Describe and document
This section aligns with the active data management stage of the research data lifecycle.
Proper documentation ensures research data is well-organised, understandable, and reusable in the long term – both during your project and into the future. This section outlines best practices for describing your data, including the use of metadata, consistent file naming, and version control strategies.
Data collection and creation
Maintaining good documentation practices as you collect and create research data will save time and reduce confusion later. You should capture information about your methods, tools, file formats, and workflows to support transparency, reproducibility, and collaboration.
Data description and documentation
Metadata is structured information that describes your data. This helps others (and future you) to understand, locate, and reuse it. Good metadata is essential for making data discoverable and meaningful.
Common metadata fields include:
- name of the data collection
- creator(s)
- date of completion
- description of the resource
- geographic area (if applicable)
- summary
- language
- copyright and licensing
- access conditions
- persistent identifiers (e.g. DOI, URL).
You may also use a separate documentation file (e.g. a README.txt) to provide extra context, such as:
- file structure and contents
- naming conventions
- software or tools required to use the data
- any quirks, limitations, or assumptions in the dataset.
Learn more on the ANDS Guide for Metadata.
Note
Describing your data in Deakin’s Research Data Planner (RDP) can make it visible in DRO and aggregators such as Research Data Australia (RDA), and through search engines like Google Scholar.
Use the Research Data Planner (RDP) to create a data record and, where relevant, link to your open dataset. Remember, shared data is only useful if others can understand it.
File naming best practices
Consistent, descriptive file naming helps you keep track of your data over time, especially in collaborative environments.
Consider the following tips:
- Organise files in a logical folder hierarchy.
- Use clear, descriptive file names (avoid vague terms like "final" or "new").
- Avoid spaces and special characters—use underscores or hyphens instead.
- Include relevant info such as project name, date (YYYYMMDD), and version.
See QUT’s Document Naming Convention help guide for a useful example.
Version control strategies
Version control helps you keep track of changes to your data, especially when multiple researchers are involved.
Depending on your software or setup, version control might include:
- using tools with built-in version tracking (e.g. Microsoft Word, Google Docs, Git)
- manually including version numbers or timestamps in file names
- maintaining a single master file and tracking edits separately
- keeping a version log or changelog to record updates.
Establish a clear version control approach early in your project, and make sure all team members follow it consistently.