Implementation of FAIR Practices in Computational Metabolomics Workflows - A Case Study

Scientific workflows facilitate the automation of data analysis tasks by integrating various software and tools executed in a particular order. To enable transparency and reusability in workflows, it is essential to implement the FAIR principles. Here, we describe our experiences implementing the FAIR principles for metabolomics workflows using Metabolome Annotation Workflow (MAW) as a case study. MAW is specified using the Common Workflow Language (CWL), allowing for the subsequent execution of the workflow on different workflow engines. MAW is registered using CWL description on WorkflowHub with the DOI https://doi.org/10.48546/WORKFLOWHUB.WORKFLOW.510.2. During the submission process on WorkflowHub, a CWL description is used for packaging MAW using the Workflow RO-Crate profile, which includes metadata in Bioschemas. Researchers can use the instructions presented in this snapshot as a base template to adopt FAIR practices for their bioinformatics or cheminformatics workflows while incorporating necessary amendments specific to their research area.