Can LCA be FAIR? Assessing the status quo and opportunities for FAIR data sharing
LCAはFAIRになり得るか？現状評価とFAIRデータ共有の機会 (AI 翻訳)
Agneta Ghose
🤖 gxceed AI 要約
日本語
本研究は、ライフサイクルアセスメント（LCA）データの共有現状をFAIR原則（見つけやすさ、アクセス可能性、相互運用性、再利用性）の観点から評価した。公開資金による研究データの共有では、FAIR原則の実装がほとんど進んでおらず、LCA特有のデータ共有ガイドラインが欠如していることを指摘。LCAデータのFAIR化のためのワークフローを提案し、コミュニティのスキル・技術開発、戦略的資金提供、ベストプラクティスの認知を推奨している。
English
This study assesses the status quo of LCA data sharing against the FAIR principles. It finds that FAIR implementation is rare in practice and that LCA-specific guidance is missing, while generic repositories are the main enabler. A workflow for FAIRification of LCA data is proposed, along with recommendations on skills, funding, and community recognition.
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
LCAデータのFAIR化は、日本のカーボンフットプリント制度や製品環境情報の開示要請が進む中で、データの信頼性と相互運用性を高める上で重要。ただし本稿は研究データ共有が中心で、直接の制度対応ではない。
In the global GX context
FAIR data sharing is foundational for credible LCA-based environmental disclosures increasingly required by frameworks like CSRD and the EU's Product Environmental Footprint. This paper highlights the infrastructure gaps that should be addressed to support transparent, interoperable LCA data across supply chains.
👥 読者別の含意
🔬研究者:Identifies actionable gaps and a workflow for FAIR-compliant LCA data sharing.
🏢実務担当者:Highlights the need for standardized LCA data formats to support product-level environmental claims and reporting.
📄 Abstract（原文）
Abstract Aim The purpose of this study is to assess the status quo of data sharing in LCA in relation to the FAIR (findability, accessibility, interoperability, and reuse) data principles. Methods This study investigates how is LCA data from publicly funded research currently shared. Firstly, the focus is on life cycle inventory data shared in journal articles. Given that FAIR data sharing is not only the responsibility of the LCA practitioner, this study further investigates guidelines (e.g., data sharing standards and data management plans) and infrastructure (repositories, data formats, and nomenclature) to identify the tools and services available to LCA community which are essential to enable FAIR data sharing. Results The study identifies that although there is growing awareness to improve data sharing practices, implementation of FAIR guidelines for data sharing is seldom seen in practice. LCA studies that adhere to FAIR principles are primarily due to use of generic data repositories which provide tools to support data sharing. However, there is no guidance on how LCA specific data should be shared to ensure its findability, accessibility, interoperability, and reusability. This study suggests a workflow to enable FAIRification of LCA data. In addition, the study recommends further efforts within the LCA community on skill and technology development, strategic funding, and recognition of the best practices in relation to data sharing. Conclusion In conclusion, this study highlights the necessity of data sharing incentives, guidelines, and platforms/repositories specific for the LCA community.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1007/s11367-024-02280-3first seen 2026-08-02 19:00:32
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