Data Organization & File Naming

Well-organised research data are easier to understand, analyse, share, preserve, and reuse. A clear file and folder structure, consistent naming conventions, appropriate file formats, and effective version control help maintain the integrity and usability of research data throughout the research lifecycle.

File and Folder Structure

Use a logical and consistent folder structure that reflects the research project and makes files easy to locate.

Example:

Project_Name/
├── 01_Admin/
├── 02_Data/
│   ├── Raw/
│   ├── Processed/
│   └── Final/
├── 03_Analysis/
├── 04_Code/
├── 05_Documentation/
└── 06_Outputs/

File Naming Conventions

Use file names that are clear, consistent, descriptive, and predictable.

A useful file name may include:

project / content / date / version

Avoid spaces, special characters, and overly long file names. Use a consistent date format such as YYYY-MM-DD.

Avoid: Final data NEW!!!.xlsx
Prefer: survey_results_2026-03-15_v01.xlsx

File Formats

Where possible, use open, standardized, and widely supported file formats to facilitate access and long-term preservation.

View DANS guidance on preferred and acceptable file formats for research data.

Versioning

Versioning helps track changes to files and prevents confusion about which version is current.

Example:

experiment_results_v01.csv
experiment_results_v02.csv
experiment_results_v03.csv

For more formal versioning, dates can also be included:

experiment_results_2026-04-10_v02.csv

For code and other collaborative research materials, consider using a version control system such as Git to track changes and contributions.