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This feature is part of a paid plugin that is not part of enterprise or community edition. Email contact@krishagni.com for more details. |
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Introduction
Data validation is used to enter can be used to add validation rules to fields to ensure high-quality data. This ensures that while entering the data, the user does not violate any data entry rules. These rules can be defined either at the system level or at the CP level and the CP level take precedence over the system- level validations. They can be defined as below:
Data Validation is a series of constraints designed to check the validity of the input data.
Data Validation constraints can be made of variables of a single record or multiple records.
Data Validation is like database check constraints designed to ensure high-quality specimen data is collected.
For example
. This ensures that the user does not violate any data entry rules while entering the data.
Examples:
Participant age at the time of registration should be more than 18 yearsOnly male participant registrations are allowed
Frozen event timestamp should be later than the specimen creation time.
Defining Data Validation
Data validations can be defined using JSON. The ‘editChecks’ section of the code needs to be inserted after the ‘dictionary’ section in the workflows JSON.
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Example: Visit date should be same or later than the registration date
For more examples, please refer to the wiki page Data Validation Examples
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Adding Multiple Edit Checks in Same Workflow
In case there are many edit checks to be performed, here is a tip that could help in avoiding errors:
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When value for ‘Have you ever smoked’ in ‘Smoking History’ form is ‘Yes’, the error ‘Smokers not allowed!’ should be thrown.
Data Validations Rulesare supported for the below:
Participant Fields, Custom Form, and Custom Fields
Visit Fields, Custom Form, and Custom Fields
Specimen Fields, Events, Custom Forms, and Custom Fields
Shipment
Order
More details
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