Kepler Scientific Workflow Platform

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A Kepler Scientific Workflow Platform is a scientific workflow platform.



References

2023

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    • Q: Describe the Kepler Scientific Workflow Platform
    • A: Kepler is a scientific workflow platform developed by the National Science Foundation (NSF) that allows researchers to design, execute, and share reproducible scientific workflows. It is an open-source platform that is available free of charge to researchers.

       Kepler is designed to support the creation and execution of complex, data-intensive scientific processes. It allows researchers to design their workflow using a graphical user interface and to specify the dependencies between different tasks in the workflow. Once the workflow is designed, Kepler can automatically execute the tasks in the workflow and manage the transfer of data between them.

       Kepler is widely used in the scientific community and has been applied to a variety of research domains, including genomics, climate modeling, and astrophysics. It is also extensible, allowing researchers to add new functionality to the platform through the use of modules and plugins.

    • Q: Describe the components of the Kepler Scientific Workflow Platform.
    • A: The Kepler Scientific Workflow Platform consists of several components that work together to enable the design and execution of scientific workflows:
      1. Graphical User Interface (GUI): Kepler provides a graphical user interface that allows researchers to design their workflow by dragging and dropping components (called "actors") onto a canvas and specifying the dependencies between them.
      2. Actor library: Kepler includes a library of pre-built actors that represent different tasks that can be included in a workflow. These actors can be used to perform a wide range of tasks, including data import and export, data manipulation, and data analysis.
      3. Execution engine: The execution engine is responsible for executing the workflow once it has been designed. It manages the transfer of data between actors and ensures that each actor is executed in the correct order.
      4. Data management: Kepler provides tools for managing the data that is generated and used by the workflow. This includes tools for storing and accessing data, as well as tools for tracking the provenance of data (i.e., the history of how it was generated and modified).
      5. Community and collaboration: Kepler is designed to support collaboration and sharing within the scientific community. It includes tools for sharing workflows with other researchers and for collaborating on the design and execution of workflows.

2023

  • (Wikipedia, 2023) ⇒ https://en.wikipedia.org/wiki/Kepler_scientific_workflow_system Retrieved:2023-1-7.
    • Kepler is a free software system for designing, executing, reusing, evolving, archiving, and sharing scientific workflows.[1] [2] [3]

      Kepler's facilities provide process and data monitoring, provenance information, and high-speed data movement. Workflows in general, and scientific workflows in particular, are directed graphs where the nodes represent discrete computational components, and the edges represent paths along which data and results can flow between components.[4]

      In Kepler, the nodes are called 'Actors' and the edges are called 'channels'. Kepler includes a graphical user interface for composing workflows in a desktop environment, a runtime engine for executing workflows within the GUI and independently from a command-line, and a distributed computing option that allows workflow tasks to be distributed among compute nodes in a computer cluster or computing grid. The Kepler system principally targets the use of a workflow metaphor for organizing computational tasks that are directed towards particular scientific analysis and modeling goals. Thus, Kepler scientific workflows generally model the flow of data from one step to another in a series of computations that achieve some scientific goal.

  1. Ludäscher B., Altintas I., Berkley C., Higgins D., Jaeger-Frank E., Jones M., Lee E., Tao J., Zhao Y. 2006. Scientific Workflow Management and the Kepler System. Special Issue: Workflow in Grid Systems. Concurrency and Computation: Practice & Experience 18(10): 1039-1065.
  2. Altintas I, Berkley C, Jaeger E, Jones M, Ludäscher B, Mock S. 2004. Kepler: An Extensible System for Design and Execution of Scientific Workflows. Proceedings of the Future of Grid Data Environments, Global Grid Forum 10.
  3. Michener, William K., James H. Beach, Matthew B. Jones, Bertram Ludaescher, Deana D. Pennington, Ricardo S. Pereira, Arcot Rajasekar, and Mark Schildhauer. 2007. “A Knowledge Environment for the Biodiversity and Ecological Sciences", Journal of Intelligent Information Systems, 29(1): 111-126.
  4. Taylor, I.J.; Deelman, E.; Gannon, D.B.; Shields, M. (Eds.), “Workflows for e-Science: Scientific Workflows for Grids”, 530 p., Springer. .