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Cultural heritage preservation in the digital age, harnessing artificial intelligence for the future: a bibliometric analysis

Dessy Harisanty (Faculty of Vocational Studies, Universitas Airlangga, Surabaya, Indonesia)
Kathleen Lourdes Ballesteros Obille (School of Library and Information Studies, University of the Philippines Diliman, Quezon City, Philippines)
Nove E. Variant Anna (Faculty of Vocational Studies, Universitas Airlangga, Surabaya, Indonesia)
Endah Purwanti (Faculty of Science and Technology, Universitas Airlangga, Surabaya, Indonesia)
Fitri Retrialisca (Faculty of Vocational Studies, Universitas Airlangga, Surabaya, Indonesia)

Digital Library Perspectives

ISSN: 2059-5816

Article publication date: 20 September 2024

Issue publication date: 29 October 2024

206

Abstract

Purpose

This study aims to investigate the performance analysis, science mapping and future direction of artificial intelligence (AI) technology, applications, tools and software used to preserve, curate and predict the historical value of cultural heritage.

Design/methodology/approach

This study uses the bibliometric research method and utilizes the Scopus database to gather data. The keywords used are “artificial intelligence” and “cultural heritage,” resulting in 718 data sets spanning from 2001 to 2023. The data is restricted to the years 2001−2023, is in English language and encompasses all types of documents, including conference papers, articles, book chapters, lecture notes, reviews and editorials.

Findings

The performance analysis of research on the use of AI to aid in the preservation of cultural heritage has been ongoing since 2001, and research in this area continues to grow. The countries contributing to this research include Italy, China, Greece, Spain and the UK, with Italy being the most prolific in terms of authored works. The research primarily falls under the disciplines of computer science, mathematics, engineering, social sciences and arts and humanities, respectively. Document types mainly consist of articles and proceedings. In the science mapping process, five clusters have been identified. These clusters are labeled according to the contributions of AI tools, software, apps and technology to cultural heritage preservation. The clusters include “conservation assessment,” “exhibition and visualization,” “software solutions,” “virtual exhibition” and “metadata and database.” The future direction of research lies in extended reality, which integrates virtual reality (VR), augmented reality (AR) and mixed reality (MR); virtual restoration and preservation; 3D printing; as well as the utilization of robotics, drones and the Internet of Things (IoT) for mapping, conserving and monitoring historical sites and cultural heritage sites.

Practical implications

The cultural heritage institution can use this result as a source to develop AI-based strategic planning for curating, preservation, preventing and presenting cultural heritages. Researchers and academicians will get insight and deeper understanding on the research trend and use the interdisciplinary of AI and cultural heritage for expanding collaboration.

Social implications

This study will help to reveal the trend and evolution of AI and cultural heritage. The finding also will fill the knowledge gap on the research on AI and cultural heritage.

Originality/value

Some similar bibliometric studies have been conducted; however, there are still limited studies on contribution of AI to preserve cultural heritage in wider view. The value of this study is the cluster in which AI is used to preserve, curate, present and assess cultural heritages.

Keywords

Acknowledgements

This research is the result of the International Research Collaboration Top 500 Universitas Airlangga with Ref. No.: 360/UN3.15/PT/2023.

Citation

Harisanty, D., Obille, K.L.B., Anna, N.E.V., Purwanti, E. and Retrialisca, F. (2024), "Cultural heritage preservation in the digital age, harnessing artificial intelligence for the future: a bibliometric analysis", Digital Library Perspectives, Vol. 40 No. 4, pp. 609-630. https://doi.org/10.1108/DLP-01-2024-0018

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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