https://github.com/nuest/reproducible-research-giscience-longitudinal-study
https://github.com/nuest/reproducible-research-giscience-longitudinal-study
Last synced: 22 days ago
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- Host: GitHub
- URL: https://github.com/nuest/reproducible-research-giscience-longitudinal-study
- Owner: nuest
- License: apache-2.0
- Created: 2023-05-10T07:21:42.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2025-09-30T07:43:20.000Z (7 months ago)
- Last Synced: 2025-09-30T09:26:13.866Z (7 months ago)
- Language: HTML
- Size: 8.15 MB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# reproducible-research-giscience-longitudinal-study
[](https://doi.org/10.5281/zenodo.17733628)
This is the data and software repo to support the computational analysis related to the paper *Longitudinal assessment of research in GIScience domain shows a positive impact of reproducible research practices*.
This study was coordinated by Frank Ostermann 
,
Daniel Nüst , and
Carlos Granell .
Acknowledgement: [AGILE](https://agile-gi.eu/)...
## Study goals and overall methodology
TODO:
Data...
- AGILE "averages" dataset as csv from previous paper
- AGILE dataset, full papers for years ... - ...
- GIScience dataset, full papers for years xxxx, yyyy, ...
- citation data?
Methods...
- alluvial plot for both pre and post intervention AGILE
- alluvial plot for GIScience matching pre/post years
- timeline plot of actual data points and averages, wich old AGILE dataset in light colour for loose reference
## Contents
- `data`: contains several CSV files that contained assessment data of the eligible conference papers.
- `data-clean`: contains a processed CSV file ready for analysis and a `README` file (data sheet) to describe each column.
- `figs`: contains generated figures from notebooks.
- `*.qmd` files: [Quarto](https://quarto.org/) documents for data preparation and analysis.
- `*.ipynb` files: [Jupyter notebooks](https://jupyter.org/) for data analysis.
- `install.R`: R libraries used by Quarto documents.
- `06_environemnt.yml`: Python libraries used by Jupyter notebooks.
- `Dockerfile` & `compose.yml`: contains a Dockerfile to build a Docker image using [Docker Compose](https://docs.docker.com/compose/).
- `manuscript`: contains the manuscript LaTeX source files.
## Reproducibility
### Reproducibility setup
- TODO: create one common configuration for R/Python. Now, R notebooks are based on `rocker/rstudio:4.4`, and python notebooks on conda.
#### Reproduce online with Binder
[](https://mybinder.org/)
> [!NOTE]
> Building the computing enviroment in Binder can be slow.
#### Reproduce locally with Docker
TODO
### Mapping of code to figures and tables in the paper
The following scripts and notebooks each generate figures or tables in the published paper:
- `02_methods.qmd` generates **Table 1** and **Table 2**.
- `03_results_reprolevels.qmd` generates **Figure 2**, **Figure 3**, and **Table 3**.
- `04_results_hypotheses.ipynb`generates **Table 4**, **Table 5**, **Table 6**, and **Table 7**.
- `05_results_assessprocess.qmd` generates **Table 8**, **Figure 4**, **Table 9**, and **Table 10**.
- `06_discussion.qmd` generates **Figure 5**.
## License
The **code** in this repository (notebooks, scripts) is licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). See the [LICENSE](LICENSE) file for details.
The **data** in this repository (/data, /data-clean) is licensed under [Create Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/) (CC BY 4.0). See the [LICENSE-DATA](LICENSE-DATA) file for details.
The **text** and **figures** in this repository (/manuscript, /figs) are licensed under [Create Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/) (CC BY 4.0). See the [LICENSE-MANUSCRIPT](LICENSE-DATA) file for details.