A Beginner's Guide to Kepler Workflow System

Kepler is a software application for analyzing and modeling scientific data. Kepler provides an intuitive and simple graphical user interface and components. Scientists with a little background in computer science can create executable workflows. Kepler also provides components to easily scale-up and execute the workflow over distributed platforms such Cloud, Compute clusters.

  1. Computational Science
  2. Data-Parallel Distributed
  3. Kepler Workflow System
  4. People
  5. Performance
  6. Platforms
  7. Process
  8. Provenance
  9. Publication
  10. Reproducibility
  11. Reusability
  12. Scalability
  13. Scientific Workflows
  14. Tool
  15. Workflows


    The course teaches workflow-based thinking to capture the end-to-end process as reusable blocks of knowledge and integrate the tools and technologies used in big data analysis in an intuitive manner. Our workflow-driven driven approach enables us to teach basic concepts in big data analysis and process management. The learning objectives of our training include:
  • Learn about Scientific workflows with real-world examples
  • Learn about Kepler workflow system
  • Learn about how to get started with Kepler
  • Learn about building loops in Kepler
  • Learn to use Kepler Docker containers
  • Learn about Integrating Kepler workflow with Jupyter notebook

Target Audience

This course is meant for students and professionals who would like to learn more about Kepler.


To cite bioKepler, please use the following reference:

I. Altintas, J. Wang, D. Crawl, W. Li, “Challenges and approaches for distributed workflow-driven analysis of large-scale biological data” , in: Proceedings of the Workshop on Data analytics in the Cloud at EDBT/ICDT 2012 Conference, DanaC2012, 2012, pp 73-78.