Best Practices

Follow these best practices when building fields and templates in CEDAR:

  1. Naming Fields

    Naming fields

    • For the “Field name” label, use snake_case format (e.g., parent_dataset_id instead of Parent Dataset ID).
    • For the “Preferred Label”, use title case format (e.g., Parent Dataset ID).
  2. Creating Descriptions
    • Provide clear and concise descriptions for each field.
    • Include an example value after the description. For example, the “Parent Dataset ID” field description could be: Unique identifier of the dataset used to generate this derived dataset. Example: HNDF-123-HH..
    • Use ChatGPT or other LLM tools to improve the text quality when writing the description.

  3. Naming Boolean Fields

    Naming boolean fields

    Use a question format for boolean fields (e.g., is_rehydrated, is_cell_type_annotation_included) to indicate a “Yes” or “No” response.

  4. Using Regular Expressions for Identifier Validation

    Using regex for identifier validation

    • Apply regular expressions to ensure identifier fields match specific patterns. To do this, select the “OPTIONS” setting and enter the desired regex in the “Enter Regex” field.
    • Common regex patterns:
      • ORCID: (\d{4}-){3}\d{3}(\d|X)
      • DOI: 10\.\d+/.*
      • UniProt ID: ([A-N,R-Z][0-9]([A-Z][A-Z, 0-9][A-Z, 0-9][0-9]){1,2})|([O,P,Q][0-9][A-Z, 0-9][A-Z, 0-9][A-Z, 0-9][0-9])(\.\d+)?]
      • ISBN: (-13|-10)?[:]?[ ]?(\d{2,3}[ -]?)?\d{1,5}[ -]?\d{1,7}[ -]?\d{1,6}[ -]?(\d|X)
    • Tip: Visit Identifiers.org for more regex examples.
  5. Using Value Set vs. Multiple Choice
    • Decide between value sets and multiple choice based on whether the values are shareable concepts. Use Multiple Choice for non-shareable values, such as a collection of input parameters.