Technology supports the creation of FAIR computational workflows in diverse user environments, indicating better research practices.
The ability to create FAIR computational workflows is increasingly critical for ensuring transparency, reproducibility, and reusability in data-driven research. By using computational workflows, researchers can automate long sequences of scripts and combine tools from different programming languages into fully managed, reproducible pipelines, making FAIR practices easier to implement without sacrificing flexibility. To support this, the Scientific Workflow Infrastructure (SciWIn) provides complementary clients: SciWIn-Client and SciWIn-Studio. Those applications are designed to support efficient interaction with computational workflows based on the Common Workflow Language (CWL). Both applications address the same core requirement: the easy, fast, and frictionless creation of FAIR computational workflows, while targeting different user groups. The command-line application SciWIn-Client (s4n) is aimed at users who are comfortable working at the command line and seek automation and scripting capabilities. In contrast, the upcoming SciWIn-Studio provides a graphical user interface for users who prefer visual interaction and guided workflow construction.
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Krumsieck et al. (2026) studied this question.
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