Metavalidation

Metavalidation is a process used to evaluate the quality and reliability of data or information that has already undergone some form of validation. Instead of validating the primary data itself, metavalidation focuses on the methods, criteria, and results of the original validation process. It's a second-order validation, ensuring that the initial validation was performed adequately and produced trustworthy outcomes.

This technique is particularly useful in situations where the consequences of incorrect data are high, such as in scientific research, financial reporting, or regulatory compliance. Metavalidation helps to identify potential biases, errors, or limitations in the original validation procedure. It can involve reviewing the documentation of the validation, re-performing parts of the validation with different parameters, or comparing the results of the original validation with independent assessments.

The goal of metavalidation is to increase confidence in the validated data. By scrutinizing the validation process itself, organizations can gain assurance that the data meets the required standards and is fit for its intended purpose. This can lead to more robust decision-making and a reduction in risks associated with using unreliable information.