ABSTRACT
A bibliometric analysis was conducted to examine the trends and developments in the field of Virtual Power Plants (VPPs) from 2000 to June 2022. The selection and identification of data involved a systematic search resulting in 1245 articles for bibliometric analysis after applying the inclusion and exclusion criteria. Strategic diagrams, overlay graphs, and evolution maps were used to analyze the trends and themes in different periods. The analysis reveals the emergence and evolution of various themes and their interconnections. In the early periods, the focus was on energy market issues, distributed generation, and the control of Distributed Energy Resources. Themes such as microgrids, renewable energy, electric vehicles, and economic analysis have gained prominence over time. The present study also identified the introduction of new concepts such as prosumers, collaborative networks, and dynamic power plants in later periods. The performance analysis for the last period (2022) highlighted the centrality and density of themes such as power plants, renewable power plants, battery energy storage systems, and robust optimization. These themes are considered both fundamental and transverse in the research field. This study discusses the importance of VPPs and battery energy storage systems in addressing grid intermittency issues and providing auxiliary market services. The analysis also emphasized the management of the demand side and the integration of electric vehicles and Building Energy Management Systems in VPPs. Therefore, future directions for VPP research include innovative structures and topologies, big-data analysis, and diversified optimization techniques. This study provides insights into the evolution and current state of research in the field of VPPs and identifies areas for further exploration and development.
ABSTRACT
Big data launches a modern way of producing science and research around the world. Due to an explosion of data available in scientific databases, combined with recent advances in information technology, the researcher has at his disposal new methods and technologies that facilitate scientific development. Considering the challenges of producing science in a dynamic and complex scenario, the main objective of this article is to present a method aligned with tools recently developed to support scientific production, based on steps and technologies that will help researchers to materialize their objectives efficiently and effectively. Applying this method, the researcher can apply science mapping and bibliometric techniques with agility, taking advantage of an easy-to-use solution with cloud computing capabilities. From the application of the "Scientific Mapping Process", the researcher will be able to generate strategic information for a result-oriented scientific production, assertively going through the main steps of research and boosting scientific discovery in the most diverse fields of investigation. â¢The Scientific Mapping Process provides a method and a system to boost scientific development.â¢It automates Science Mapping and bibliometric analysis from scientific datasets.â¢It facilitates the researcher's work, increasing the assertiveness in scientific production.
ABSTRACT
Central America science production on biodiversity topics is important in planning future adaptive and conservation policies in a climate-related risk region that is considered a biodiversity hotspot but has the lowest Human Development Index of Latin America. Science production on biodiversity is related to geo-referenced species occurrence records, but the accessibility depends on political frameworks and science funding. This paper aims at foregrounding how the democratic shifts throughout the years have had an impact on science production on biodiversity research, and species records. For this exploration we developed a novel systematic scientometric analysis of science production on biodiversity topics, we used Bio-Dem (open-source software of biodiversity records and socio-political variables) and briefly analyzed the history-from 1980 to 2020-of Guatemala, El Salvador, Honduras, Nicaragua, Costa Rica, and Panama. With a data set of 16,304 documents, our analysis shows the significant discrepancies between the low science production of Central American Northern countries (Guatemala, El Salvador, Honduras, and Nicaragua), the prolific production from the Southern (Costa Rica and Panama), and how this relates to democratic stability. Scientific production tends to be more abundant when democratic conditions are guaranteed. The state capture phenomenon and colonial-rooted interactions worldwide have an effect on the conditions under which science is being produced in Central America. Democracy, science production, funding, and conservation are core elements that go hand in hand, and that need to be nourished in a region that struggles with the protection of life and extractive activities in a climate change scenario.
ABSTRACT
The agriculture sector is one of the backbones of many countries' economies. Its processes have been changing to enable technology adoption to increase productivity, quality, and sustainable development. In this research, we present a scientific mapping of the adoption of precision techniques and breakthrough technologies in agriculture, so-called Digital Agriculture. To do this, we used 4694 documents from the Web of Science database to perform a Bibliometric Performance and Network Analysis of the literature using SciMAT software with the support of the PICOC protocol. Our findings presented 22 strategic themes related to Digital Agriculture, such as Internet of Things (IoT), Unmanned Aerial Vehicles (UAV) and Climate-smart Agriculture (CSA), among others. The thematic network structure of the nine most important clusters (motor themes) was presented and an in-depth discussion was performed. The thematic evolution map provides a broad perspective of how the field has evolved over time from 1994 to 2020. In addition, our results discuss the main challenges and opportunities for research and practice in the field of study. Our findings provide a comprehensive overview of the main themes related to Digital Agriculture. These results show the main subjects analyzed on this topic and provide a basis for insights for future research.
