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Data validation

Data hygiene is essentially for conducting R&D collaboratively and scalably. To help you create clean, consistent data sets, we recommend leveraging the data hub's validation capabilities.

Basic validation​

When you create and edit columns, the following validation can currently be configured:

  • ID: Unique
  • File: Optionally, allowed extensions
  • Reference: Valid row in the referenced database
  • Select: Valid options
  • Text: Optionally, format such as SMILES
  • URL: Valid HTTP or HTTPS URI
  • User: Valid user

Advanced validation​

Need custom validation?

The data hub is highly customizable. Contact sales for assistance.

Below are examples of custom validations that can be configured for your organization:

  • File: Minimum or maximum number of items or format such as GenBank or PDB
  • Float: Minimum or maximum value
  • Text: Regular expression, format such as FASTA or InChI, or minimum or maximum length