Template for setting up reproducible projects

This is a template for setting-up a research or data science project online, such as on GitHub.

About this Repository

This repository operationalises The Turing Way recommendations for structring project repository to support reproducibility in data science projects. This repository includes files and directories recommended for enabling reproducibility and collaboration in a project, as well as sharing of research objects.

This repository follows the recommendations and guidance provided in The Turing Way handbook to data science.

The repository has been further developed to add Read the Docs documentation.

Repo Structure

Inspired by Cookie Cutter Data Science.

├── LICENSE
├── README.md          <- The top-level README for users of this project.
├── CODE_OF_CONDUCT.md <- Guidelines for users and contributors of the project.
├── CONTRIBUTING.md    <- Information on how to contribute to the project.
├── data
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── project_management <- Meeting notes and other project planning resources
│
├── src                <- Source code for use in this project.
│   │
│   ├── data           <- Scripts to download or generate data
│   │   └── make_dataset.py
│   │
│   ├── models         <- Scripts to train models and then use trained models to make
│   │   │                 predictions
│   │   ├── predict_model.py
│   │   └── train_model.py
│   │
│   └── visualisation  <- Scripts to create exploratory and results oriented visualisations
│       └── visualise.py
└──

Maintainers

This repository has been set-up and maintained by Malvika Sharan to support the work of Open Research Community Management and Research Application Management teams under the Tools, Practices and Systems Research Programme at The Alan Turing Institute.

As an open source repository, anyone beyond these teams are very welcome to reuse this template for setting up their projects.

Please create an issue to share references or ideas related to the development of this project.

🎯 Roadmap

Checklist for setting an online repository

• Add a README file
• Add a CONTRIBUTING file
• Add a LICENSE
• Add a Code of Conduct
• Install all-contributors bot
• .gitignore file (choose from a template)
• Issue templates
  • Optionally Install Welcome/behavior bot (see The Turing Way config)
• Create a directory with files for project management (meetings, report, proposals)
• Create a directory with files for communications
• Create a directory for research analysis
• Create a directory for research results/outcome to share (?)
• Create a directory for ethics approval and project policies
• Create a directory with files for stakeholders info and nature of engagement
• Connect repo with Zenodo
• Add cff file for citation
• Add badges

📫 Contact

For any organisation related queries or concerns, you can directly reach out to Malvika Sharan by emailing [email protected].

♻️ License

This work is licensed under the MIT license (code) and Creative Commons Attribution 4.0 International license (for documentation). You are free to share and adapt the material for any purpose, even commercially, as long as you provide attribution (give appropriate credit, provide a link to the license, and indicate if changes were made) in any reasonable manner, but not in any way that suggests the licensor endorses you or your use, and with no additional restrictions.

🤝 Acknowledgement

This repository has been created for anyone to reuse -- please attribute us as:

This repository uses the tamplate created and maintained by The Turing Way team members and shared under CC-BY 4.0 for reuse: https://github.com/alan-turing-institute/reproducible-project-template.

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Malvika Sharan 🤔 🖋

Emma Karoune 🤔 📖

Anne Lee Steele 🤔 📖

Vicky Hellon 🤔 📖

Jennifer Ding 🖋 📖 🤔

Hilmar Lapp 🐛

This project follows the all-contributors specification. Contributions of any kind welcome!