GeoBM: A Python-based tool for integrated visualization of global bibliometric data

The rapid proliferation of scientometric and bibliometric analyses has emphasized the need for robust, scalable methods to visualize complex, large-scale research data. Conventional geospatial visualization techniques—most notably choropleth maps—often introduce significant distortions due to their...

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Main Authors: Chun Chong Fu, Jorge Fleta-Asín, Fernando Muñoz, Carlos Sáenz-Royo, Loo Keat Wei
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:MethodsX
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Online Access:http://www.sciencedirect.com/science/article/pii/S2215016125003425
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author Chun Chong Fu
Jorge Fleta-Asín
Fernando Muñoz
Carlos Sáenz-Royo
Loo Keat Wei
author_facet Chun Chong Fu
Jorge Fleta-Asín
Fernando Muñoz
Carlos Sáenz-Royo
Loo Keat Wei
author_sort Chun Chong Fu
collection DOAJ
description The rapid proliferation of scientometric and bibliometric analyses has emphasized the need for robust, scalable methods to visualize complex, large-scale research data. Conventional geospatial visualization techniques—most notably choropleth maps—often introduce significant distortions due to their inability to adequately account for spatial heterogeneity and overdispersion in bibliometric distributions. To address these methodological shortcomings, we propose GeoBM (Geographic Bibliometric Mapping), a computational framework that enables enhanced geovisualization of global scientific output and collaboration patterns. GeoBM integrates normalized country-level publication volumes with bilateral collaboration frequencies to produce high-resolution, interpretable geographic maps that reflect both research intensity and international connectivity. Implemented in Python, the framework leverages modular, algorithmically optimized routines for real-time data processing and visualization, incorporating statistical controls to mitigate overdispersion and enhance visual fidelity. The system supports extensive customization and is deployed via open-source platforms such as Google Colab and GitHub, facilitating broad accessibility and reproducibility. By providing a dual-focus representation of publication density and collaborative strength, GeoBM offers a powerful tool for the spatial analysis of global research networks, contributing to more nuanced evaluations in science policy, research management, and innovation studies.
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spelling doaj-art-264d441d72664f8f8cdae73849d1d16d2025-08-20T03:08:18ZengElsevierMethodsX2215-01612025-12-011510349710.1016/j.mex.2025.103497GeoBM: A Python-based tool for integrated visualization of global bibliometric dataChun Chong Fu0Jorge Fleta-Asín1Fernando Muñoz2Carlos Sáenz-Royo3Loo Keat Wei4Department of Biological Science, Faculty of Science, Universiti Tunku Abdul Rahman, Bandar Barat, 31900 Kampar, Perak, MalaysiaIEDIS. Departamento de Dirección y Organización de Empresas, Facultad de Economía y Empresa, Universidad de Zaragoza, Gran Vía, 2, 50005 Zaragoza, Spain; Expert from the SIP Foundation, Zaragoza, SpainExpert from the SIP Foundation, Zaragoza, Spain; IEDIS. Departamento de Contabilidad y Finanzas, Facultad de Economía y Empresa, Universidad de Zaragoza, Gran Vía, 2, 50005 Zaragoza, SpainExpert from the SIP Foundation, Zaragoza, Spain; Departamento de Dirección y Organización de Empresas, Facultad de Ciencias Sociales y del Trabajo, Universidad de Zaragoza, Violante de Hungría, 23, 50009 Zaragoza, SpainDepartment of Biological Science, Faculty of Science, Universiti Tunku Abdul Rahman, Bandar Barat, 31900 Kampar, Perak, Malaysia; Centre for Biomedical and Nutrition Research (CBNR), Universiti Tunku Abdul Rahman, Bandar Barat, 31900 Kampar, Perak, Malaysia; Corresponding author.The rapid proliferation of scientometric and bibliometric analyses has emphasized the need for robust, scalable methods to visualize complex, large-scale research data. Conventional geospatial visualization techniques—most notably choropleth maps—often introduce significant distortions due to their inability to adequately account for spatial heterogeneity and overdispersion in bibliometric distributions. To address these methodological shortcomings, we propose GeoBM (Geographic Bibliometric Mapping), a computational framework that enables enhanced geovisualization of global scientific output and collaboration patterns. GeoBM integrates normalized country-level publication volumes with bilateral collaboration frequencies to produce high-resolution, interpretable geographic maps that reflect both research intensity and international connectivity. Implemented in Python, the framework leverages modular, algorithmically optimized routines for real-time data processing and visualization, incorporating statistical controls to mitigate overdispersion and enhance visual fidelity. The system supports extensive customization and is deployed via open-source platforms such as Google Colab and GitHub, facilitating broad accessibility and reproducibility. By providing a dual-focus representation of publication density and collaborative strength, GeoBM offers a powerful tool for the spatial analysis of global research networks, contributing to more nuanced evaluations in science policy, research management, and innovation studies.http://www.sciencedirect.com/science/article/pii/S2215016125003425Bibliometric analysisBibliometrixVOSviewerCitespacePython algorithmCountry collaboration map
spellingShingle Chun Chong Fu
Jorge Fleta-Asín
Fernando Muñoz
Carlos Sáenz-Royo
Loo Keat Wei
GeoBM: A Python-based tool for integrated visualization of global bibliometric data
MethodsX
Bibliometric analysis
Bibliometrix
VOSviewer
Citespace
Python algorithm
Country collaboration map
title GeoBM: A Python-based tool for integrated visualization of global bibliometric data
title_full GeoBM: A Python-based tool for integrated visualization of global bibliometric data
title_fullStr GeoBM: A Python-based tool for integrated visualization of global bibliometric data
title_full_unstemmed GeoBM: A Python-based tool for integrated visualization of global bibliometric data
title_short GeoBM: A Python-based tool for integrated visualization of global bibliometric data
title_sort geobm a python based tool for integrated visualization of global bibliometric data
topic Bibliometric analysis
Bibliometrix
VOSviewer
Citespace
Python algorithm
Country collaboration map
url http://www.sciencedirect.com/science/article/pii/S2215016125003425
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