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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
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...
Keywords
Bayesian networks, Data-driven, Interlinkages, SDG 6, Sustainable Development Goals
Group of research
EScGD - Engineering Sciences and Global Development

Participants