This repository contains data for spatial analyses that are part of a research project on spatial/urban design features of railway-related built structures designed by the Swiss architect Max Vogt. The data in this repository is openly available to everyone and is intended to support reproducible research. See the Quarto project website for extensive documentation.
Results of the analyses are accessible in an online collection of Vogt's buildings and presented as a poster at the Spatial Humanities 2024 conference at the University of Bamberg.
The structure of this repository is based on the Open Research Data Template by @maehr, follows the Advanced Structure for Data Analysis of The Turing Way and is organized as follows:
analysis/: notebooks used to retrieve and analyze the dataassets/: images, logos, etc. used in the README and other documentationdata/: data filesdocs/: documentation for the data and the repositoryresults/: geodata output of the analysis notebooks
Additionally, there is a Zotero group library with a collection of scientific articles and news reports that are of relevance for this project.
See Workflow for a description of the project workflow and the data obtained for this project.
To run the analysis locally, create a new conda environment based on the environment.yml file.
conda env create -f environment.ymlActivate the environment.
conda activate maxvogtOpen the Jupyter Notebook platform.
jupyter notebookPick a notebook from analysis/ to start the spatial analysis for one of Max Vogt's buildings.
These data are openly available to everyone and can be used for any research or educational purpose. If you use this data in your research, please cite as specified in CITATION.cff. The following citation formats are also available through Zenodo:
Zenodo provides an API (REST & OAI-PMH) to access the data. For example, the following command will return the metadata for the most recent version of the data
curl -i https://zenodo.org/api/records/ZENODO_RECORDThis project is maintained by @mtwente. Please understand that we can't provide individual support via email. We also believe that help is much more valuable when it's shared publicly, so more people can benefit from it.
| Type | Platforms |
|---|---|
| 🚨 Bug Reports | GitHub Issue Tracker |
| 📊 Report bad data | GitHub Issue Tracker |
| 📚 Docs Issue | GitHub Issue Tracker |
| 🎁 Feature Requests | GitHub Issue Tracker |
| 🛡 Report a security vulnerability | See SECURITY.md |
| 💬 General Questions | GitHub Discussions |
- tidy up jupyter notebooks
- add page with info on data model for OSM, Wikidata, Wikimedia Commons, CollectionBuilder
- publish via Zenodo
All contributions to this repository are welcome! If you find errors or problems with the data, or if you want to add new data or features, please open an issue or pull request. Please read CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.
We use SemVer for versioning. The available versions are listed in the tags on this repository.
The Jupyter Notebooks used for data retrieval and analysis are based on the 2021 workshop Capturing the Structure of Cities with Data Science workshop by Martin Fleischmann.
Geodata used in this analysis is retrieved from OpenStreetMap, © OpenStreetMap contributors.
See also the list of contributors who contributed to this project.
The data in this repository, excluding OpenStreetMap geodata, is released under the Creative Commons Attribution 4.0 International (CC BY 4.0) License – see the LICENSE-CCBY file for details. By using this data, you agree to give appropriate credit to the original author(s) and to indicate if any modifications have been made.
Geodata in this repository, retrieved from OpenStreetMap, is released under the Open Database License – see the LICENSE-ODbL file for details. By using this data, you agree to adhere to the attribution standards set out in the license and specified by the OpenStreetMap Foundation.
The code in this repository, excluding the Jupyter notebooks in /analysis/, is released under the GNU Affero General Public License v3.0 – see the LICENSE-AGPL file for details. By using this code, you agree to make any modifications available under the same license.
The Jupyter notebooks in /analysis/ are released under the Creative Commons Attribution 4.0 International (CC BY 4.0) License – see the LICENSE-CCBY file for details. By using this data, you agree to give appropriate credit to the original author(s) and to indicate if any modifications have been made.