# Develop a DPP data model: products, batches, fields and versions

> How to design inheritance, identifiers, multilingual values, evidence and releases for a scalable product-pass system.

- Category: Data
- Last reviewed: 17 August 2026
- Canonical HTML version: https://dppready.de/en/knowledge/dpp-data-model

A durable data model separates stable identity, variable product data, evidence and immutable published versions. It should reflect the company’s real product structure.

## In brief

- Separate model, variant, batch and item levels.
- Store values with source, unit, language and validity.
- Publish immutable snapshots instead of live drafts.

## Choose entities and relationships

Represent product families, models, variants, batches and individual items only where they add meaning, with clear inheritance and overrides.


## Describe values properly

A field needs a stable code, type, unit, language, source, owner, validity, visibility and validation rules rather than just a label and text.


## Version releases

Keep working data editable but create immutable approved snapshots for public access, audit and reproducible exports.


## Frequently asked questions

### Should every value be copied to every product?

No. Inheritance reduces duplication when overrides remain explicit and traceable.

### Can the database schema remain flexible?

Yes. Versioned field schemas can add flexibility without sacrificing validation and stable field codes.

## Official sources

- [EU Regulation 2024/1781 (ESPR)](https://eur-lex.europa.eu/eli/reg/2024/1781/oj)
- [European Commission Digital Product Passport Registry](https://single-market-economy.ec.europa.eu/single-market/digital-product-passport/dpp-registry_en)

This content is general information and does not constitute legal advice or a compliance guarantee.