File naming and organization

A clear folder structure and file naming convention help when organizing your data. They are essential when collaborating with others. Like data management plans, there is no single method for structuring and naming data.

Folder Structure

Storing files in folders is a good way of cleaning up your data. A logical folder structure can also guide the user, making it easier to understand the content of a dataset. Some institutions already have a system that you need to follow. Many research groups also make their own guidelines for data storage. There is no standard convention, so if you need to create your own folder structure, some best practices are:

• Keep all files associated with a project in a single folder
• Use a consistent and informative directory structure
• Have a self-explanatory folder name that is only as long as necessary
• Avoid assigning the same name to a folder and a subfolder
• Keep public/private/secret data in separate folders
• Keep original RAW data untouched and saved
• Establish a folder hierarchy that aligns with the project. Example: Project / Data / Technology

Data from behavioural studies frequently contain many files that have different relationships to one another. Hence, it is important to create a folder structure in the planning phase of a project before the data is collected. All material relevant to the data should be entered into the data folders, including detailed data collection and processing procedures.

Here is an example of a folder structure from CodeRefinery:

project_name/
├── README.md # overview of the project
├── data/ # data files used in the project
│ ├── README.md # describes where data came from
│ └── sub-folder/ # may contain subdirectories
├── processed_data/ # intermediate files from the analysis
├── manuscript/ # manuscript describing the results
├── results/ # results of the analysis (data, tables, figures)
├── src/ # contains all code in the project
│ ├── LICENSE # license for your code
│ ├── requirements.txt # software requirements and dependencies
│ └── ...
└── doc/ # documentation for your project
 ├── index.rst
 └── ...

File Naming

Brief and descriptive file names are important in keeping your data files organized. A file name is a principal identifier for a file. A good file name gives information about what the file contains and helps to sort multiple files. This requires a consistent file naming scheme. As with folder structure, when collaborating with others, it is vital to have a good file naming convention.

Here are some tips for naming files:

• Keep your filenames to a reasonable length
• Order the elements in the name from general to specific
• Use file names to classify types of files
• Use meaningful abbreviations.
• Use underscore (_), hyphen (- ), or capitalized letters to separate elements in the name
• Don’t use spaces, periods, or special characters: ?!& , * % # ; * ( ) @$ ^ ~ ‘ { } [ ] < >
• Use a consistent date format, such as ISO8601: YYYYMMDD, and time if needed HHMMSS
• Explain abbreviations used in your data management plan
• Consider sorting when deciding the order of elements in the file name. File names starting with the date will sort differently than files starting with the project name.
• Use sequential numbering, leading with zeros for clarity (01, 02, …)
• For consistency, include the same elements/information in all files
• Do not use any personal information like a person’s name in a file name
• Avoid generic file names (Examples: MyData.txt)

There are lots of information you could include in a file name: project name, data types, experimental tasks or conditions, date of creation, the technology used. What you choose to include depends on how you plan to use the data later. You cannot include all the information in the file name. What is less important could go into a descriptive file instead.