sketchy

create and manage research compendiums for data analysis

https://github.com/marce10/sketchy

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create and manage research compendiums for data analysis

README.Rmd

---
title: "sketchy: create custom research compendiums"
output: github_document
editor_options: 
  chunk_output_type: console
---




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```{r setup, include = FALSE}

# knitr global options
knitr::opts_chunk$set(
  collapse = TRUE,
  out.width = "100%",
  tidy = TRUE
)
library(sketchy)

```



The package is intended to facilitate the use of research compendiums for data analysis in the R environment. Standard research compendiums provide a easily recognizable means for organizing digital materials, allowing  other researchers to inspect, reproduce, and build upon that research. 

Unlike other R packages for creating research compendiums (e.g. [vertical](https://github.com/CrumpLab/vertical), [rrtools](https://github.com/benmarwick/rrtools)), `sketchy` isn't  wedded to a particular folder structure. Currently the package provides `r length(compendiums)` alternative structures (see object `compendiums`) and allows users to modify or input their own structures.   

To install the latest developmental version from [github](https://github.com/) you will need the R package [remotes](https://cran.r-project.org/package=remotes):

```{r 1, eval = FALSE}

# From github
remotes::install_github("maRce10/sketchy")

#load package
library(sketchy)

```

## Default compendium skeletons

Compendiums can be set up with the function `make_compendium()`. The function creates the folder/subfolder structure and prints a diagram of the skeleton in the console:

### Basic compendium

```{r 3, eval = TRUE}

path = tempdir()

# load data
data(compendiums)

make_compendium(name = "proyect_x", path = path, format = "basic")

```


  

(*in these examples the compendiums are created in a temporary directory, change 'path' to create it in a different directory*)


### Alternative structures

We can use folder structures from other sources. For instance, in this example we use the structured suggested by Wilson *et al.* (2017):

```{r 4, eval = TRUE}

make_compendium(name = "proyect_z", path = path, format = "large_compendium")

```

  

When creating a compendium that includes a "manuscript" folder the package adds a "manuscript_template.Rmd" file for facilitating paper writing within the compendium itself.


We can check all compendium structure available as follows:

```{r 5, eval = TRUE}

for(i in 1:length(compendiums)){
  print("---------------", quote = FALSE)
  print(names(compendiums)[i], quote = FALSE)
  print_skeleton(folders = compendiums[[i]]$skeleton)
}
  
```
---

Please cite [sketchy](https://marce10.github.io/sketchy/) as follows:

Araya-Salas, M., Willink, B., Arriaga, A. (2020), *sketchy: research compendiums for data analysis in R*. R package version 1.0.0. 


# References

1. Alston, J., & Rick, J. (2020). *A Beginner’s Guide to Conducting Reproducible Research*. 

1. Marwick, B., Boettiger, C., & Mullen, L. (2018). *Packaging Data Analytical Work Reproducibly Using R (and Friends)*. American Statistician, 72(1), 80–88.

1. Wilson G, Bryan J, Cranston K, Kitzes J, Nederbragt L. & Teal, T. K.. 2017. *Good enough practices in scientific computing*. PLOS Computational Biology 13(6): e1005510.

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