Reproducible research at the GIScience conference

This repository is the reproducibility package for the article “Reproducible research and GIScience: an evaluation using GIScience conference papers”. This repository is based on a previous analysis of AGILE conference submissions, see https://github.com/nuest/reproducible-research-and-giscience (10.5281/zenodo.1227260). Find the preprint and a deposition of this repository via the badges below.

Reproduce online

Click the “Binder” button below to open an interactive editing environment with all required software installed on MyBinder.org. It uses the current version of the branch master in the repository, but you can also enter the Zenodo DOI (see above) in the MyBinder user interface to open a preserved release version.

You can start RStudio for the text analysis and figures via “New > RStudio” or open the Jupyter Notebook for the bibliographic analysis in the folder author_analysis. You can navigate to the R Markdown notebook files (see list of files below) to inspect and execute the code for the text analysis and reproduce the figures as described in Reproduce locally, except that local installation of required packages is not required.

Use this link to directly open the Jupyter Notebook.

Use this link to directly open RStudio.

Reproduce analyses

Open one of the two R Markdown analysis files (.Rmd) with RStudio. Then select “Knit > Knit to PDF” to render the document. If you have errors rendering the whole PDF, try running each chunk to locate the problem or use “Knit to HTML”. Depending on the R Markdown parameters, the historic tex analysis tries to download proceedings PDFs from a private share and requires a login. This download does not work with knitting the whole document - please execute the chunk data_download_drive manually.

The documents do not include code to install required packages. Run the code in the file install.R to install all dependencies. You can skip the installation of LaTeX (recommended to use tinytex) and installation of LaTeX packages if you knit to HTML or run the chunks directly from RStudio.

Reproduce locally with Docker

Install Docker CE or a compatible tool for building an image based on a Dockerfile and running a container based on the image. The Dockerfile uses the Rocker image rocker/binder:3.6.3, providing R version 3.6.3 with a CRAN mirror timestamp of July 5th 2019.

Download the project files, open a command line in the root directory (where this file is), and run the commands as documented at the end of the Dockerfile.

If you have repo2docker, you can also run repo2docker . and use the --editable option to edit the workflows. The repo2docker option is the only way the original authors worked on the analysis to ensure the computing environment is properly managed. You can most easily achieve it using the included Makefile, just run

make

Files in this repository

• paper/reproducible-research-at-giscience.Rmd: The paper manuscript; it uses the data from the directories results and author_analysis, which is generated by the other Rmd and Jupyter notebooks (see below).
• paper/reproducible-research-at-giscience-appendix.Rmd: Appendix for the manuscript with the assessment results table.
• results/paper_assessment.csv: Results of manual paper evaluation.
• results/text_analysis_{topwordstems,keywordstems}.csv: Results of automated text analysis.
• results/figure_[...].{pdf,png}: Figures and plots from text analysis and paper assessment; the plots are also created as part of the manuscript.
• giscience-reproducibility-assessment.Rmd: R Markdown document with the visualisations about the assessment of paper reproducibility.
• giscience-historic-text-analysis.Rmd: R Markdown document with the text analysis of historic GIScience proceedings.
• Dockerfile: A recipe for the computational environment using Docker.
• install.R: R script file executed during creation of the Docker image to install required dependencies.
• author_analysis/*: Data, code, and results simple comparison of authors’ last names of the compared conferences based on a Jupyter Notebook; the contents of the file author_counts.csv are used in the article manuscript.
• docs/*: Prerendered HTML files of the analysis documents hosted online at https://nuest.github.io/reproducible-research-at-giscience/; files can be rendered with make docs

Deposition on Zenodo

This repository is archived on Zenodo: https://doi.org/10.5281/zenodo.4032875

The deposited archive was created using the GitHub-Zenodo-integration and includes all source files and the appendix as PDF.

You can open the Zenodo deposit directly on Binder:

License

The documents in this repository are licensed under a Creative Commons Attribution 4.0 International License.

All contained code is licensed under the Apache License 2.0.

The data used is licensed under a Open Data Commons Attribution License.