Data-enhanced revealing of trends in Geoscience
Author:
Zhao Yu1, Wang Meng23, Ding Jiaxin4, Qi Jiexing4, Wu Lyuwen4, Zhang Sibo4, Fu Luoyi4, Wang Xinbing4, Cheng Li5
Affiliation:
1. School of Earth Sciences and Resources, China University of Geosciences , Beijing , , China 2. Key Laboratory of Ecological Security and Sustainable Development of Arid Areas, State Key Laboratory of Desert and Oasis Ecology, Chinese Academy of Sciences , Urumqi, Xinjiang , , China 3. Xinjiang Key Laboratory of Mineral Resources and Digital Geology , Urumqi , , China 4. Shanghai Jiao Tong University , Shanghai , , China 5. Journal Center, China University of Geosciences , Beijing , , China
Abstract
Abstract
Purpose
This article presents an in-depth analysis of global research trends in Geosciences from 2014 to 2023. By integrating bibliometric analysis with expert insights from the Deeptime Digital Earth (DDE) initiative, this article identifies key emerging themes shaping the landscape of Earth Sciences①.
Design/methodology/approach
The identification process involved a meticulous analysis of over 400,000 papers from 466 Geosciences journals and approximately 5,800 papers from 93 interdisciplinary journals sourced from the Web of Science and Dimensions database. To map relationships between articles, citation networks were constructed, and spectral clustering algorithms were then employed to identify groups of related research, resulting in 407 clusters. Relevant research terms were extracted using the Log-Likelihood Ratio (LLR) algorithm, followed by statistical analyses on the volume of papers, average publication year, and average citation count within each cluster. Additionally, expert knowledge from DDE Scientific Committee was utilized to select top 30 trends based on their representation, relevance, and impact within Geosciences, and finalize naming of these top trends with consideration of the content and implications of the associated research. This comprehensive approach in systematically delineating and characterizing the trends in a way which is understandable to geoscientists.
Findings
Thirty significant trends were identified in the field of Geosciences, spanning five domains: deep space, deep time, deep Earth, habitable Earth, and big data. These topics reflect the latest trends and advancements in Geosciences and have the potential to address real-world problems that are closely related to society, science, and technology.
Research limitations
The analyzed data of this study only contain those were included in the Web of Science.
Practical implications
This study will strongly support the organizations and individual scientists to understand the modern frontier of earth science, especially on solid earth. The organizations such as the surveys or natural science fund could map out areas for future exploration and analyze the hot topics reference to this study.
Originality/value
This paper integrates bibliometric analysis with expert insights to highlight the most significant trends on earth science and reach the individual scientist and public by global voting.
Publisher
Walter de Gruyter GmbH
Reference24 articles.
1. Ai, X., Ma, M., Wang, X., & Kuang, H. (2022). A novel bibliometric and visual analysis of global geoscience research using landscape indices. Frontiers of Earth Science, 16(2), 340–351. https://doi.org/10.1007/s11707-021-0875-z 2. Aksnes, D. W., & Sivertsen, G. (2023). Global trends in international research collaboration, 1980-2021. Journal of Data and Information Science, 8(2), 26–42. https://doi.org/10.2478/jdis-2023-0015 3. Allen, L., Jones, C., Dolby, K., Lynn, D., & Walport, M. (2009). Looking for Landmarks: The Role of Expert Review and Bibliometric Analysis in Evaluating Scientific Publication Outputs. PLOS ONE, 4(6), e5910. https://doi.org/10.1371/journal.pone.0005910 4. Bergen, K. J., Johnson, P. A., de Hoop, M. V., & Beroza, G. C. (2019). Machine learning for data-driven discovery in solid Earth geoscience. Science, 363(6433), eaau0323. https://doi.org/doi:10.1126/science.aau0323 5. CenCO2PIP Consortium (2023). Toward a Cenozoic history of atmospheric CO2. Science, 382(6675), eadi5177. https://doi.org/doi:10.1126/science.adi5177
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