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Data-driven Bayesian network modelling to explore the relationships between SDG 6 and the 2030 Agenda

Author
Requejo-Castro, D.; Giné , R.; Pérez-Foguet, A.
Type of activity
Journal article
Journal
Science of the total environment
Date of publication
2020-03
Volume
710
First page
136014:1
Last page
136014:19
DOI
10.1016/j.scitotenv.2019.136014
Repository
http://hdl.handle.net/2117/182954 Open in new window
URL
https://www.sciencedirect.com/science/article/pii/S0048969719360103 Open in new window
Abstract
The Sustainable Development Goals (SDGs) are presented as integrated and indivisible. Therefore, for monitoring purposes, conventional indicator-based frameworks need to be combined with approaches that capture and describe the links and interdependencies between the Goals and their targets. In this study, we propose a data-driven Bayesian network (BN) approach to identify and interpret SDGs interlinkages. We focus our analysis on the interlinkages of SDG 6, related to water and sanitation, acro...
Citation
Requejo-Castro, D.; Giné , R.; Pérez-Foguet, A. Data-driven Bayesian network modelling to explore the relationships between SDG 6 and the 2030 Agenda. "Science of the total environment", Març 2020, vol. 710, p. 136014:1-136014:19.
Keywords
Bayesian networks, Data-driven, Interlinkages, SDG 6, Sustainable Development Goals
Group of research
EScGD - Engineering Sciences and Global Development

Participants