This page serves as a home for my evolving approach to digital data archival. It contains my intentions, thought process, resources, and the current schema.

Why

• Data created over a lifetime begs to be archived, or risks extinction
• Housing data in the cloud has risks (service shutting down, privacy, etc.)
• Streaming services can’t guarantee content availability in the future
• There’s some emotional satisfaction to building a system that lasts

Goals

1. Simple - The simpler it is, the longer I’ll use and trust it
2. Intuitive - Should be useable without external knowledge a decade from now
3. Digestible - External organizing tools should be able to map it

Backups

The 3-2-1 backup rule should be implemented as much as possible:

3 - “Data doesn’t exist if there’s not at least three copies of it.”
2 - “Two copies are local, but on different devices.”
1 - “At least one copy off-site.”

RAID is not a backup!

Common Strategies

From my research, there seems to be a few schools of thought on how to organize data.

TODO: Add sources here.

By data type

Intent:

• I want to browse all the books in my collection.
• I want to point media player to movies directory.

Pros:

• Can be easily digested by external apps
• Less effort manually organizing by arbitrary subjects
• Less total directories/nesting

Cons:

• Directory structure isn't intuitive when looking for specific subject
• Required external dependencies for organizing by topic

By subject

Intent:

• “I want to browse all content about Linux.”
• “I want to save a random article about Woodworking.”

Pros:

• More intuitively navigate the file system when seeking data
• File types can easily be searched for versus searching by subject

Cons:

• Digestion into external apps more difficult
• Much more effort to initially organize

By date

Intent:

• “I want to see all photos I took from 2015.”
• “I want to see all movies released in 1945.”

Pros:

• Good for timelines of personal data (photos, school, medical, etc)

Cons:

• Difficult to navigate

Other Considerations

The level of effort to implement/maintain a system is important. There are at least these three aspects that need to be considered:

1. Initial - Effort to setup the system and do the initial sorting
2. Modification - Effort/complexity to add/edit data and update references
3. Navigation - Effort to navigate and find data

Example Schema

TODO: Move this to a gist and embed it so the history can be easily accessible.

tank/                                                            (root zpool)
  archive/                              (low avail, high compression dataset)
    literature/
      cheatsheets/
      manuals/
      papers/
      quotes/        
    software/
      fonts/
      operatingsystems/
      games/
        windows/
  media/           (high avail, low compression dataset - unoriginal content)
    .dump/                                        (staging area for new data)
      audiobooks/        
      ebooks/
      movies/
      movies3d/
      music/
      tmp/
      tv/
    README.txt                 (info about why things are organized this way)
    audio/
      audiobooks/
      comedy/
      music/
    literature/
      ebooks/
    video/
      courses/
      comedy/
      movies/
        Movie Name, The (YYYY)/
          metadata/
      movies3d/
        Movie Name, The (YYYY)/
          metadata/
      tv/
        Show Name, The (YYYY)/
          Season 01/
            metadata/
      youtube/
        Channel Name/
          video.name-videoid.mkv
          video.name-videoid-thumb.mkv
        Steve Jobs/
          something_something_interview-e4dF2s.mkv
        Elon Musk/
    subject/                       (content by subject... needs more thought)
      README.txt            (info file outlining how subjects are structured)
      Psychology/
        README.txt     (notes/paths to related media in ebooks, movies, etc.)
        Depression/
          Depression Education Course/
            01 - introduction.mp4
          Depression Sucks Paper.pdf
      Steve Jobs/
        README.txt        (paths to related content (books, movies, yt, etc.)
  vault/             (high avail, low compression dataset - original content)
    .dump/
      photos/
      documents/
    README.txt
    dwelling/
      Travel Trailer/
    finance/
      taxes/
      retirement/
      budget.xls
    travel/
      201804 - California Road Trip/
        photos/
        itinerary.pdf
    health/
      fitness/
      therapy/
    hobby/
      hiking/
      homelab/
      woodworking/
      diving/
      gaming/
      coding/
      trading/
    work/
      resumes/
      hiring/
      201910 - Company/                               (job start date YYYYMM)
    volunteer/
      pcta/
    misc/

Schema Notes

• Adding the ZFS datasets may be overkill. It makes the schema a bit less file system agnostic. I may move it to a separate post at some point.
• Need to think about data security (do I want my taxes available to anyone with access to the vault?).

Resources

• /r/datacurator
• gitmind.com/app/doc/7802011078
• Alternative Sorting Ideas

TODO: Find an add more of the resources I’ve used.