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DAM Taxonomy — 15,000 Assets

System

DAM Taxonomy — 15,000 Assets

I didn’t inherit an archive — I built one. The structure came before the tool: every field answers a question Sales or Curation actually asked, not a question an archivist would. Two layers, one naming grammar, and a metadata set that made the collection sellable.

I didn’t inherit an archive — I built one. The structure came before the tool: every field answers a question Sales or Curation actually asked, not a question an archivist would. Two layers, one naming grammar, and a metadata set that made the collection sellable.

Type

System

Format

Two-layer asset system + naming schema

From

AIR implementation · two-year digital transformation

01 · Context

When I started, the artwork lived in spreadsheets with documentation that varied piece to piece — roughly 3,000–4,000 images, and critical creative and financial details routinely lost between teams. Over two years it grew to 15,000+ assets under a single standard. I designed the structure so every field answered a question Sales or Curation actually asked — can this reproduce at the sizes clients buy? Who owns the rights? — then implemented the DAM around it. Every part of the system exists because someone downstream needed it to sell, license, reproduce, or legally share a piece.

02 · The artifact

Archive

15,000+ assets · single source of truth

Layer 1

File system of record (Drive)

Every artist has a folder; files organized by format — original, reproduction, wall covering, licensing, web upload. Artwork kept separate from production images and from sales/marketing collateral, so no one pulls the wrong asset onto a client call. Client-provided event and install material lives under the artist, flagged confidential, with use-rights tracked.

Layer 2 · AIR

The searchable layer (curation · sales · marketing)

Where accepted work becomes findable. Image specs captured at onboarding; every asset filterable by the questions a proposal actually starts from — artist, location, title, visual and style descriptors, market alignment. The tag set is extensible: a genuinely useful new descriptor gets added rather than forced into an existing field.

Naming schema

[ARTIST-LAST]_[WORK-TITLE]_[FORMAT]

e.g. Rivera_Morning@field_reproduction

Format is the load-bearing token: it routes the file to the right pipeline (original vs reproduction vs licensing vs web) and keeps sales collateral out of the production tool.

Schema fields

artist

location

title

medium

style

palette

market-alignment

rights-status

format

↳ recreated & sanitized · sample filenames illustrative · rights values generalized

03 · Outcome

15k+

15k+

assets on a single metadata standard, from ~3,000–4,000 at the start

75%+

75%+

of the reproduction collection reproducible at 50″+ — the large-format capture standard

majority

majority

of company revenue enabled — print-on-demand & licensing ran on this archive

This system was a revenue decision disguised as a filing system. In two years we took the capture required from none, to 40 inches, to 50 — and raising it is what made print-on-demand and licensing viable at scale. It also expanded the sellable collection: artists who couldn’t produce large physical originals could now earn from large-format reproductions. Every field earns its maintenance cost or gets cut.