How does Brainspace differentiate between 'Active' and 'Inactive' data?

The differentiation between 'Active' and 'Inactive' data in Brainspace is primarily based on assessing data usage frequency and relevance. Active data refers to data that is currently in use, being accessed frequently, or highly relevant to ongoing investigations or projects. This type of data is actively contributing to the decision-making process and is often the focus of analysis.

In contrast, inactive data may hold less relevance, have not been accessed for a significant period, or could be outdated in terms of the immediate context or objectives of the users. By evaluating how often and how relevant the data is to users, Brainspace can make informed classifications. This assessment helps organizations prioritize data review efforts, enhance storage management, and improve efficiency in data retrieval and processing.

Other options, while potentially relevant in different contexts, do not encapsulate the primary method of classification utilized by Brainspace. For example, simply considering data age does not consider how frequently it is accessed or its ongoing relevance to current tasks. Similarly, data formatting differences and user access levels do not inherently determine the active or inactive classification; rather, they serve different roles within data organization and security.