CITI Training CUNY Researcher Practice Test 2025 – Complete Study Resource

A critical component of data lifecycle management involves ensuring that data is archived or disposed of properly after the study. This stage is essential because it addresses how data is handled once its primary use has been fulfilled. Proper archiving allows for data to be stored securely for future reference, ensuring it remains accessible for future analysis, audits, or compliance with institutional and legal requirements. Conversely, proper disposal of data is vital to protect sensitive information and comply with privacy laws, minimizing the risk of data breaches.

Other approaches, such as only focusing on the collection phase, do not encompass the full scope of data lifecycle management since they neglect subsequent stages that are crucial for data integrity and security. Limiting access to data solely to the lead researcher could hinder collaboration and transparency, which are important in research contexts. Lastly, while using proprietary software may have benefits, rigidly adhering to it is not a critical component of effective data lifecycle management; flexibility in tools can often lead to better outcomes depending on the specific needs of a study.