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https://github.com/openplantpathology/Reproducibility_in_Plant_Pathology

A systematic/quantitative review of articles, which provides a basis for identifying what has been done so far in the field of plant pathology research reproducibility and suggestions for ways to improving it.
https://github.com/openplantpathology/Reproducibility_in_Plant_Pathology

open-science plant-pathology r reproducible-research reproducible-science research-compendium rstats

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A systematic/quantitative review of articles, which provides a basis for identifying what has been done so far in the field of plant pathology research reproducibility and suggestions for ways to improving it.

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README 

        



# Reproducibility in Plant Pathology



![Publish

Docker](https://github.com/openplantpathology/Reproducibility_in_Plant_Pathology/workflows/Publish%20Docker/badge.svg)

[![DOI](https://zenodo.org/badge/62676177.svg)](https://zenodo.org/badge/latestdoi/62676177)

[![Project Status: Active – The project has reached a stable, usable

state and is being actively

developed.](http://www.repostatus.org/badges/latest/active.svg)](http://www.repostatus.org/#active)



This repository contains the data and code for our article:



> Sparks, A.H., Del Ponte, E.M., Alves, K. S., Foster, Z., Grünwald, N.

> J. (2023). *Openness and computational reproducibility in plant

> pathology: where do we stand and a way forward*, *Phytopathology*

> .



Our pre-print is online on the agriRxiv preprint server:



> Sparks, A.H., Del Ponte, E.M., Alves, K. S., Foster, Z., Grünwald, N.

> J. (2023). *Openness and computational reproducibility in plant

> pathology: where do we stand and a way forward*. agriRxiv, Accessed 04

> Mar 2023. Online at 



The paper is a systematic and quantitative review of articles published

in 21 plant pathology journals that spans five years of publications. It

provides a basis for identifying what has been done so far in the

discipline of plant pathology’s published research to ensure

computational reproducibility. The results show that as a discipline,

plant pathologists are not widely sharing data or code openly, making

the works largely unreproducible. Based on these results and our own

experiences, we offer suggestions as to how we can further improve

reproducibility in the discipline of plant pathology, but which are not

unique to the discipline, that would allow reviewers to make better

suggestions, readers to learn more from the work and earns author more

citations for their work.



### How to cite



Please cite this compendium as:



> Sparks, A.H., Del Ponte, E.M., Alves, K. S., Foster, Z., Grünwald, N.

> J. (2023). *Compendium of R code and data for ‘Status and Best

> Practices for Reproducible Research In Plant Pathology’*. Accessed 04

> Mar 2023. Online at 



### How to download or install



#### The R package



This repository is organized as an R package. There is one R function,

`import_notes()` that is used in the paper’s figure and table making

when the file, `analysis/paper/paper.Rmd` is knit. Additionally, a

bibliography file, “references.bib”, of the articles that were examined

and the notes from the evaluation,

“Reproducibility_in_plant_pathology_notes.ods” of the articles are both

located in `inst/extdata` directory. We have used the R package

structure to help manage dependencies, to take advantage of continuous

integration for automated code testing and for file organisation.



You can download the compendium as a zip from from this URL:



Or you can install this compendium as an R package,

Reproducibility.in.Plant.Pathology, from GitHub with:



``` r

if (!require("remotes"))

  install.packages("remotes")

remotes::install_github("openplantpathology/Reproducibility_in_Plant_Pathology"

)

```



Once the download is complete, open the

`Reproducibility_in_Plant_Pathology.Rproj` in RStudio to begin working

with the package and compendium files.



#### The Docker Instance



Get the latest instance from Dockerhub, launch it and go to

`localhost:8787` in your browser. Login with `rstudio`, password is

`rstudio`.



``` bash

docker pull adamhsparks/reproducibility_in_plant_pathology

docker run -d -p 8787:8787 adamhsparks/reproducibility_in_plant_pathology

```



#### The Paper



The file structure follows a normal R package with one exception. The

top-level “/analysis” directory contains the directories and files

necessary to re-knit the MS Word document of the paper from an Rmd file,

“/analysis/paper/paper.Rmd”.



A script, `knit_paper.R`, is located in `analysis/paper/knit_paper.R`

that will knit the [manuscript](analysis/paper/paper.docx) and the

[supplementary materials](analysis/supplementary-materials.docx) in a

Docker session.



## Meta



### Licensing



Code: [MIT](http://opensource.org/licenses/MIT) year: 2023, copyright

holder: Adam H. Sparks



Data: [CC-0](http://creativecommons.org/publicdomain/zero/1.0/)

attribution requested in reuse



Adam H. Sparks Senior Research Scientist Farming Systems Innovation

Primary Industries Development Department of Primary Industries and

Regional Development Level 6.34, 1 Nash St., Perth WA 6000



### Code of Conduct



Please note that the Reproducibility.in.Plant.Pathology project is

released with a [Contributor Code of

Conduct](https://openplantpathology.github.io/Reproducible.Plant.Pathology/CODE_OF_CONDUCT.html).

By contributing to this project, you agree to abide by its terms.