What is the distinction between "de-identified" and "anonymized" data?

The distinction between "de-identified" and "anonymized" data lies in the levels of identifiers that may remain in each type of data. De-identified data is data that has had all personally identifiable information removed to protect individuals' privacy, but it may still retain some indirect identifiers that could potentially be used to re-identify the data under certain circumstances. This could include specific demographic information or other details that, in combination with other data, might allow for re-identification.

Anonymized data, on the other hand, goes a step further. It is processed to completely remove any possibility of tracing the information back to an individual. In anonymization, not only are direct identifiers removed, but features or characteristics that could inadvertently lead to identification are also effectively eliminated.

Understanding this distinction is crucial in contexts where privacy regulations and data protection policies are concerned, as the methods of handling each type of data have different implications for compliance with legal standards and ethical considerations in research and data sharing.