VISUALIZATION OF ENERGY WITH ZERO CARBON FOOTPRINT USING VOSVIEWER
VOSviewerを使用したゼロカーボンフットプリントエネルギーの可視化 (AI 翻訳)
GELMANOVA ZOYA SALIKHOVNA, FAYEZ WAZANI ABDUL WALID
🤖 gxceed AI 要約
日本語
本研究は、VOSviewerを用いた書誌計量分析により、2020～2025年の19,450件の論文からゼロカーボンエネルギー研究の構造と発展を可視化した。キーワード共起ネットワークから主要テーマ（再生可能エネルギー、エネルギー転換、脱炭素化等）やAI・機械学習の役割を明らかにし、今後の研究の方向性を示している。
English
This study uses VOSviewer to perform a bibliometric analysis of 19,450 publications from 2020-2025, visualizing the structure of zero-carbon energy research. It identifies key themes like renewable energy, energy transition, and AI integration, offering a systematic mapping for researchers and policymakers.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では、ゼロカーボンエネルギー研究の全体像を把握する参考となるが、国内政策やSSBJ等の開示基準との直接的な連動は薄い。日本の研究ポジショニング把握に活用できる。
In the global GX context
This bibliometric mapping provides a global snapshot of zero-carbon energy research trends, valuable for identifying emerging themes and gaps. It supports researchers and policymakers in understanding the interdisciplinary landscape, though it lacks country-specific insights.
👥 読者別の含意
🔬研究者:Provides a comprehensive overview of research clusters and emerging trends in zero-carbon energy, useful for identifying collaboration opportunities and under-explored areas.
🏢実務担当者:Helps corporate sustainability teams understand the broader research landscape and technological trends in decarbonization, though direct applicability is limited.
🏛政策担当者:Offers a systematic mapping of research priorities and knowledge gaps, informing funding and policy directions in the energy transition.
📄 Abstract（原文）
This study examines the structure and development of zero-carbon energy research through bibliometric analysis and scientific visualization. A dataset of 19,450 publications from the Web of Science (2020–2025) was analyzed using VOSviewer to construct keyword co-occurrence networks, thematic clusters, and research linkages. The results identify key research areas, including renewable energy, energy transition, energy efficiency, decarbonization, sustainability, and carbon footprint reduction. The findings reveal a highly interdisciplinary field, combining insights from engineering, environmental science, economics, and data analytics. Network visualization highlights the relationships among major themes and uncovers emerging trends, particularly the growing role of digital technologies such as artificial intelligence and machine learning in optimizing energy systems. The study also identifies knowledge gaps and evolving research directions that are critical for future investigation. This research provides a clear and systematic mapping of the zero-carbon energy domain, offering valuable insights for researchers, policymakers, and industry stakeholders working to accelerate the transition toward sustainable and carbon-neutral energy systems.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.19712399first seen 2026-05-15 17:14:45
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。