u/marcioyared

Not because the catalog is bad, but because the archive itself becomes fragmented over time.

That was exactly what happened to me after more than 25 years of accumulated media spread across:

• old cameras

• multiple Macs

• external drives

• exports

• backups of backups

• messaging apps like ICQ, MSN and WhatsApp

The problems became increasingly familiar:

• duplicate files propagated across imports and exports

• media without GPS metadata

• missing or inconsistent dates

• folders distributed across multiple drives

• filenames generated by devices and apps that became completely unintelligible over time

Things like:

3A0D38C7-528F-4DA8-840D-F95655F5F879.jpg

At some point, I realized the problem was no longer the catalog itself. The archive had lost structural consistency.

So I built a workflow focused on the filesystem layer itself:

• reorganizing media into a predictable folder structure

• separating duplicates instead of silently deleting them

• recovering missing dates using available file metadata

• isolating unresolved media for manual review

• renaming files into human-readable chronological structures

For example:

France/Ile-de-France/Paris/2015/

France - Ile-de-France - Paris - 20150403110113.000.jpg

If this normalization step is executed before importing media into a catalog system, the files always remain in the same place and consistently aligned with the catalog metadata.

The benchmark eventually processed:

• 363,575 media files

• 2.1 TB of archives

• 25 years of accumulated media

• multiple drives and fragmented libraries

• 392 hours of long-running execution

The goal was never to replace Lightroom or other DAM systems.

The goal was to make the archive itself understandable again.

If people are interested, I can share more details about the workflow and structure I ended up using.

Over the years I ended up accumulating 10 different Apple Photos libraries across multiple Macs, imports, exports and backup copies.

When I changed Macs in 2016 and again in 2019, I kept older libraries as safety backups before migrating everything. Over time this slowly created duplicated media, fragmented organization and inconsistent structures between libraries.

The archive also contained media going back to the early 2000s, long before GPS metadata became common in cameras and phones, so many photos simply had no location information at all.

At some point I realized the Photos libraries themselves were gradually becoming operational archives rather than clean photo collections.

So before consolidating and importing everything again, I normalized the archive structure at file level first.

The normalization process eventually handled:

• 10 Apple Photos libraries
• 116,445 media files
• duplicated photos and videos
• older media without GPS metadata
• backup libraries accumulated across years of Mac migrations

The goal was not to replace Apple Photos, but to prepare a cleaner and more consistent archive before importing everything again into a new organized library.

During normalization:

• duplicated media was not copied to the destination folders
• media without GPS metadata was isolated for later review
• the remaining files were reorganized into a deterministic archive structure before import

After normalization, the libraries became much easier to consolidate into a cleaner Apple Photos workflow without carrying years of duplicated structures and fragmented imports forward again.

One interesting thing during the process is that managed Photos libraries behaved much more predictably than the exported backup structures accumulated over the years.

Most of the structural fragmentation actually came from:

• backup copies
• exports
• duplicated migrations
• recursive archive accumulation
• inconsistent imports between libraries

Files/year

 

I’m curious how other long-time Apple Photos users handle:

• multiple libraries
• Mac migrations
• backup libraries
• duplicated imports
• older photos without GPS metadata

I also documented parts of the normalization process while rebuilding the archive. Happy to share more details if anyone is interested.

P.S.: English is not my native language. The text was reviewed with AI assistance, but the benchmark, analysis, and operational observations are entirely real-world results from the normalization process.