Which statement best describes data lifecycle management (DLM)?

The statement that best describes data lifecycle management (DLM) is that it refers to the tools and processes for handling data during a research study and after it concludes. DLM encompasses a comprehensive approach to managing data throughout its entire lifecycle, from the initial planning and collection stages through to storage, analysis, sharing, and ultimately, the archiving or disposal of data. This ensures that data is managed effectively to maintain its integrity, security, and utility over time.

In this context, the emphasis is on not just the collection of data but on the overall management strategies that involve how data is processed, accessed, shared among researchers, and preserved after the research findings are disseminated. Therefore, the focus on both the active phase of a research study and subsequent management practices reflects the holistic nature of DLM.

Options that suggest a narrower focus, such as only covering data collection methods, limiting DLM to just storage solutions, or confining it to quantitative research studies, do not capture the full breadth and significance of data lifecycle management. Each of those options fails to recognize that DLM applies to a variety of data types and incorporates practices for both qualitative and quantitative research, highlighting its importance in responsible research conduct.