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File tree (path) and filename

A clear and consistent file naming convention, along with an organized folder structure, is essential for making data more accessible and reusable. For this reason, Stewards must ensure that file names and directory structures are properly formatted and meaningful.

You can review this information in the Dataset Files tab, where all relevant file details are displayed.

Figure 1: Table with all information related to the dataset files

In the default table view, you can see a list of all dataset files along with their metadata. By switching to the Tree view, you can visualize the folder structure more clearly, making it easier to navigate through subdirectories and locate specific files.

Figure 2: Tree view with the file paths related to the dataset files

Best practices for file naming:

  • Descriptive Names:

    • Are file names clear and explain the content (e.g., experiment1_results.csv)?
    • Avoid vague or generic names like data1.csv.

  • Consistent Formatting:

    • Do all file names follow the same pattern?
    • Use underscores (_) or hyphens (-) instead of spaces.

  • Versioning (if applicable):

    • Does version information (e.g., dataset_v1.0.csv) indicate updates or revisions?

  • Character Restrictions:

    • Do file names only use A-Z, a-z, 0-9, hyphens (-), or underscores (_)?
    • Avoid special characters like &%, $#, : , or ).



Best practices for folder structure:

  • Logical Organization:

    • Are files grouped into folders based on experiment, data type, time period, or other relevant categories (e.g., raw_data/, processed_data/, scripts/)?

  • Clear Hierarchy:

    • Is the folder structure simple and easy to navigate?
    • Avoid overly deep nesting of folders.

  • README Files:

    • Is there a README file in the main dataset folder that provides an overview, data structure, and key information?