Beyond the Repository: Building an AI-Powered Knowledge Nexus for SDGs Research

M. Hema Sundara Rao () and V. Dhana Raju ()
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M. Hema Sundara Rao: Andhra University, Research Scholar (UGC-JRF), Department of Library and Information Science
V. Dhana Raju: Andhra University, Department of Library and Information Science

A chapter in Proceedings of the International Conference on Marching Beyond the Libraries: Talent, Technology, and Transformation (ICMBL 2025), 2026, pp 99-103 from Springer

Abstract: Abstract The intertwined global challenges of climate change, energy access, and public health—collectively represented in the Climate-Energy-Health Nexus (SDGs 3, 7, 13)—demand research that transcends disciplinary isolation. Yet, the scholarly landscape remains highly fragmented. This paper presents a scientometric analysis of 45,219 publications (2000–2024) to chart this nexus and reveal structural discontinuities. The analysis reveals three major, discipline-bound clusters: Climate Impacts & Health Adaptation, Energy Transitions & Air Quality, and Household Energy & Health Equity, with only 47 “bridge” papers connecting them, indicating weak cross-domain integration. To address this fragmentation, the study proposes a conceptual framework for an AI-powered Knowledge Nexus that leverages Natural Language Processing (NLP) for semantic enrichment and a Dynamic Knowledge Graph supported by Graph Neural Networks (GNNs) to map, evolve, and predict inter-research linkages. A manual proof-of-concept using 5,183 papers uncovered 23 additional relevant studies linking clean energy to mental health pathways—a 34% increase in discovery beyond conventional keyword searches. The findings argue that transitioning from static repositories to intelligent, AI-facilitated knowledge environments is critical to accelerating the integrative science needed to fulfil the 2030 Agenda.

Keywords: AI for SDGs; Knowledge Nexus; Scientometrics; Climate-Energy-Health Nexus; Natural Language Processing; SDG 3; SDG 7; SDG 13 (search for similar items in EconPapers)
Date: 2026
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DOI: 10.2991/978-94-6239-614-2_12

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