Bibliometric analysis of fourth industrial revolution applied to heritage studies based on web of science and scopus databases from 2016 to 2021

被引:19
作者
Alviz-Meza, Anibal [1 ,2 ]
Vasquez-Coronado, Manuel H. [3 ]
Delgado-Caramutti, Jorge G. [4 ]
Blanco-Victorio, Daniel J. [4 ]
机构
[1] Univ Senor Sipan, Fac Engn Arquitecture & Urbanism, Grp Invest Deterioro Mat, Transic Energet & Ciencia Datos DANT3, Chiclayo 14001, Peru
[2] Univ Cartagena, Chem Engn Sch, Ave Consulado Calle,30 48 152, Cartagena De Indias, Colombia
[3] Univ Senor Sipan, Semillero Invest Corros Met Energras Sostenibles, Fac Enginering Arquitecture & Urbanism, Chiclayo 14001, Pimentel, Peru
[4] Univ Senor Sipan, INVESSALUD, Life Sci & Human Hlth Care, Chiclayo 14001, Pimentel, Peru
关键词
Bibliometric; Heritage; Industry; 4; 0; Scopus; Web of Science; Biblioshiny; VOSviewer; DECAY; ART;
D O I
10.1186/s40494-022-00821-3
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
Using past material and spiritual remains, cultural heritage examines communities' identity formation across time. Cultural heritage requires public and private institutions to care about its restoration, maintenance, conservation, and promotion. Through a bibliometric perspective, this study has analyzed, quantified, and mapped the scientific production of the fourth industrial revolution applied to heritage studies from 2016 to 2021 in the Scopus and Web of Science databases. Biblioshiny software from RStudio was employed to categorize and evaluate the contribution of authors, countries, institutions, and journals. In addition, VOSviewer was used to visualize their collaboration networks. As a main result, we found that augmented reality and remote sensing represent the research hotspot concerning heritage studies. Those techniques have become common in archaeology, as well as museums, leading to an increase in their activity. Perhaps, more recent tools, such as machine learning and deep learning, will provide future pathways in cultural heritage from data collected in social networks. This bibliometric analysis, therefore, provides an updated perspective of the implementations of technologies from industry 4.0 in heritage science as a possible guideline for future worldwide research.
引用
收藏
页数:17
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