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Ten quick tips for building FAIR workflows

PLoS Computational Biology, vol. 19, pp. e1011369

Abstract

Research data is accumulating rapidly and with it the challenge of fully reproducible science. As a consequence, implementation of high-quality management of scientific data has become a global priority. The FAIR (Findable, Accesible, Interoperable and Reusable) principles provide practical guidelines for maximizing the value of research data; however, processing data using workflows-systematic executions of a series of computational tools-is equally important for good data management. The FAIR principles have recently been adapted to Research Software (FAIR4RS Principles) to promote the reproducibility and reusability of any type of research software. Here, we propose a set of 10 quick tips, drafted by experienced workflow developers that will help researchers to apply FAIR4RS principles to workflows. The tips have been arranged according to the FAIR acronym, clarifying the purpose of each tip with respect to the FAIR4RS principles. Altogether, these tips can be seen as practical guidelines for workflow developers who aim to contribute to more reproducible and sustainable computational science, aiming to positively impact the open science and FAIR community.

Authors 10

  1. Radboud University Nijmegen · Radboud University Medical Center

    Affiliation as printed

    Medical BioSciences Department, Radboud University Medical Center, Nijmegen, the Netherlands

  2. Radboud University Nijmegen · Radboud University Medical Center

    Affiliation as printed

    Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands

    Medical BioSciences Department, Radboud University Medical Center, Nijmegen, the Netherlands

    Translational Metabolic Laboratory, Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, the Netherlands

  3. Leiden University Medical Center

    Affiliation as printed

    Sequencing Analysis Support Core, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands

  4. University Medical Center Groningen · University of Groningen

    Affiliation as printed

    Genomics Coordination Center and Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands

  5. University Medical Center Groningen · University of Groningen

    Affiliation as printed

    Genomics Coordination Center and Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands

  6. University of Groningen

    Affiliation as printed

    Department of Analytical Biochemistry, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, the Netherlands

  7. Radboud University Nijmegen · Radboud University Medical Center

    Affiliation as printed

    Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands

    Translational Metabolic Laboratory, Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, the Netherlands

  8. University Medical Center Groningen · University of Groningen

    Affiliation as printed

    Genomics Coordination Center and Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands

  9. Peter A.C. ’t Hoen corresponding

    Radboud University Nijmegen · Radboud University Medical Center

    Affiliation as printed

    Medical BioSciences Department, Radboud University Medical Center, Nijmegen, the Netherlands

  10. Radboud University Nijmegen · Radboud University Medical Center

    Affiliation as printed

    Medical BioSciences Department, Radboud University Medical Center, Nijmegen, the Netherlands

    Translational Metabolic Laboratory, Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, the Netherlands

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References 49