Data lifecycle management (DLM) is best described as?

Data lifecycle management (DLM) encompasses the systematic processes involved in handling data throughout its entire lifespan, from initial collection, through processing and analysis, to its eventual archiving or disposal. This approach ensures that data is managed in a way that maximizes its value and minimizes risks associated with data loss or privacy concerns.

The correct answer emphasizes the importance of not only collecting and analyzing data but also the protocols and tools required for managing data responsibly both during the course of a study and afterward. This includes aspects such as data storage, organization, security, sharing, compliance with regulations, and ultimately deciding when and how to archive or delete data.

Other options fail to capture the complete essence of DLM. Retaining data indefinitely does not reflect a well-managed data lifecycle, where considerations for data relevance and storage costs are essential. A method for data visualization focuses specifically on how data is represented rather than how it is systematically managed. Lastly, simply collecting data from previous studies does not encompass the ongoing management and processing aspects of DLM.