Review of
"Unveiling the diversity of spatial data infrastructures in Latin America: evidence from an exploratory inquiry"

Review of "Unveiling the diversity of spatial data infrastructures in Latin America: evidence from an exploratory inquiry"

Submitted by vronsee  

Aug. 31, 2022, 8:55 a.m.

Lead reviewer


Review Body


Did you manage to reproduce it?
Fully Reproducible
Reproducibility rating
How much of the paper did you manage to reproduce?
10 / 10
Briefly describe the procedure followed/tools used to reproduce it

I downloaded the provided code and data. I opened the Rmd file in RStudio. RStudio proposed to install the missing packages needed for the analysis. I installed them and then knit the file successfully.

Briefly describe your familiarity with the procedure/tools used by the paper.

I am very familiar with R and also RMarkdown documents.

Which type of operating system were you working in?
Apple Operating System (macOSX)
What additional software did you need to install?

R-Packages that were used in the analysis.

What software did you use

R version 4.1.3 in RStudio 2022.07.1 "Spotted Wakerobin" Release

What were the main challenges you ran into (if any)?

It was not a real challenge because RStudio immediatly suggested the download of missing packages, but I would say the main and only part was that packages weren't downloaded automatically by the script.

What were the positive features of this approach?

RMarkdown is nice for the combination of code and text and makes it easy for others to understand the background of the analysis. It's great that data and code is provided in a zip file and everything is directly at hand for reproduction.

Any other comments/suggestions on the reproducibility approach?

Only a minor remark to avoid possible problems that could eventually come up with different versions of R and R packages. I didn't run into those problems, but maybe at some point others might.

I would recommend to include information on the R Version and R packages and their versions the code is dependent on. This could be either in the script itself to include a check and automatic download of the necessary packages. Or a remark in the readme file that lists the dependencies. Or as a sessionInfo that shows the used R Version and the R packages and respective versions used in the analysis. A docker container would be most elegant solution I suppose. However analysis does not use very complicated functions, so it might be rather stable across versions.


Documentation rating
How well was the material documented?
9 / 10
How could the documentation be improved?

It would have been nice to include R Package dependencies and R version used, see above. Also for others not so familiar with RMarkdown it might be nice to provide a few lines to explain what it is and how to produce the html file. (e.g. Rstudio and the knit button)

What do you like about the documentation?

RMarkdown is a documentation itself - great! The Readme file included most important metadata.

After attempting to reproduce, how familiar do you feel with the code and methods used in the paper?
9 / 10
Any suggestions on how the analysis could be made more transparent?

The code chunks in the RMarkdown could be commented more for others to see which exact analysis is done in the respective part.


Reusability rating
Rate the project on reusability of the material
9 / 10
Permissive Data license included:  
Permissive Code license included:  

Any suggestions on how the project could be more reusable?

The license for the reuse of data or code is stated on figshare. It might be nice to put it in the readme file as well to make it even more clear also after the download. Also it would be nice to mention how to cite the paper in the readme file. It is mentioned in the Rmd file, but a bit hidden within the code.

Any final comments