This article explains the importance of applying file naming conventions and provides tips for your research data file names.

Introduction

File names are an important aspect of research data organisation and storage. Implementing a consistent system with descriptive names ensures that your files are easy to find and identify. This helps prevent loss of research data and supports efficient file sorting and retrieval by humans and computers.

Why is file naming important?

Descriptive systematic file names are essential for organising and easily identifying files, especially in collaborative settings. How a file naming convention, i.e. a framework or system for naming files, looks depends on your project and data types. However, there are certain key elements to consider that can help you implement a good file naming system for all types of research data. 

How should I name my files?

What is the most important information needed to describe, identify and categorise the contents of your file? This is typically a name or abbreviation used to describe the contents of the file themselves and/or the (sub)project. 

After identifying what is the most important information for understanding and categorising your files, you need to compliment this with other encoded information that describes the file contents. This will help you and others sort through your files. Think critically about what other information is the most important for describing file contents and try to keep file names within 30-35 characters. We recommend encoding information about:

• Date: use the international standard YYYYMMDD or YYYY-MM-DD
• File version: use leading zeros, v01 or v001 (depending on the number of versions you expect) instead of v1, for sequential sorting
• Project stage: identify if the file contains raw data, processed data, analysed data, documentation, writing, or other information related to a specific stage of your research
• another parameter that is most important to you, for example data type, method, etc. 

By implementing descriptive file names with (encoded) information, you can ensure that your files are accurately described in a way that can be easily decoded by others. When using abbreviations and acronyms to name your files, be sure that the document defining these naming conventions is stored with all copies of your research data. 

File naming tips to consider

Consider the following tips when setting up your file naming system:

• Avoid using spaces, periods or non-alpha-numeric characters such as #$^&()+=?\/!@*%{}[]<>. Some software programs don't recognise file names with these characters or struggle to retrieve them. Instead, use underscores, dashes, or CamelCase to differentiate encoded information.
• Avoid descriptive versioning, e.g. ‘final’, ‘this_is_the_newest_version’, ‘final_version_comments_final’. Files are never really final, it makes file names unclear and unnecessarily long and descriptive versioning is confusing to others. Instead, use a numeric system for versioning, and/or update the date in the file name to easily differentiate the newest and oldest version of a file. 

File naming example 

Instead of naming a file ‘data.csv’, a more descriptive and consistent file name could be: 
[project]_[filesubject]_[subsubject]_[date]_[version].[extension]

In a real-world setting, this could look like: 

ProjectName_Amsterdam_SurveyResponses_20250105_v01.csv

And could be abbreviated to:

PN_AMS_SurveyData_20250105_v01.csv

With the used abbreviations and/or codes defined and explained in your data documentation. 

Questions/Support

Do you have questions about this service or would you like personal support? Feel free to contact us. You can send an email to data@wur.nl.