User-friendly Composition of FAIR Workflows in a Notebook Environment

TL;DR

This paper introduces a user-friendly toolset that enhances the FAIRness of scientific workflows in Jupyter notebooks by integrating semantic technologies, enabling easier reuse and searchability of workflow components.

Contribution

It presents a novel, minimally intrusive approach and toolset for adding semantic descriptions to Python workflows in notebooks, improving FAIR compliance and usability.

Findings

System usability score of 78.75, above average

Participants found the system user-friendly

Semantic descriptions enable better search and reuse

Abstract

There has been a large focus in recent years on making assets in scientific research findable, accessible, interoperable and reusable, collectively known as the FAIR principles. A particular area of focus lies in applying these principles to scientific computational workflows. Jupyter notebooks are a very popular medium by which to program and communicate computational scientific analyses. However, they present unique challenges when it comes to reuse of only particular steps of an analysis without disrupting the usual flow and benefits of the notebook approach, making it difficult to fully comply with the FAIR principles. Here we present an approach and toolset for adding the power of semantic technologies to Python-encoded scientific workflows in a simple, automated and minimally intrusive manner. The semantic descriptions are published as a series of nanopublications that can be searched and used in other notebooks by means of a Jupyter Lab plugin. We describe the implementation of the proposed approach and toolset, and provide the results of a user study with 15 participants, designed around image processing workflows, to evaluate the usability of the system and its perceived effect on FAIRness. Our results show that our approach is feasible and perceived as user-friendly. Our system received an overall score of 78.75 on the System Usability Scale, which is above the average score reported in the literature.