JRC DPP Data Framework: Essential, Recommended or Voluntary
How JRC145830 helps prioritise DPP data, and why its research categories do not create legal obligations.
JRC Publishes a Framework for DPP Data Prioritisation
On 19 March 2026 the European Commission’s Joint Research Centre (JRC) published JRC145830: Methodology for defining data requirements for the Digital Product Passport under the ESPR framework. The report presents a structured, repeatable methodology for proposing which data should appear in a Digital Product Passport and why.
It is a public research report addressing a question many companies preparing for DPP are asking: how can data points be prioritised as essential, strongly recommended, or voluntary? It is a research methodology intended to inform delegated acts and impact assessments, not a binding legal field list in itself.
The Core Idea: Three Tiers
The three labels below simplify the JRC’s prioritisation approach. Step B.4 assesses usefulness, effort and feasibility; Table 15 uses six illustrative categories (A–F), not three fixed legal categories:
| Tier | What it means | Practical implication |
|---|---|---|
| Essential | Data considered necessary for a use case or proposed regulatory purpose | Mandatory only where the applicable law requires it, from the relevant application date |
| Strongly recommended | High value-to-effort ratio; clearly useful to regulators, consumers or value-chain partners | May inform later mandatory field lists, but is not automatically mandatory |
| Voluntary | Data outside the applicable mandatory dataset, potentially of high or low value | Assess its usefulness and disclosure conditions; voluntary does not mean unimportant |
The framework does not replace the ESPR or sector-specific regulations. It provides a systematic way to prioritise data preparation before final field lists are confirmed in delegated acts.
Why This Matters Now
1. It reduces guesswork
The JRC methodology adds a documented assessment process to the ESPR, working plan and preparatory studies. It helps teams explain why a data point merits preparation.
2. It validates early preparation
Early preparation remains useful, but the methodology does not guarantee the future field list. Separate existing legal obligations from proposed requirements and internal priorities.
3. It applies beyond ESPR
The JRC explicitly notes that the modular methodology can be applied outside the ESPR framework where equivalent context and feasibility analyses are carried out. This is relevant for standalone DPP mandates already in sector legislation: the Battery Regulation (EU) 2023/1542 (battery passport obligations from 18 February 2027), the Toy Safety Regulation (EU) 2025/2509 (from 1 August 2030) and Regulation (EU) 2026/405 on detergents (from 23 September 2029). Each of these acts already defines its own minimum dataset in its own annex, which is why the JRC framework is a method for prioritising data in future delegated acts rather than a substitute for the confirmed sector lists.
What the Methodology Does Not Do
The report intentionally limits its scope:
- It does not prescribe a binding encoding standard. It does address semantic definitions, vocabularies and ontologies in Step C.
- It does not publish final field lists for any product category; those will come through delegated acts.
- It addresses DPP system architecture only to the extent needed to inform data access rights, governance and granularity decisions.
JRC145830 supports proposals about data content and its semantic organisation. It is neither a final legal dataset nor a complete technical implementation specification.
Practical Takeaway for Companies
If you are already mapping product data for DPP purposes, the JRC methodology supports a structured prioritisation workflow. One practical way to apply it is the model described in the DPP data requirements guide: use five core data layers (identity, operator, composition, sustainability, traceability) and use the three categories to prioritise data within each group for your product category.
For a detailed walkthrough of the three tiers and sector-by-sector examples, see the full reference article: DPP Data Classification: Essential, Recommended, Voluntary.
Read Next
- DPP Data Classification: Essential, Recommended, Voluntary: full reference guide
- DPP Data Requirements: What Data You Actually Need
- What is a Digital Product Passport (DPP)?
- EU Commission ESPR Working Plan 2025–2030: DPP Timeline and Sector Priorities
Official Sources
- JRC145830: Methodology for defining data requirements for the Digital Product Passport under the ESPR framework
- ESPR Regulation (EU) 2024/1781
Start preparing for DPP by organising the data for one product. Try OriginPass.eu to see how you can present it in a digital passport.