Strategies to recover and continue critical research phases after data loss: - Ensure regular backups of research data to an external drive, cloud storage, or both. - Utilize version control systems like Git to track changes and maintain a record of all data versions. - Employ data recovery software, such as Recuva or EaseUS, to attempt to recover lost data. - Maintain redundant data storage, such as duplicate datasets or mirrored drives, to minimize data loss. - Recreate Lost Data (If Possible): If data cannot be recovered, attempt to recreate it by re-running experiments, re-collecting data, or re-analyzing existing data. - Inform stakeholders, including team members, supervisors, and clients, about the data loss and recovery plan

First, I’d assess backups, such as cloud storage, external drives, or institutional systems, to recover lost data. If unavailable, I’d leverage any interim analysis, drafts, or shared data from collaborators to reconstruct key elements. Learning from this, I’d implement robust data management protocols, including automated backups and version control, to prevent future losses. Continuity comes from resilience and adapting quickly to safeguard critical progress.