Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-30874
Publication type: Working paper – expertise – study
Title: Digital public infrastructure for environmental sustainability
Authors: Chen, Yaxuan
Vergara, Ana Fernandez
Hamilton, Angus
Stockinger, Kurt
et. al: No
DOI: 10.21256/zhaw-30874
Extent: vii, 60
Issue Date: May-2024
Publisher / Ed. Institution: United Nations Environment Programme
ISBN: 978-92-807-4157-5
Language: English
Subjects: Sustainability; Green energy; Technology infrastructure; Data science; Database; Machine learning; Artificial intelligence
Subject (DDC): 006: Special computer methods
338.927: Environmental economics and sustainable development
Abstract: The report examines common information challenges stakeholders face when making decisions related to environmental sustainability and explores the role that Digital Public Infrastructure (DPI) can play as a key part of the solution. To tackle the interconnected triple environmental planetary crises, it is critical to have accessible, timely, credible, and insightful information that can support environmental sustainability decision-making. Developing interconnected data exchange mechanisms has become a necessity, but sole reliance on private solutions will likely fail to comprehensively address the challenges and may result in further data fragmentation. A blend of private and public solutions is essential. However, there is currently a notable gap in DPI to facilitate the flow of environmental sustainability information to different stakeholders. This report analyses three cases related to the agri-food sector and identifies six categories of technology innovations (TIs) that could help tackle information challenges: • Open data discovery for environmental sustainability • Privacy enhancing technologies to enable flow of environmental sustainability information • Data markets for environmental sustainability-related data • Computational law and data integration of green and circular economy policy measures • Using Large Language Models to ‘speak’ with green and circular economy policy • Tools and techniques for human-centred artificial intelligence in environmental sustainability decision-making.
URI: https://wedocs.unep.org/20.500.11822/45181
https://digitalcollection.zhaw.ch/handle/11475/30874
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Computer Science (InIT)
Published as part of the ZHAW project: DECIDE - Digital Enabling of Circularity, Innovation, Development and Environment (UNEP)
Appears in collections:Publikationen School of Engineering

Files in This Item:
File Description SizeFormat 
2024_Chen-etal_Digital-Public-Infrastructure-for-Environmental-Sutainability.pdf7.04 MBAdobe PDFThumbnail
View/Open
Show full item record
Chen, Y., Vergara, A. F., Hamilton, A., & Stockinger, K. (2024). Digital public infrastructure for environmental sustainability. United Nations Environment Programme. https://doi.org/10.21256/zhaw-30874
Chen, Y. et al. (2024) Digital public infrastructure for environmental sustainability. United Nations Environment Programme. Available at: https://doi.org/10.21256/zhaw-30874.
Y. Chen, A. F. Vergara, A. Hamilton, and K. Stockinger, “Digital public infrastructure for environmental sustainability,” United Nations Environment Programme, May 2024. doi: 10.21256/zhaw-30874.
CHEN, Yaxuan, Ana Fernandez VERGARA, Angus HAMILTON und Kurt STOCKINGER, 2024. Digital public infrastructure for environmental sustainability [online]. United Nations Environment Programme. Verfügbar unter: https://wedocs.unep.org/20.500.11822/45181
Chen, Yaxuan, Ana Fernandez Vergara, Angus Hamilton, and Kurt Stockinger. 2024. “Digital Public Infrastructure for Environmental Sustainability.” United Nations Environment Programme. https://doi.org/10.21256/zhaw-30874.
Chen, Yaxuan, et al. Digital Public Infrastructure for Environmental Sustainability. United Nations Environment Programme, May 2024, https://doi.org/10.21256/zhaw-30874.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.