Short answer
The Metadata Model Builder returns a starter DAM metadata schema for one of six industries: 12 core fields for every asset plus 5 industry fields, 17 fields in total. Each field carries a data type and a rule: mandatory, conditional or optional. The schema exports as JSON for configuring vendor demos and the proof of concept, once daily users have validated it.
How it works
The Metadata Model Builder joins one fixed core layer with one industry layer and shows the result as a table of field, type, rule and layer.
- Pick an industry: manufacturing, retail, CPG, fashion and apparel, pharma and life sciences, or media and publishing.
- The tool lists the 12 core fields, marked Core, followed by the 5 fields for that industry, marked Industry.
- The heading reports the field count, 17 for every industry.
- The JSON export holds the industry key and a list of fields, each with field name, type, rule and layer.
A metadata schema is the set of fields, data types and controlled vocabularies that describe every asset in a DAM. The core layer covers description, ownership, status, rights, channels, alt text and AI involvement.
The 12 core fields
| Field | Type | Rule |
|---|---|---|
| Title | Text | Mandatory |
| Description | Text | Optional |
| Asset type | Picklist | Mandatory |
| Brand | Picklist | Mandatory |
| Owner | User | Mandatory |
| Status | Picklist: Draft, In review, Approved, Expired, Archived | Mandatory |
| Usage rights | Picklist: Owned, Licensed, Restricted | Mandatory |
| Rights expiry | Date | Conditional |
| Channels permitted | Multi-select | Mandatory |
| Regions permitted | Multi-select | Optional |
| Alt text | Text per language | Mandatory for images |
| AI involvement | Picklist: None, Edited, Generated | Mandatory |
Industry layers
| Industry | Industry fields with rule |
|---|---|
| Manufacturing | Product SKU (mandatory), Product family (mandatory), View (optional), Technical document type (conditional), Dealer visibility (optional) |
| Retail | Product SKU (mandatory), Season (mandatory), Shot type (mandatory), Marketplace (optional), Colourway (conditional) |
| CPG | Product SKU (mandatory), Market (mandatory), Artwork version (conditional), Regulatory approval (conditional), Retailer (optional) |
| Fashion and apparel | Style number (mandatory), Collection (mandatory), Model release (conditional), Colourway (mandatory), Shoot (optional) |
| Pharma and life sciences | Product (mandatory), Market (mandatory), Review number (mandatory), Claims approved (conditional), Review expiry (mandatory) |
| Media and publishing | Publication (mandatory), Credit (mandatory), Syndication rights (mandatory), Event date (optional), Location (optional) |
Worked example
The Metadata Model Builder opens on manufacturing, and the starter schema holds 17 fields.
Worked example: a manufacturer keeps the default industry. The schema holds 10 mandatory fields, 1 field mandatory for images, 2 conditional fields and 4 optional fields.
- Mandatory: Title, Asset type, Brand, Owner, Status, Usage rights, Channels permitted, AI involvement, Product SKU and Product family.
- Mandatory for images: Alt text, per language.
- Conditional: Rights expiry and Technical document type.
- Optional: Description, Regions permitted, View and Dealer visibility.
The builder names a rule and leaves the condition to the workshop. The manufacturer sets Rights expiry as required when Usage rights reads Licensed. Technical document type becomes required when Asset type reads document.
Product SKU is typed as a relation to the PIM. The value links each asset to a product record, and product data stays in the PIM. DAMSelection assessment: DAM and PIM form one product content supply chain, so the SKU relation is the first field to test with the PIM team.
How to use the result
The Metadata Model Builder output belongs in Checkpoint 2, Define, and returns at Checkpoint 5, Test, as configuration input for every vendor.
- Run a workshop with daily users and walk through every field, rule and picklist value.
- Write the conditions for each conditional field and the values for each picklist, using a controlled vocabulary.
- Design the facets for search with the DAM taxonomy guide.
- Send the validated schema with the scenario "Configure our metadata schema" from the Demo Script Generator.
- Reuse the schema in the proof of concept and later in metadata mapping for migration.
DAMSelection assessment: the metadata model decides DAM success, so design it before the first demo. The metadata schema design guide explains field design in depth.
Limitations
The Metadata Model Builder gives a starter schema, and five gaps need work before configuration.
- Most picklists arrive without values. Brand, Asset type, Season and Market need your own vocabularies.
- Conditional rules carry no condition. The workshop writes each one.
- The six industries cover common patterns only. Organisations that span two industries merge both layers by hand in the JSON.
- Alt text is the only field defined per language. Multilingual titles and descriptions need a decision on translated values.
- The schema holds no mapping to embedded metadata. The IPTC Photo Metadata Standard defines embedded fields such as Title and Description that a DAM reads and writes.
A starter schema needs workshop validation with daily users before configuration. The other DAM selection tools use the validated schema at Test.
Frequently asked
What metadata fields should a DAM have?
A DAM needs fields for identity, ownership, status, rights, channels, accessibility and AI involvement on every asset, plus industry fields that link assets to products or publications. The Metadata Model Builder proposes 12 core fields and 5 industry fields as a starting point.
What is the difference between mandatory and conditional metadata?
A mandatory field must hold a value before an asset can be saved or approved. A conditional field becomes mandatory only when another field holds a set value. Rights expiry, for example, becomes required when Usage rights reads Licensed.
Why does the DAM schema include an AI involvement field?
The AI involvement field records whether an asset was untouched, edited or generated with AI, using the values None, Edited and Generated. Teams use it to label AI content, filter it in search and answer disclosure questions. The [EU AI Act guide](/dam/learn/eu-ai-act-generated-assets/) covers the obligations.
Can I export the DAM metadata schema?
The DAM metadata schema exports as a JSON file after a work email. The file holds the industry and every field with name, type, rule and layer. Vendors can load it in the scripted demo, and the same file supports the proof of concept and migration mapping.
How many metadata fields should a DAM schema have?
A DAM schema needs enough fields to find, govern and distribute every asset, and each mandatory field adds work at upload. The Metadata Model Builder starts at 17 fields with 10 mandatory. Remove fields that no search, rule or channel uses before configuration.
Script your demos
Give every vendor the same scenarios and pass criteria.