The proliferation of Digital Product Passports (DPP), driven by regulatory demands for sustainability, faces significant challenges from semantic fragmentation. This paper proposes a novel approach to achieve global semantic interoperability by embedding UN/CEFACT Transparency Protocol (UNTP) semantics as a submodel within the Asset Administration Shell (AAS). The AAS provides a robust technical vehicle, while UNTP ofers a sector-agnostic, internationally recognized semantic base. We formalize how UNTP DPP semantics can be structured as an AAS submodel, illustrate its potential for cross-sector interoperability, and contextualize sectorspecific ecosystems as downstream applications. This alignment aims to create a scalable and coherent foundation for DPPs, with the aim of mitigating duplicate eforts. The paper explores architectural implications, integration with data spaces, and synergies with existing standards.
The global shift towards sustainability has made Digital Product Passports (DPP) a crucial component of
industrial policy and regulation, such as the EU’s Ecodesign for Sustainable Products Regulation (ESPR)
[
To address this, we propose a framework for global semantic interoperability by embedding the
semantics of the UN Transparency Protocol (UNTP) [
The remainder of this paper reviews the relevant background on DPPs and related standards (Section 2), details the proposed UNTP-AAS integration (Section 3), illustrates its application with a use case (Section 4), discusses key challenges (Section 5), and summarizes our findings and outlines future directions (Section 6). Asset Administration Shell (AAS) Digital Twin of the Asset (IEC 63278)
Semantic Anchoring via semanticId
UNTP DPP Specification (Global Semantic Definitions)
StandDaardtaizEexdcAhAanSgAePIs /
DPPs are evolving into regulatory requirements under policies like the ESPR, which mandate them for
products such as batteries, electronics, and textiles. DPPs must support unique product identification,
standardized data structures, lifecycle data management, and robust access control [
Several architectures exist for product information. GS1 EPCIS 2.0 focuses on event-based
traceability, while the EU’s EPREL database supports energy labeling but lacks an open ontology. The Asset
Administration Shell (AAS), a de facto standard in Industrie 4.0, provides a modular framework for the
representation of digital assets. A crucial feature of AAS is its ability to link every element of the data
to an external semantic definition via a globally unique semanticId, ensuring data can be correctly
interpreted between systems [
Large-scale data space initiatives like the sector-agnostic Gaia-X [
This highlights the need for a neutral and globally harmonized semantic foundation. The UN/CEFACT
Transparency Protocol (UNTP) is designed to fill this gap. Based on the UN/CEFACT CCL, the UNTP
DPP specification defines a lightweight structured model for B2B data exchange, focusing on product
identification, provenance, emissions, circularity, and conformity claims [
We propose operationalizing the UNTP-AAS integration through a dedicated AAS Submodel Template
for DPPs in Figure 1. The UNTP DPP specification [
Table 1 illustrates how representative UNTP DPP data fields (i.e. product identification, materials provenance, and emissions data) can be mapped to AAS Property and
Product GTIN
Material Name
Carbon Footprint
URI: <untp_vocab>/Product#idValue From Product.name URI: <untp_vocab>/Product#name From MaterialsProvenance.Material.name URI: <untp_vocab>/Material#name
MaterialsProvenance.Material.massFraction URI: <untp_vocab>/Material#massFraction From EmissionsScorecard.carbonFootprint URI: <untp_vocab>/...#carbonFootprint
EmissionsScorecard.reportingStandard.name URI: <untp_vocab>/Standard#name Property; idShort: “ProductGTIN" Property; idShort: “ProductName"
Property; idShort:
“MassFraction"; Unit: %
Property; idShort:
“CarbonFootprintValue"
Property; idShort:
“PCFReportingStandard"
SubmodelElementCollection types from the AAS Metamodel v3.0.2 [
This integration yields significant architectural advantages. By embedding DPP data natively within
the digital twin, the information becomes an integral part of the asset’s comprehensive digital
representation, accessible via standardized AAS APIs. This approach complements emerging federated data space
architectures such as Gaia-X, where the data space provides the identity and exchange infrastructure,
while the AAS-based DPP supplies the standardized, semantically rich data payload. Furthermore, the
framework is highly synergistic with other industrial standards. In joint architectures [
The ECO-TCO project [
The proposed UNTP-AAS framework ofers a structured solution to address the project’s needs. An AAS serves as the central digital twin for the product, consolidating data from PLM, MES, and ERP systems into dedicated submodels. A specific DPP submodel, structured with UNTP semantics, provides standardized and verifiable sustainability data (e.g., recycled content, carbon footprint). This semantically harmonized data can then be reliably used in TCO calculations and EPD generation, improving data quality, reducing integration efort, and ensuring alignment with regulatory requirements, thus demonstrating that a common semantic layer is not merely a convenience but a prerequisite for automating such complex, cross-domain sustainability analyses. The project serves as a compelling example of how standardized DPPs can deliver tangible business and environmental value.
The vision of globally interoperable DPPs based on UNTP and AAS is promising, but requires navigating
several interconnected challenges. On a semantic level, a primary task is to bridge the conceptual
diferences between UN/CEFACT’s origins in static trade data and the dynamic, event-driven nature of
digital twins. To avoid being perceived as a competing standard, the strategy must emphasize its role as
a harmonization layer, providing authoritative mappings or ’crosswalks’ to established domain-specific
models like GS1 and ECLASS, rather than seeking to replace them. This approach is exemplified by the
joint architectures mentioned earlier, where UNTP provides the neutral semantic layer that connects
and adds value to established standards like ECLASS and OPC UA. A potential mitigation is to develop
collaborative "semantic profiles" and clearly position UNTP as a foundational B2B data layer that
feeds more dynamic, consumer-facing DPP applications. On a technical level, the lack of large-scale
implementations and the perceived complexity of AAS and semantic technologies, especially for SMEs
[
Beyond technical and semantic issues, the challenges of governance and adoption are paramount.
A mismatch often exists between the agile development cycles required by industry and the more
deliberate, consensus-driven pace of standards bodies like UN/CEFACT. Establishing formal liaisons
and joint working groups can help align these timelines. A more critical challenge lies in ensuring
robust data security, privacy, and granular access control for sensitive DPP information. This requires
leveraging native AAS security features and aligning with established data space trust frameworks
such as the International Data Spaces (IDS) model. Architectural design must explicitly incorporate
privacy-by-design principles and mechanisms for intellectual property protection, compliant with legal
frameworks like GDPR and the EU Data Act [
This paper argued that the embedding of UNTP semantics within AAS submodels ofers a powerful and globally viable solution to the challenge of DPP interoperability. The result is a framework that is technically robust, semantically consistent, and capable of operating in various systems and jurisdictions.
Realizing this vision requires sustained collaborative action from all stakeholders. Key future steps
include:
• Finalizing Standards: Accelerate the development and alignment of UNTP and AAS submodel
templates through collaboration between UN/CEFACT, IDTA, ISO, and other standards bodies.
• Developing Open-Source Tools: Create accessible tools for converting, validating, and
deploying UNTP-AAS DPPs to lower adoption barriers for SMEs.
• Promoting Pilot Projects: Launch cross-domain pilots based on initiatives like ECO-TCO to
validate the architecture and demonstrate tangible benefits.
• Strengthening Governance: Develop robust data governance practices to address privacy, IP
protection, and fine-grained access control, integrating legal frameworks such as the EU Data
Act and the AI Act [
The achievement of a globally interoperable DPP ecosystem is a strategic imperative to advance sustainability and innovation. The synergistic approach presented here provides a clear and actionable path toward this goal.
Declaration on Generative AI: The author(s) have not employed any Generative AI tools.