Building Digital Product Passports: EPCIS 2.0 Meets Knowledge Graphs

The EU Digital Product Passport (DPP) regulation mandates robust product traceability to support sustainability reporting and regulatory compliance. However, the inherent complexity of global supply chains, marked by frequent changes in product ownership, transformations, and aggregations, poses significant challenges. While GS1 EPCIS 2.0 offers a standardized framework for capturing and sharing product visibility data, querying traceability information becomes inefficient and cumbersome, particularly in scenarios involving multilevel transformations and aggregations. This paper proposes an integrated architecture that combines EPCIS 2.0 with a knowledge graph to address these challenges. By linking traceability events using GS1 keys, the system constructs a graph-based model that enables the retrieval of complete product histories with a single query, regardless of the complexity of the supply chain. The platform ingests visibility events in real time from distributed sources, enhancing scalability, interoperability, and traceability accuracy.

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Publication Details

Published
2025-04-22
DOI
https://doi.org/10.1109/rfid64926.2025.11015538
Citations
2
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
4.96

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article

Building Digital Product Passports: EPCIS 2.0 Meets Knowledge Graphs

Yalew Tolcha, Daeyoung Kim, Gunwoo Park
2 citations
Semantic Web and Ontologies
4.96
article

Building Digital Product Passports: EPCIS 2.0 Meets Knowledge Graphs

Yalew Tolcha, Daeyoung Kim, Gunwoo Park
article en
2 citations

Abstract

The EU Digital Product Passport (DPP) regulation mandates robust product traceability to support sustainability reporting and regulatory compliance. However, the inherent complexity of global supply chains, marked by frequent changes in product ownership, transformations, and aggregations, poses significant challenges. While GS1 EPCIS 2.0 offers a standardized framework for capturing and sharing product visibility data, querying traceability information becomes inefficient and cumbersome, particularly in scenarios involving multilevel transformations and aggregations. This paper proposes an integrated architecture that combines EPCIS 2.0 with a knowledge graph to address these challenges. By linking traceability events using GS1 keys, the system constructs a graph-based model that enables the retrieval of complete product histories with a single query, regardless of the complexity of the supply chain. The platform ingests visibility events in real time from distributed sources, enhancing scalability, interoperability, and traceability accuracy.

Korea Advanced Institute of Science and Technology (KR), Innovative Design Labs (United States) (US)
National Research Foundation of Korea, Institute of Information and Communication Technologies, Bulgarian Academy of Sciences
Decent work and economic growth
Openalex Percentile: Top 5%
Semantic Web and Ontologies
4.96
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