Data Spaces for Sustainable Product Development –A Structured Analysis of Technical and Semantic Infrastructures
持続可能な製品開発のためのデータスペース – 技術的・意味的インフラの構造分析 (AI 翻訳)
Niklas Quernheim, Hannah Scheerer, Annika Hesse, Sven Winter, Hendrik van der Valk, Boris Otto, Benjamin Schleich
🤖 gxceed AI 要約
日本語
持続可能な製品開発には材料由来やエネルギー消費、排出など環境情報の早期・体系的な利用が不可欠であり、相互運用可能なデータ共有基盤が求められる。本論文はDigital Product Passport、Catena-X、PACT、Asset Administration Shellなどのデータスペース構想を体系的に比較し、持続可能性評価への貢献可能性を分析。既存アーキテクチャは相互運用性・共有に焦点を当てる一方、LCA特有の文脈情報の体系的なサポートが不足していることを指摘する。
English
Sustainable product development requires early access to environmental data such as material origin, energy use, and emissions, demanding interoperable cross-organizational data sharing. This paper systematically compares data space initiatives—Digital Product Passport, Catena-X, PACT, and Asset Administration Shell—and finds that while they prioritize interoperability, they lack systematic support for LCA-specific context information. It provides a structured foundation for data-driven life-cycle assessment and digital engineering integration.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本ではSSBJ開示やサプライチェーン排出量把握が課題であり、データ連携基盤の設計は重要。本論文は欧州のデータスペース動向を整理しており、日本企業がグローバルな開示インフラ（Catena-X等）対応を検討する際の参考になる。
In the global GX context
As ISSB, CSRD, and SEC climate rules push for transparent value-chain emissions, federated data spaces like Catena-X and the Digital Product Passport are emerging as key infrastructure. This paper provides a structured comparison of these initiatives, highlighting gaps in LCA-specific semantic support that matter for any disclosure-standard implementation.
👥 読者別の含意
🔬研究者:Provides a structured map of data-space initiatives and identifies research gaps in LCA-specific semantic support for sustainability data exchange.
🏢実務担当者:Offers a landscape of data space architectures (DPP, Catena-X, PACT, AAS) that companies can use to plan data-sharing capabilities for Scope 3/carbon transparency.
🏛政策担当者:Highlights the need for harmonized semantic models in data infrastructure to support regulation-driven sustainability disclosures.
📄 Abstract（原文）
Sustainable product development relies on the early and systematic availability of environmental information, such as material origin, energy consumption, and emissions. This results in new requirements for data integration and processing to provide valuable sustainability metrics. In recent years, data space initiatives, standards, and regulations have emerged to enable interoperable, and cross-organizational exchange of such information. Examples include the Digital Product Passport, Catena-X, the Partnership for Carbon Transparency, and the Asset Administration Shell. While these infrastructures vary in terms of architecture, semantic modeling, and maturity, there is a lack of structured analysis highlighting their potential relevance for sustainability-oriented use cases. The purpose of this paper is to investigate the research proposition that federated data space architectures support acquisition, exchange, sharing, and processing and use of data required for sustainable product development. The methodology encompasses a structured literature review of use cases and a systematic comparison of existing data space concepts. The analysis evaluates supported data types, semantic models, interoperability features, and the potential contribution of these systems to support sustainability assessments, especially in early design stages. The main findings are (1) there are existing approaches for data spaces in which sustainability typically is a priority. (2) The utilization of data spaces for sustainable product development lacks published use cases in science. (3) Existing architectures focus on the interoperability and sharing of data but lack systematic support of LCA specific context information. Beside these findings, the paper provides a structured overview of data space approaches relevant for sustainable product development. This lays a foundation for future research on data-driven life cycle assessment and the integration of environmental information into digital engineering processes.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.procir.2026.05.393first seen 2026-08-02 19:23:36
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