This notebook presents geoextent, a Python library for reliably extracting the geospatial and temporal extents of files, directories, and repository records. The geospatial and temporal metadata of research data could greatly benefit the discovery of relevant and related datasets (Gregory et al., 2018). However, it is underused in scientific data repositories except for specialised repositories. Much more scientific disciplines collect data and publish work that has some temporal or spatial relation. These datasets may not be connected through regular search indices based on keywords or full texts. The library geoextent presented in this notebook helps to understand the potential of extract information from files shared in data repositories and may be used to integrate geospatial and temporal metadata into repository infrastructures.
To run the showcase notebook, install JupyterLab or the classic Jupyter Notebook and then start a local server as shown below. If your IDE has support for the Jupyter format, installing ipykernel might be enough. We recommend running the below commands in a virtual environment as described here. The notebook must be trusted.
cd showcase
pip install -r requirements.txt
pip install -r showcase/requirements.txt
pip install -e .
jupyter trust showcase/SG_01_Exploring_Research_Data_Repositories_with_geoextent.ipynb
jupyter labThen open the local Jupyter Notebook server using the displayed link and open the notebook (*.ipynb files) in the showcase/ directory. Consult the documentation on paired notebooks based on Jupytext before editing selected notebooks.
Garzón, Sebastian and Nüst, Daniel, 2021. Exploring Research Data Repositories with geoextent.
geoextent is licensed under MIT license, see file LICENSE.
This project is developed as part of the DFG-funded research project Opening Reproducible Research (o2r, https://o2r.info).
Copyright (C) 2021 - o2r project.