File Names

File names are frequently overlooked, but are key to locating and retrieving files efficiently, especially for complex or collaborative projects.

Adopting a consistent, logical and descriptive file naming convention is good practice and will assist with data analyses and re-use.

Abbreviations and codes can be used, providing they are clear and uniformly applied. If necessary include a README.txt file in the directory (folder) that explains the naming format and any abbreviations or codes used.

File names can include information such as:

• Project or experiment name or acronym
• Researcher name/initials
• Year or date of experiment
• Location/spatial coordinates
• Data type
• File version number

The formatting of file names, file paths and field names (in databases) is very important. Poorly formatted names affect readability and can cause compatibility and processing issues i.e. when sharing data files across platforms, migrating and backing up data, working with command-line interfaces or scripting languages, web servers or URLs.

You should avoid:

• special characters such as ~ ! @ # $ % ^ & * ( ) ` ; < > ? , [ ] { } ' ‘| While there are differences between the Windows and MacOS operating systems (e.g. colons cause  problems in Windows and not on Macs) it is advisable to steer clear of special characters;
• spaces in file names. Modern systems and applications have become more lenient regarding spaces but best practice is to use underscores ( _ ), dashes ( - ), or camel case (e.g. FileName) instead, and to apply them consistently;
• lengthy file names. For example, Windows has a 250 character limit for file paths. This includes the local drive prefix e.g. C:\Users\jc*****\OneDrive - James Cook University - so lengthy file names and/or a deep file structure can cause issues.

Some examples using dates, versions or timestamps:

Dates – for time-bound data where the date is part of the content (e.g. interviews, observations).
Example: 20250714_interview_Townsville_P01.wav

Versions – for evolving files where iterations need tracking (e.g. cleaned datasets, transcripts).
Example: interview_Townsville_P01_transcript_v02.docx

Timestamps – for code or analyses where creation/run date is useful, optionally with versions.
Example: 20250714_analysis_pipeline_v01.py

Renaming multiple files is onerous but there are bulk renaming utilities that can help, such as:

Windows

• PowerRename (part of Microsoft PowerToys) — a good option if you prefer a Microsoft-supported tool
• Bulk Rename Utility — a powerful and flexible free tool for more advanced renaming

Mac:

• Renamer 4

See also:  Maketecheasier for additional suggestions for Windows tools.