Estimating networks of sustainable development goals

Acosta L, Lee S, Nzimenyera I, Sebestyén V, Abonyi J. Network science and explainable AI-based life cycle management of sustainability models

Model-based assessment of the potential impacts of variables on the Sustainable Development Goals (SDGs) can bring great additional information about possible policy intervention points. In the context of sustainability planning, machine learning techniques can provide data-driven solutions throughout the modeling life cycle. In a changing environment, existing models must be continuously reviewed and developed for effective decision support. Thus, we propose to use the Machine Learning Operations (MLOps) life cycle framework. A novel approach for model identification and development is introduced, which involves utilizing the Shapley value to determine the individual direct and indirect contributions of each variable towards the output, as well as network analysis to identify key drivers and support the identification and validation of possible policy intervention points. The applicability of the methods is demonstrated through a case study of the Hungarian water model developed by the Global Green Growth Institute. Based on the model exploration of the case of water efficiency and water stress (in the examined period for the SDG 6.4.1 & 6.4.2) SDG indicators, water reuse and water circularity offer a more effective intervention option than pricing and the use of internal or external renewable water resources.

Bleak prospects and targeted actions for achieving the Sustainable Development Goals

At the mid-point to 2030, progress towards achieving the Sustainable Development Goals (SDGs) varies significantly across countries. While the classification of countries can lay the foundation for improving policy efficiency and promoting joint action, bottom-up, SDG data-driven country classifications have largely remained unexplored. Here, we classified 166 countries based on their performances in the 17 SDGs and further used the classification to analyze SDG interactions and compare development aid distributions. The countries were classified into five groups, ranging from "lowest development with good environment" to "high development needing climate action". None of them scored highly in all SDGs, and due to trade-offs related to environment and climate SDGs, none of them can achieve all SDGs eventually. To maximize the potential for achieving the SDGs, all countries need to undergo a sustainable transformation, and prioritizing certain SDGs, such as SDG 9 (industry, innovation and infrastructure), can help countries with lower sustainable development levels achieve more with less. Furthermore, global development aid should be better aligned with country needs, particularly in areas of education, energy, environment, and water supply and sanitation. By better characterizing different countries, this study reveals the bleak prospects of achieving all SDGs and provides valuable insights into more targeted actions for national sustainable development and global collaboration.

Sustainable development goals applied to digital pathology and artificial intelligence applications in low- to middle-income countries

Digital Pathology (DP) and Artificial Intelligence (AI) can be useful in low- and middle-income countries; however, many challenges exist. The United Nations developed sustainable development goals that aim to overcome some of these challenges. The sustainable development goals have not been applied to DP/AI applications in low- to middle income countries. We established a framework to align the 17 sustainable development goals with a 27-indicator list for low- and middle-income countries (World Bank/WHO) and a list of 21 essential elements for DP/AI. After categorization into three domains (human factors, IT/electronics, and materials + reagents), we permutated these layers into 153 concatenated statements for prioritization on a four-tiered scale. The two authors tested the subjective ranking framework and endpoints included ranked sum scores and visualization across the three layers. The authors assigned 364 points with 1.1-1.3 points per statement. We noted the prioritization of human factors (43%) at the indicator layer whereas IT/electronic (36%) and human factors (35%) scored highest at the essential elements layer. The authors considered goal 9 (industry, innovation, and infrastructure; average points 2.33; sum 42), goal 4 (quality education; 2.17; 39), and goal 8 (decent work and economic growth; 2.11; 38) most relevant; intra-/inter-rater variability assessment after a 3-month-washout period confirmed these findings. The established framework allows individual stakeholders to capture the relative importance of sustainable development goals for overcoming limitations to a specific problem. The framework can be used to raise awareness and help identify synergies between large-scale global objectives and solutions in resource-limited settings.

The role of complexity for digital twins of cities

We argue that theories and methods drawn from complexity science are urgently needed to guide the development and use of digital twins for cities. The theoretical framework from complexity science takes into account both the short-term and the long-term dynamics of cities and their interactions. This is the foundation for a new approach that treats cities not as large machines or logistic systems but as mutually interwoven self-organizing phenomena, which evolve, to an extent, like living systems.

Toward evaluating the effect of technology choices on linkages between sustainable development goals

Linkages between the Sustainable Development Goals (SDGs) have sparked research interest because a better understanding of SDG co-benefits may enable faster progress on multiple sustainability fronts. However, SDG linkages are typically analyzed without considering the technologies used to implement a primary SDG, which may have secondary effects on other SDGs. Here, we outline an approach to study this problem by connecting the industries and services required to produce a technology to the United Nations SDG indicator framework, using SDG7 and four energy technologies as an illustrative case. We find that all technologies in our set involve potential co-benefits with SDGs 1, 8-10, 12-13, and 17, and trade-offs with SDGs 6, 8-9, 11-12, and 14-15. Deployment services primarily induce co-benefits; manufacturing has mixed impacts. Our work sheds light on the technology characteristics (e.g., scale, high- or low-tech) that influence linkages while also pointing to SDG-relevant characteristics not captured by UN indicators.

