D, Shields M, editors. Workflows for e-Science: scientific workflows for grids. Berlin: Springer; 2007.

    Google Scholar 

  12. Wainer J, Weske M, Vossen G, Medeiros CB. Scientific workflow systems. In: Proceedings of the NSF Workshop on Workflow and Process Automation in Information Systems: State of the Art and Future Directions; 1996.

    Google Scholar 

  13. Wiener JL, Ioannidis YE. A moose and a fox can aid scientists with data management problems. In: Proceedings of the 4th International Workshop on Database Programming Languages; 1993. p. 376–98.

    Chapter  Google Scholar 

  14. Yu J, Buyya R. A taxonomy of scientific workflow systems for grid computing. ACM SIGMOD Rec. 2005;34(3):44–9. Special Issue on Scientific Workflows.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bertram Ludäscher .

Editor information

Editors and Affiliations

Section Editor information

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Ludäscher, B., Bowers, S., McPhillips, T. (2018). Scientific Workflows. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_1471

Download citation

Publish with us

Policies and ethics