Subject(s)
Internet of Things , Unmanned Aerial Devices , Agriculture , Bibliometrics , Humans , SoftwareABSTRACT
Landslides are generated by natural causes and by human action, causing various geomorphological changes as well as physical and socioeconomic loss of the environment and human life. The study, characterization and implementation of techniques are essential to reduce land vulnerability, different socioeconomic sector susceptibility and actions to guarantee better slope stability with a significant positive impact on society. The aim of this work is the bibliometric analysis of the different types of landslides that the United States Geological Survey (USGS) emphasizes, through the SCOPUS database and the VOSviewer software version 1.6.17, for the analysis of their structure, scientific production, and the close relationship with several scientific fields and its trends. The methodology focuses on: (i) search criteria; (ii) data extraction and cleaning; (iii) generation of graphs and bibliometric mapping; and (iv) analysis of results and possible trends. The study and analysis of landslides are in a period of exponential growth, focusing mainly on techniques and solutions for the stabilization, prevention, and categorization of the most susceptible hillslope sectors. Therefore, this research field has the full collaboration of various authors and places a significant focus on the conceptual evolution of the landslide science.
Subject(s)
Landslides , Geographic Information Systems , Geology , HumansABSTRACT
This paper analyzes the scientific map of technostress and the scientific production on this topic between 1982 and 2017, highlighting its structure, evolution, and trends in this field. A literature review based on bibliometric analysis of 246 records indexed in Scopus database was conducted. These publications were analyzed according to bibliometric indicators and through science maps with SciMAT. Co-occurrence of terms by grouping techniques was implemented. In addition, elaboration of maps of science and performance analysis for periods was executed. The main contribution of this work is to provide the first scientific map of technostress and a detailed understanding of the scientific production that predicts the directions of future research. The bibliometric analyses permit an overview of the growth, extent and distribution of the scientific literature related to the technostress and the study of the scientific production of an institution, country, author or research group.
ABSTRACT
In order to identify the strategic topics and the thematic evolution structure of data mining applied to healthcare, in this paper, a bibliometric performance and network analysis (BPNA) was conducted. For this purpose, 6138 articles were sourced from the Web of Science covering the period from 1995 to July 2020 and the SciMAT software was used. Our results present a strategic diagram composed of 19 themes, of which the 8 motor themes ('NEURAL-NETWORKS', 'CANCER', 'ELETRONIC-HEALTH-RECORDS', 'DIABETES-MELLITUS', 'ALZHEIMER'S-DISEASE', 'BREAST-CANCER', 'DEPRESSION', and 'RANDOM-FOREST') are depicted in a thematic network. An in-depth analysis was carried out in order to find hidden patterns and to provide a general perspective of the field. The thematic network structure is arranged thusly that its subjects are organized into two different areas, (i) practices and techniques related to data mining in healthcare, and (ii) health concepts and disease supported by data mining, embodying, respectively, the hotspots related to the data mining and medical scopes, hence demonstrating the field's evolution over time. Such results make it possible to form the basis for future research and facilitate decision-making by researchers and practitioners, institutions, and governments interested in data mining in healthcare.
Subject(s)
Biomedical Research , Data Mining , Bibliometrics , Delivery of Health Care , Humans , IntelligenceABSTRACT
In this study, we explore a 100 years of Work and Organizational Psychology (WOP). To do this, we carry out a bibliometric performance and network analysis (BPNA) to understand the evolution structure and the most important themes in the field of study. To perform the BNPA, 8,966 documents published since 1919 were exported from the Web of Science and Scopus databases. The SciMAT software was used to process data and to create the evolution structure, the strategic diagram, and the thematic network structure of the strategic themes of the field of WOP. We identified 29 strategic clusters and discuss the most important themes (motor themes) and their relationship with other clusters. This research presents the complete evolution of the field of study, identifying emerging themes and others with a high degree of development. We hope that this work will support researchers and future research in the field of WOP.