ASSURED Training useful vocabulary

A Data Subject is the observation about whom the data relates. 

Usually a Data Subject is a natural person, but in the context of ASSURED, we expand this definition to be the observation that is represented by a single row in microdata. 

Output Checkers assess outputs produced from sensitive data to ascertain if they can be considered 'Safe', because they are unlikely to lead to a disclosure that harms the Data Subjects, or not.

Many Trusted Research Environments require outputs to undergo a check before they are removed from the Safe Setting.

Sensitive Data refers to any form of data that has the potential to cause harm to the Data Subjects if it is misused. Whilst usually such concerns relate to the possible impact upon people, for example by revealing private information about someone, there are other reasons why a dataset may be sensitive including for commercial or environmental reasons. 

ASSURED has been designed to be as discipline-agnostic as is possible, that is to say that many of the principles will be the same whether the harm is to a person, business, or rare species. We therefore prefer to use the term Sensitive Data, as data that requires protection may not be personal data.  

Sensitive Data in our context are microdata, containing information at the individual-level. Each row in such a dataset will represent a single observation, be it a person, a household, or a business. Microdata are typically obtained from surveys, censuses, or administrative systems.