What is Structured data?

Structured data refers to information organized in a standardized format, usually following agreed-upon schemas or data models. This means that every piece of data — from a product’s material composition to its carbon footprint — is placed in a precise location within a digital “blueprint.” For Digital Product Passports, this structure ensures that anyone, anywhere, can understand the information without ambiguity.

Unlike unstructured data (such as free-text descriptions or scattered PDFs), structured data is predictable. A field called material_origin will always contain the origin details of a material, and a field called recycled_content_percentage will always represent exactly what it says — without room for misinterpretation.

The European Union’s upcoming regulations for DPPs make one thing clear: interoperability is non-negotiable. A DPP is not meant for one company or one platform — it must work across industries, borders, and digital ecosystems. Structured data is what makes this interoperability possible.

When a DPP stores data in a standardized, machine-readable format (such as JSON-LD, XML, or GS1 EPCIS structures), it enables:

• Instant access: Systems can retrieve exactly what they need in milliseconds.
• Data validation: Automated checks can confirm accuracy and completeness.
• Global compatibility: A DPP from a textile manufacturer in Italy can be read seamlessly by a retailer in Japan.

Without structured data, DPPs would be slow, error-prone, and vulnerable to misinterpretation — undermining the entire purpose of their creation.

Consumers and stakeholders are more likely to trust product information if it is consistent and verifiable. Structured data allows third parties, such as certification bodies or customs authorities, to quickly verify claims against recognized standards.

Imagine scanning a QR code on a shoe and instantly seeing:

• The precise percentage of recycled rubber in the sole
• The origin of the leather, linked to a certified farm database
• The CO₂ emissions of production, measured according to ISO standards

This is not a manually crafted marketing page — it’s structured, verified data pulled directly from the DPP, leaving no room for manipulation.

To ensure that structured data truly serves its purpose in a DPP, companies should:

1. Adopt an agreed schema — such as those recommended by the EU, GS1, or industry-specific alliances.
2. Ensure field-level accuracy — each field should only contain what it is intended to store.
3. Embed semantic meaning — using ontologies or linked data principles so machines can understand the context.
4. Keep it lightweight but complete — excessive complexity slows systems, but missing data reduces value.
5. Integrate validation tools — to prevent inconsistencies before publishing the passport.

As the Digital Product Passport becomes a legal and commercial requirement, structured data will form the “language” through which all products communicate their identity and history. It will allow AI systems to instantly compare sustainability scores, regulators to verify compliance in seconds, and consumers to make confident purchasing decisions.

In essence, structured data transforms a DPP from a static record into a living, interoperable, and trusted digital asset. Without it, the passport would be just another PDF in a crowded inbox — with it, the DPP becomes a powerful tool for a transparent, sustainable, and accountable marketplace.