SciWIn-Client and SciWIn-Studio: Simplifying FAIR Computational Workflows

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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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-17
DOI
https://doi.org/10.5281/zenodo.19060805
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
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article

SciWIn-Client and SciWIn-Studio: Simplifying FAIR Computational Workflows

Jens Krumsieck, Harald Bernd Kurt Von Waldow, Antonia Leidel, Xaver Stiensmeier
Zenodo (CERN European Organization for Nuclear Research)
Scientific Computing and Data Management
article

SciWIn-Client and SciWIn-Studio: Simplifying FAIR Computational Workflows

Jens Krumsieck, Harald Bernd Kurt Von Waldow, Antonia Leidel, Xaver Stiensmeier
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Bielefeld University (DE), Johann Heinrich von Thünen-Institut (DE), Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 17%
Scientific Computing and Data Management
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SciWIn-Client and SciWIn-Studio: Simplifying FAIR Computational Workflows — Jens Krumsieck, Harald Bernd Kurt Von Waldow, et al. · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS