Innovative Bibliometric Methodology: A New Big Data-Based Framework for Scientific Research

Eduardo Marlés-Sáenz, Eduardo Gómez-Luna, Josep M. Guerrero and Juan C. Vasquez ()
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Eduardo Marlés-Sáenz: High Voltage Research Group—GRALTA, School of Electrical and Electronic Engineering, Universidad del Valle, Cali 760015, Colombia
Eduardo Gómez-Luna: High Voltage Research Group—GRALTA, School of Electrical and Electronic Engineering, Universidad del Valle, Cali 760015, Colombia
Josep M. Guerrero: Center for Research on Microgrids (CROM), AAU Energy, Aalborg University, 9220 Aalborg, Denmark
Juan C. Vasquez: Center for Research on Microgrids (CROM), AAU Energy, Aalborg University, 9220 Aalborg, Denmark

Energies, 2025, vol. 18, issue 10, 1-33

Abstract: The accelerated growth of scientific publications in renowned databases such as Scopus (Elsevier) and Web of Science (Clarivate) has made the identification of unresolved research problems increasingly complex. This challenge is exacerbated by the vast amount of information that must be analyzed, highlighting the imminent need for the application of big data techniques to extract relevant information for researchers, stakeholders in innovation and development, and regulatory policymakers. To address this challenge, this article presents an innovative, structured, and systematic methodology for conducting bibliometric analyses of scientific publications. The proposed approach is designed for researchers who only have an initial research idea, a broad problem context, or a general study area and require methodological tools to precisely define their research problem. The methodology follows a recommended flowchart-guided process, leveraging open-source tools such as Bibliometrix (R), spreadsheets, and text processing techniques to conduct a comprehensive bibliometric study. This enables the analysis of the intellectual, conceptual, and social structures of a research field, facilitating the identification of research gaps and emerging trends. As a practical application, the proposed methodology was implemented for the 2004–2024 period, within the framework of an applied research project in engineering. This case study aimed to answer key research questions formulated during the study design phase, demonstrating the effectiveness of the approach in systematically analyzing scientific production. Beyond the energy sector and energy systems, this methodology has proven to be adaptable to diverse disciplines, such as health sciences, industrial management, construction, and urban development, provided that relevant databases are accessible. Through this structured approach, researchers can better define their research problems and identify future challenges in various areas of knowledge.

Keywords: bibliometric; methodology; big data-based; distributed energy resources; analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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