Kauê de Sousa, Marie-Angélique Laporte
Here we introduce a reusable, project-oriented data analysis template designed to align with the FAIR principles (Findable, Accessible, Interoperable, and Reusable). The template offers a structured and scalable approach for managing scientific data and code, particularly suited for collaborative and open science environments. It integrates good practices from R-based workflows, GitHub–Zenodo integration, and metadata standards including DataCite and CFF.
The template aims to:
- Improve consistency and reproducibility across research projects.
- Ensure research outputs are FAIR and ready for long-term archiving.
- Provide a ready-to-use metadata structure for data and code publication.
- Support automated workflows and interoperability with platforms like Zenodo, GitHub, and institutional repositories.
The project follows a project-oriented layout inspired by best practices in the R community.
template-repo-data-analysis/
├── data/ # Anonimized raw and cleaned datasets
├── docs/ # Reports or additional documentation
├── metadata/ # Metadata files and templates
│ ├── project-metadata.xlsx # Excel file with project metadata
│ ├── project-metadata.json # JSON file with project metadata for DataCite
│ ├── example-metadata-data-mip-uganda.csv # Description of the dataset used as example
│ └── README.md
├── output/ # Model results, figures, tables
├── script/ # Scripts for validation, metadata generation, etc.
├── .gitignore # Indicates which files or folders to exclude from version control
├── LICENSE # A valid license file stablishing the rights to use the data
├── CITATION.cff # Used by GitHub and Zenodo to generate citation metadata
├── template-repo-data-analysis.Rproj # RStudio file to set up the environment (must be renamed)
└── README.md # Project overview
- Project-oriented structure.
- FAIR-compliant metadata with Zenodo and DataCite standards.
- Automation via R scripts for JSON conversion and validation.
- Citation support with
CITATION.cfffile. - Clear separation of raw data, outputs, scripts, and documentation.
- GitHub–Zenodo integration for DOI minting.
The metadata/ folder contains:
metadata.xlsx: Main spreadsheet with sheets for general metadata, authors, funders, dates, and communities.metadata.json: DataCite-compliant metadata for institutional or repository submission.CITATION.cff: Used by GitHub and Zenodo to generate citation metadata (it must be placed on the main root).README.md: Guide to using the metadata tools.
- Clone or fork the repository and open it in RStudio.
- Complete
metadata.xlsxusing the provided structure. - Add your data
- Run your analysis
- Run the R scripts from the
script/folder to:- Validate metadata
- Convert to JSON
- Publish to Zenodo:
- Enable the GitHub repo in your Zenodo GitHub settings.
- Create a GitHub release. Zenodo will use the
CITATION.cffto generate the DOI metadata.
This template is suitable for:
- Research projects requiring data publication.
- Collaborative projects across CGIAR and university partners.
- Students and researchers new to reproducible data workflows.
The structure is extensible and can support:
- Additional metadata schemas and controled vocabularies (e.g., Dublin Core, DCAT)
- Workflow automation using GitHub Actions or R scripts
- Integration with institutional data catalogs
This template is open for improvement! You can:
- Suggest edits via GitHub Issues
- Fork the repository for your own project
- Contribute back improvements via pull request