Openness and Computational Reproducibility in Plant Pathology: Where we Stand and a Way Forward

DOI: 10.31220/agriRxiv.2021.00082
Statement: This article is a preprint and has not been peer-reviewed. It reports new research that has yet to be evaluated and so should not be used to guide clinical practice.
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    Abstract: Openness and computational reproducibility in plant pathology: where do we stand and a way forward. Abstract Open research practices have been highlighted extensively during the last ten years in many fields of scientific study as essential standards needed to promote transparency and reproducibility of scientific results. Scientific claims can only be evaluated based on how protocols, materials, equipment and methods were described; data were collected and prepared; and analyzes were conducted. Openly sharing protocols, data and computational code is central for current scholarly dissemination and communication, but in many fields, including plant pathology, adoption of these practices has been slow. We randomly selected 450 articles published from 2012 to 2021 across 21 journals representative of the plant pathology discipline and assigned them scores reflecting their openness and computational reproducibility. We found that most of the articles were not following protocols for open science and were failing to share data or code in a reproducible way. We also propose that use of open-source tools facilitates computationally reproducible work and analyzes benefitting not just readers, but the authors as well. Finally, we also provide ideas and tools to promote open, reproducible computational research practices among plant pathologists. Open preprint This article is a preprint and has not been peer reviewed

    Key words: plant pathology; data; protocols; reproducible; computational reproducibility; practice

    Submit time: 1 January 2021

    Copyright: The copyright holder for this preprint is the author/funder, who has granted agriXiv a license to display the preprint in perpetuity.
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    1 2021-01-01

    10.31220/agriRxiv.2021.00082V1

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Adam Sparks, Emerson M. Del Ponte, Kaique S. Alves, Zachary Foster, Niklaus J. Grünwal. Openness and Computational Reproducibility in Plant Pathology: Where we Stand and a Way Forward. 2021. agriXiv.2021.00082

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