Planned Dropbox storage migration and cleanup

• Day: 2026-06-08
• Time: 11:40 to 11:50
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: HIGH
• Assignee: Matías Nehuen Iglesias
• Tags: Dropbox, Data-Migration, Storage-Governance, Manifest, Deduplication, Backup

Description

Session Goal

Reframe a Dropbox space problem as a storage governance and migration task: keep Dropbox as a lightweight coordination layer while moving heavy research datasets and project artifacts to local/external archival storage.

Key Activities

• Reviewed multiple instructions and plans for Dropbox cleanup, including staged migration, manifest-based verification, and reversible pointer-file workflows.
• Defined a classification rule for what should remain synced in Dropbox versus what should be archived or deduplicated elsewhere.
• Established a migration priority heuristic: maximize storage saved while minimizing risk, starting with raw/source data, then duplicated project folders, then code and documentation.
• Outlined a parallel Dropbox_data mirror approach to preserve path intuition while reducing sync pressure.
• Included operational safeguards such as README pointer files, manifest generation, duplicate detection, and post-migration sync reconciliation.

Achievements

• Clarified the technical strategy for reducing Dropbox footprint without losing recoverability.
• Produced a reversible migration model that avoids breaking folder references by leaving pointer READMEs in place.
• Identified verification steps to confirm that heavy data has been removed from the synced Dropbox directory and that cloud storage is actually freed.
• Separated coordination files from bulky research data, making the storage architecture more maintainable.

Pending Tasks

• Execute the folder inventory and classify each path by sync necessity.
• Move heavy datasets to the external/local archive and generate manifests for moved content.
• Check for duplicate project folders before deletion.
• Verify Dropbox reconciliation after deletions and confirm the synced folder is lightweight.
• Add policy/README pointers to prevent accidental re-syncing of large datasets.

Evidence

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• event_ids: []