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https://github.com/nceas/fairdataone

DataONE FAIR manuscript
https://github.com/nceas/fairdataone

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DataONE FAIR manuscript

Awesome Lists containing this project

README

          

---
output: github_document
article_title: "A quantitiative assessment of metadata practices in the global DataONE repository network"
authors: ["S. Jeanette Clark", "Chris Beltz", "Peter Slaughter", "Ted Habermmann", "Matthew B. Jones"]
pub_date: 2021
---

```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
# Please put your title here to include it in the file below.
title <- rmarkdown::metadata$article_title
authors <- rmarkdown::metadata$authors
pub_date <- rmarkdown::metadata$pub_date
```

# fairdataone

*Status*: Incomplete Work in Progress (WIP)

This repository contains the data and code for our paper:

> `r authors`, (`r pub_date`). _`r title`_. Name of journal/book

Our pre-print is online here:

> `r authors`, (`r pub_date`). _`r title`_. Name of journal/book, Accessed `r format(Sys.Date(), "%d %b %Y")`. Online at

### How to cite

Please cite this compendium as:

> `r authors`, (`r format(Sys.Date(), "%Y")`). _Compendium of R code and data for `r title`_. Accessed `r format(Sys.Date(), "%d %b %Y")`. Online at

## Contents

- [:file\_folder: manuscript](/manuscript): R Markdown source document
for manuscript. Includes code to reproduce the figures and tables
generated by the analysis. It also has a rendered version,
`manuscript.pdf`, suitable for reading (the code is replaced by figures
and tables in this file)
- [:file\_folder: data](/manuscript/data): Data used in the analysis. Most
data are retrieved from a data archive, but small static data files may also
be retrieved from this directory.
- [:file\_folder: figures](/manuscript/figures): Plots and other illustrations.

## How to run run locally

This research compendium has been developed using the statistical programming
language R. To work with the compendium, you will need
installed on your computer the [R software](https://cloud.r-project.org/)
itself and optionally [RStudio Desktop](https://rstudio.com/products/rstudio/download/).

After downloading the compendium from GitHub:

- open the `.Rproj` file in RStudio
- run `devtools::install()` to ensure you have the packages this analysis
depends on (also listed in the [DESCRIPTION](/DESCRIPTION) file). This also
installs the `fairdataone` package, which is necessary to Knit the manuscript.
- finally, open `manuscript/manuscript.Rmd` and knit to produce the `manuscript.pdf`,
or run `rmarkdown::render("manuscript/manuscript.Rmd")` in the R console.

### Licenses

**Text and figures :** [CC-BY-4.0](http://creativecommons.org/licenses/by/4.0/)

**Code :** See the [DESCRIPTION](DESCRIPTION) file

**Data :** [CC-0](http://creativecommons.org/publicdomain/zero/1.0/) attribution requested in reuse