I actually do not have much experience conducting studies but I have seen other research projects that have implemented data management processes similar to the ones you mentioned.
These processes are crucial for ensuring the quality, integrity, and security of research data. Maintaining an audit trail and time-stamping data is essential for tracking changes, ensuring data provenance, and enabling the reproducibility of the research. This typically involves logging all actions performed on the data, including who made the changes, when they were made, and what the changes were. Moreover, having a robust data backup and recovery plan is crucial to protect against data loss or corruption. This may involve regular backups to local or cloud-based storage, as well as the ability to restore data from these backups in the event of a system failure or other data-related incident.
For the software for data management, I have seen the researchers use specialized data management platforms (e.g., REDCap, OpenClinica, Qualtrics) which offer tailored features and workflows for their specific needs. Furthermore, cloud-based storage and collaboration tools were widely utilized and can facilitate secure data sharing, version control, and remote access.