Reusability Challenges of Scientific Workflows: A Case Study for Galaxy

TL;DR

This paper investigates the challenges faced in reusing scientific workflows, identifies key issues hindering reusability, and provides guidelines to improve workflow design for better reuse in scientific research.

Contribution

It offers an in-depth analysis of reusability challenges in scientific workflows and proposes actionable guidelines to enhance workflow reusability and support future tool development.

Findings

Identified key reusability challenges such as tool upgrading and incomplete workflows.

Provided an action list and guidelines for better workflow design.

Exposed specific issues hindering workflow reuse in scientific research.

Abstract

Scientific workflow has become essential in software engineering because it provides a structured approach to designing, executing, and analyzing scientific experiments. Software developers and researchers have developed hundreds of scientific workflow management systems so scientists in various domains can benefit from them by automating repetitive tasks, enhancing collaboration, and ensuring the reproducibility of their results. However, even for expert users, workflow creation is a complex task due to the dramatic growth of tools and data heterogeneity. Thus, scientists attempt to reuse existing workflows shared in workflow repositories. Unfortunately, several challenges prevent scientists from reusing those workflows. In this study, we thus first attempted to identify those reusability challenges. We also offered an action list and evidence-based guidelines to promote the reusability of scientific workflows. Our intensive manual investigation examined the reusability of existing workflows and exposed several challenges. The challenges preventing reusability include tool upgrading, tool support unavailability, design flaws, incomplete workflows, failure to load a workflow, etc. Such challenges and our action list offered guidelines to future workflow composers to create better workflows with enhanced reusability. In the future, we plan to develop a recommender system using reusable workflows that can assist scientists in creating effective and error-free workflows.