Abstract

Research data is accumulating at an unprecedented rate, presenting significant challenges for achieving fully reproducible science. As a result, implementing high-quality management of scientific data has become a global priority. One key aspect of this effort is the use of computational workflows, which describe the complex, multi-step methods used for data analysis. In Galaxy, workflows are a powerful feature that allows researchers to link multiple steps of complex analyses seamlessly. To maximize their impact, these workflows should adhere to best practices that make them FAIR: Findable, Accessible, Interoperable, and Reusable.

About This Material

This is a Hands-on Tutorial from the GTN which is usable either for individual self-study, or as a teaching material in a classroom.

Questions this will address

• How can a Galaxy workflow be annotated to improve reusability?
• What are the best practices for testing a Galaxy workflow?
• How can a Galaxy workflow be submitted to the Intergalactic Workflow Commission (IWC)?

Learning Objectives

• Annotate a Galaxy workflows with essential metadata
• Annotate and apply best practices to data analysis Galaxy workflows for consistency and reusability
• Implement robust tests to ensure workflow reliability and accuracy
• Successfully integrate key data analysis Galaxy workflows into IWC, improving accessibility and usability