DPP Data Model

The complete EPRS 16-category framework, built in

The platform implements the full EU Digital Product Passport data model defined by the European Parliamentary Research Service. Fifteen structured categories cover every data point the regulation requires — from material composition and supply chain facilities to carbon footprints, circularity scores, and substances of concern. Each category is stored per product and compiled into the final JSON-LD DPP document.

This is not a simplified summary. It is the actual regulatory data structure, ready for the delegated acts.

15 categories. Every data point accounted for.

Composition — Materials with percentages, fibre length, origin, and recycled content. Supply Chain — Multi-tier facility tracking with GPS coordinates and GLN identifiers. Environmental — Carbon footprint with Scope 1, 2, and 3 breakdown, water consumption, energy use, and methodology. Health and Safety — Substances of concern with CAS numbers, concentration levels, and REACH compliance status. Circularity — Recyclability index, disassembly instructions, recovery potential. Technical Performance — Durability score, expected lifespan, resistance properties, test standards.

Plus transport legs, documentation and conformity declarations, social and labour conditions, animal welfare certifications, brand information, identifiers, commercial data, cost and scale, and after-sales repair and recycling events.

Full relational data behind every category

Beyond the 15 DPP categories, the platform maintains normalised relational data for input materials with supplier provenance, certifications linked to suppliers or products or individual materials, compliance declarations with validity tracking, per-product carbon footprints with stage-level detail, multi-tier facility registries, and technical test results with laboratory provenance.

Every data point traces back to its source

The DPP is not a form you fill in. It is assembled from verified supplier data, AI-extracted documents, and your product catalogue — with a complete chain of custody. Every value records which supplier provided it, from which document it was extracted, and when. Auditors get traceability. You get confidence.

What is the EPRS 16-category framework?

The European Parliamentary Research Service (EPRS) defined a structured information framework for Digital Product Passports that categorises all the data a DPP must contain. This framework was developed to support the implementation of ESPR 2024/1781 and serves as the reference architecture for DPP data models across the EU.

Aura implements 15 of these categories as structured, per-product data fields that compile into the final JSON-LD DPP document. The categories cover the full lifecycle of a product: what it is made of (Composition), where it was made (Supply Chain), how it was transported (Transport), what environmental impact it has (Environmental), whether it meets safety standards (Health and Safety), how it can be recycled (Circularity), and more.

Each category is not a free-text field. It is a structured schema with specific data points. The Composition category, for example, stores individual materials with name, percentage, fibre length, origin country, and recycled content. The Environmental category stores carbon footprint data with Scope 1, 2, and 3 breakdown, water consumption, energy use, and the methodology used for measurement.

This structure matters because the CEN/CENELEC technical standards (prEN 18216, prEN 18223) will define how DPP data is exchanged between systems and registered in the EU central registry. A DPP built on structured, standards-aligned data will be interoperable from day one. A DPP built on unstructured text or proprietary formats will need to be rebuilt.

How is supplier data mapped to DPP categories?

The platform maintains a direct mapping between supplier-provided data and DPP categories. When a supplier uploads a document through the portal, the AI extracts structured data and routes it to the correct category automatically:

Certifications are polymorphic: they can be linked to suppliers, products, or individual materials. A single OEKO-TEX certificate from a supplier can be associated with every product that supplier manufactures. Carbon footprints are stored per product-supplier pair with Scope 1/2/3 breakdown, methodology, and stage-level detail (manufacturing, transport, use phase, end-of-life).

This mapping is not something you configure manually. The supplier data collection workflow handles it as part of the AI-powered document extraction process.

What output format does the DPP use?

The final DPP document is generated as JSON-LD, the linked data format specified by the W3C and referenced in the CEN/CENELEC prEN 18216 data exchange standard. The document carries contexts from three vocabularies:

• W3C Verifiable Credentials v2 — The credential envelope that makes the DPP a verifiable, cryptographically signed document
• GS1 vocabulary — Product identification using GTIN, GLN, and the Digital Product Passport type
• UNTP (UN Trade and Transport) — Supply chain and trade vocabulary for international interoperability

The JSON-LD format is served through the GS1 Digital Link resolver when a verifier requests the machine-readable DPP (via Accept: application/ld+json or ?linkType=gs1:dpp). Consumers scanning a QR code are redirected to the human-readable DPP landing page instead.

This dual-delivery model, one document serving both machine and human consumers, is core to how the EU DPP ecosystem will operate. Market surveillance authorities and customs officials will query the machine-readable JSON-LD. Consumers will see the branded product page.

How does data provenance tracking work?

Every data point in the DPP maintains a chain of custody recording:

• Which supplier provided the data
• From which document it was extracted (linked to the original uploaded file)
• Against which data request the document was submitted
• When the data was received and validated

This provenance chain satisfies the audit requirements of ESPR 2024/1781 and aligns with the CEN/CENELEC prEN 18221 standard for data storage and retention. When auditors or market surveillance authorities query a data point, they can trace it from the DPP back through the validation step, the supplier response, the original document, and the data request that initiated the collection.

The platform retains all provenance data for 10 years, aligned with the regulatory retention period specified in prEN 18221 for textiles and the Construction Products Regulation (CPR).

How Aura helps

Aura gives you the actual regulatory data structure, pre-built and ready for the delegated acts. You do not need to interpret the EPRS framework, build your own data model, or map supplier data to DPP categories manually. The platform handles the mapping, the data extraction, the provenance tracking, and the JSON-LD generation. When CEN/CENELEC standards are finalised and the EU central registry becomes operational, your DPPs are already in the correct format. No data migration. No reformatting. No reconfiguration.

Frequently asked questions

Does the data model support all product types or just textiles?

The 15-category EPRS framework is product-agnostic. It applies to all product categories that will fall under ESPR delegated acts, including textiles, electronics, batteries, furniture, and construction products. The specific data points required within each category may vary by product type, and the AI research assistant can tell you exactly which fields are relevant for your products.

How is the DPP data model different from a product information management (PIM) system?

A PIM stores commercial product data (descriptions, images, pricing). The DPP data model stores regulatory compliance data: material composition, environmental impact, supply chain transparency, circularity metrics, and substances of concern. The two are complementary. Aura ingests product identity data from your PIM or product catalogue and enriches it with the regulatory data required for compliance.

What happens when new delegated acts change the data requirements?

Aura’s regulatory team monitors EU legislative developments and updates the platform as new delegated acts are adopted. The AI research assistant knowledge base is rebuilt automatically. If a new delegated act introduces additional data requirements for your product category, the compliance assessment will flag the new gaps and guide you through the steps to fill them.

Can I export the raw DPP data for use in other systems?

Yes. The platform provides a full Item Trace API (GET /itemtrace?gtin={gtin}) that returns all 15 DPP data categories for a product in a single response. This is available through the GS1 Digital Link resolver and can be used for integration with external systems, reporting, or data warehousing.