Communication, Social Networks and Sustainable Development Goals: A Reflection From the Perspective of Social Marketing and Happiness Management in the General Elections in Spain

The challenges imposed by the global development agenda imply reflecting on the role and contribution of political parties to development processes in the online environment. Social networks have been characterised as a part of the strategies of political campaigns, as it allows political leaders to establish bidirectional communication with citizens. In this context, the present study aims to empirically explore the leading Spanish political formations' publications from a social marketing perspective. In this way, it will be possible to verify how issues related to the Sustainable Development Goals (SDGs) are addressed. On the one hand, this requires elaborating the communication profiles of the main political parties presented to the Spanish General Elections from 2015 to 2019. On the other hand, to analyse whether social themes better discriminate or distinguish one political party from another. For this purpose, a methodology based on text mining, content analysis from a quantitative and qualitative approach, and simple correspondence analysis has been used. Finally, it should be noted that the results of this research show that there are differences between political parties according to the social issues published, with a divergence between the social issues that provoke a better reaction from the public and those most published on Facebook.

A Scoping Review of Ontologies Relevant to Design Strategies in Response to the UN Sustainable Development Goals (SDGs)

Since the initiation of the 2030 Agenda for Sustainable Development in 2015, academia and industry have been taking action to seek how to address the Sustainable Development Goals (SDGs) via research, practice, and community engagement. Due to the UN SDGs comprising comprehensive domain-centric ontologies for reaching a consensus on their achievement, so far there has been a literature gap on how and what product design strategies can help achieve which of the SDGs. Inspired by the implication of creating a better world with design, this study conducted a scoping review to synthesize existing design strategies toward the implementation of the SDGs. More than 110 design strategies/methods were collected and synthesized as evidence to map onto the ontological domains of the SDGs. The results indicate that Goals 8, 9, 11, and 12 can be correspondingly addressed by the current body of design strategies, whereas a gap exists in the design strategies to address Goals 15, 16, and 17. Most of the corresponding strategies can be workable to Goals 3, 4, 6, and 7 to a certain extent and, in a broad sense, are in line with the contextual implications of Goals 1, 2, 5, 10, 13, and 14. This study provides a useful starting point for researchers to explore how design has been contributing to the sustainability goals. It also contributes to existing knowledge of the design discipline by providing methodological guidance for researchers and practitioners to conduct further research and practice on the UN SDGs.

Policy priority inference: A computational framework to analyze the allocation of resources for the sustainable development goals

We build a computational framework to support the planning of development and the evaluation of budgetary strategies toward the 2030 Agenda. The methodology takes into account some of the complexities of the political economy underpinning the policymaking process: the multidimensionality of development, the interlinkages between these dimensions, and the inefficiencies of policy interventions, as well as institutional factors that promote or discourage these inefficiencies. The framework is scalable and usable even with limited publicly available information: development-indicator data. However, it can be further refined as more data becomes available, for example, on public expenditure. We demonstrate its usage through an application for the Mexican federal government. For this, we infer historical policy priorities, that is, the non-observable allocations of transformative resources that generated past changes in development indicators. We also show how to use the tool to assess the feasibility of development goals, to measure policy coherence, and to identify accelerators. Overall, the framework and its computational tools allow policymakers and other stakeholders to embrace a complexity (and a quantitative) view to tackle the challenges of the Sustainable Development Goals.

Multidimensional Assessment of the Social Development of EU Countries in the Context of Implementing the Concept of Sustainable Development

Measuring and monitoring the implementation of the concept of sustainable development is an important aspect of the assessment of the functioning of EU countries. One of the pivots of sustainable development is social order, although the literature analysis indicated that multidimensional empirical research in this area is scarce. The main goal of this article was to present the diversity of indicators characterizing social development in EU Member States in the context of progress made by each of them in implementing the concept of sustainable development between 2014 and 2018. The purpose of this article was also to compare Poland with the other EU countries in the years 2014 and 2018. The research procedure consisted of two stages. The first stage was to analyse and assess the regional differentiation of the values of variables explaining social development in the EU in the context of implementing the concept of sustainable development. The second stage envisaged a multidimensional assessment of the diversity of the thematic areas identified in the first stage, as well as a characterization of social development in the EU in the context of implementing the concept of sustainable development. Based on the obtained results, a conclusion could be drawn that many countries are witnessing positive trends which bring them closer to the successful implementation of the sustainable development paradigm—one of the principal priorities of the Europe 2020 strategy, a long-term socio-economic program of the EU. The multidimensional analysis also showed that the level of social development in the context of sustainable development differs across the EU. Particularly notable differences among EU countries could be observed for the variables denoting labour market and health, with demography being the least diversified of all areas. In Poland, the indicators regarding poverty and social exclusion improved significantly as a result of the implementation of numerous social programs. In addition to that, a positive change in education indicators was also reported in Poland. This favourable trend indicates that some of the goals set out in the Europe 2020 strategy have already been met by Poland while others are becoming increasingly attainable.