Trends in use of scientific workflows in different science disciplines

Dr Siddeswara Guru1, Igor Makunin 2, David Abramson2, Ben Evans3, Damien Watkins4, llkay Altintas5

1TERN, Brisbane, Australia

2University of Queensland, Brisbane, Australia,,

3 National Computing Infrastructure, Canberra, Australia,

4 Data61 CSIRO, Melbourne, Australia,

5San Diego Supercomputer Center, University of California, San Diego, USA,


A scientific workflow is a series of well-defined coordinated, structured activities that enable scientific problem solving [1]. Scientific workflows have gained wide popularity in the research community for its ability to:

  1. describe, manage, share and execute scientific analyses;
  • Provide high-level abstract view of scientific computation, while hiding underlying details;
  • Interface with distributed computing environment;
  • capture complete workflow as an artefact and make it as a reusable entity [2];
  • capture provenance information for further analysis and knowledge re-use.

There are several Scientific Workflow Management Systems (SWMS) used in science disciplines and some of them are very discipline-centric [3]. The basic functions of SWMS is to design, create, execute and manage workflows. Apart from providing execution environment for workflows, SWMS support additional functionalities such as run-time execution monitoring and reporting, and workflow provenance

In this BoF, we will provide an overview presentation of some of the SWMS (e.g., Kepler, Galaxy, Vis Trails, Cylc) used in different science disciplines. Furthermore, we will run an interactive Q&A panel discussion to understand motivations and use cases where scientific workflows are used, choosing a right tool for particular application, building a community around workflow management system and future activities for more co-ordination in tools development.

BoF Details:

  • The BoF will have a keynote talk from llkay Altintas followed by four short presentations on Galaxy, VisTrails, Workspace and Cylc used in different science discipline and a panel discussion. All the speakers will form a panel with additional.
  • The BoF will run for 90 minutes with 30 minutes of Keynote talk followed by 20 minutes of short presentations and remaining time for panel discussion.


  1. Talia, D. Workflows Systems for Science: Concepts and Tools. ISRN Software Engineering, 2013.
  2. Guru, S.M., I.C. Hanigan, H.A. Nguyen, E. Burns, J. Stein, W. Blanchard, D. B. Lindenmayer, and T. Clancy, Development of a cloud-based platform for reproducible science: the case study of IUCN Red List of Ecosystems Assessment. Ecological Informatics, 2016.
  3. Liu, J., E. Pacitti, P. Valduriez, M. Mattoso, A Survey of Data-Intensive Scientific Workflow Management. Journal of Grid Computing, 2015,13:4, p. 457-493.


Siddeswara Guru is a Data Science Director for the Terrestrial Ecosystem Research Network (TERN). He initiates, coordinates and manages ecological data, e-infrastructure and synthesis projects apart from overseeing the data and information management activities across TERN.

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