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Application of Digital Technology in Cultural Heritage
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Application of Digital Technology in Cultural Heritage

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 20 September 2025 | Viewed by 5227

Special Issue Editors

Prof. Dr. Theodore Ganetsos

E-Mail Website
Guest Editor
Department of Industrial Design and Production Engineering, University of West Attica, 12244 Athens, Greece
Interests: physics of ionic bonds; non-destructive techniques; materials for photovoltaic applications; identification of materials and pigments; art and technology; archaeometry
Dr. Antreas Kantaros

E-Mail Website
Guest Editor
Department of Industrial Design and Production Engineering, University of West Attica, 12244 Athens, Greece
Interests: 3D printing; 3D scanning; non-destructive techniques; 3D CAD design; circular economy; sustainability; material science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The preservation, restoration, and study of cultural heritage have long relied on innovative techniques to safeguard humanity's shared history. The advancement of digital technologies has introduced transformative tools that allow non-invasive, precise, and scalable methods for documenting, analyzing, and preserving artifacts and heritage sites. This Special Issue of Applied Sciences seeks to explore the integration of digital and non-destructive techniques in cultural heritage, offering a platform to discuss the latest applications and advancements in the field.

The contributions in this Special Issue will focus on a range of state-of-the-art methods, including the following:

  • 3D Scanning: High-resolution 3D scanning technologies have revolutionized the documentation and analysis of historical artifacts, enabling detailed geometric data acquisition. Such data facilitate virtual reconstructions, condition assessments, and digital preservation, making it accessible to both researchers and the general public.
  • 3D Printing: The emerging technology of 3D printing has enabled the creation of accurate reproductions of artifacts for educational purposes, exhibitions, and physical restorations. This technology allows for the re-materialization of digital models, providing a tangible way to experience cultural heritage while minimizing risks to original pieces.
  • Raman Spectroscopy: Raman spectroscopy serves as a non-invasive tool to analyze the molecular composition of pigments, ceramics, and other materials used in historical artifacts. This technique aids in the identification of degradation processes and the provenance of materials, fostering better conservation strategies.
  • Fourier Transform Infrared Spectroscopy (FTIR): FTIR is extensively used in cultural heritage studies for the characterization of organic materials such as varnishes, resins, and binders. Its ability to provide molecular fingerprints of complex materials contributes significantly to conservation science.
  • Scanning Electron Microscopy (SEM): SEM offers detailed imagery and elemental analysis of cultural heritage materials at the microscale. This technology supports the study of degradation patterns and assists in the selection of appropriate conservation materials.

Additionally, the Special Issue welcomes papers on the following topics:

  • X-ray Computed Tomography (XCT): A non-invasive imaging technique providing three-dimensional insights into the internal structures of artifacts without the need for destructive sampling.
  • Hyperspectral Imaging: Used for the analysis of surface compositions, hyperspectral imaging detects a wide range of wavelengths to identify different materials, helping in detecting hidden layers of artwork or assessing their conditions.
  • Machine Learning and AI in Heritage Conservation: The integration of machine learning and artificial intelligence tools into the processing of large datasets collected from various scanning and spectroscopy techniques. These tools aid in automating and enhancing data analysis, fostering more efficient decision-making in conservation.

This Special  Issue aims to showcase the significant contributions of digital technologies in making cultural heritage more accessible and better preserved. By focusing on non-destructive and highly detailed methods, this collection of papers will demonstrate the synergy between cutting-edge scientific tools and the enduring value of our cultural patrimony.

Prof. Dr. Theodore Ganetsos
Dr. Antreas Kantaros
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • non-destructive techniques
  • 3D scanning
  • 3D printing
  • Raman spectroscopy
  • FTIR
  • SEM
  • XCT
  • hyperspectral imaging
  • machine learning
  • cultural heritage preservation
  • digital technology

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Published Papers (3 papers)

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Research

27 pages, 14735 KiB  
Article
Traditional and New Sensing Techniques Combination for the Identification of the Forgotten “New Flour-Weighing House” in Valencia, Spain
by Antonio Gómez-Gil, Giacomo Patrucco and José Luis Lerma
Appl. Sci. 2024, 14(24), 11962; https://doi.org/10.3390/app142411962 - 20 Dec 2024
Viewed by 910
Abstract
In the city of Valencia (Spain), there existed from the Middle Ages until the mid-nineteenth century a building that fulfilled a municipal strategic function: The “new flour-weighing house”. Its purpose was to distribute food to the population and collect the corresponding indirect municipal [...] Read more.
In the city of Valencia (Spain), there existed from the Middle Ages until the mid-nineteenth century a building that fulfilled a municipal strategic function: The “new flour-weighing house”. Its purpose was to distribute food to the population and collect the corresponding indirect municipal taxes. Today, the existence of this building is not remembered, neither by scientists nor by citizens, and its importance, location and appearance are unknown. The building investigated, behind which the medieval façade of the “flour-weighing house” is hidden, is the Colomina Palace. In the investigation, its growth phases have been detected, and an idea of its structural organisation has been obtained. Research and investigation have been carried out by consulting historical, cartographic and archival material, together with advanced geomatics techniques, including close-range photogrammetry, terrestrial laser scanning and thermography. The fuse of colour and thermal imagery, together with point clouds and 3D models, help to visualise and check the different spatial transformations of the current “Colomina Palace”, adapting the sequence from medieval times into present. The methodology proposed in this study avoids the need to carry out destructive tests and the processing of permits, which speeds up decision-making and historical architectural reconstruction. Full article
(This article belongs to the Special Issue Application of Digital Technology in Cultural Heritage)
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17 pages, 28882 KiB  
Article
Enhancing 3D-Printed Clay Models for Heritage Restoration Through 3D Scanning
by Eduardo Diz-Mellado, Jose Perez-Fenoy, Miguel Mudarra-Mata, Carlos Rivera-Gómez and Carmen Galan-Marin
Appl. Sci. 2024, 14(23), 10898; https://doi.org/10.3390/app142310898 - 25 Nov 2024
Cited by 1 | Viewed by 1715
Abstract
Recent development of methodologies based on digital twins through 3D scanning and 3D printing has increased over the past decade, offering new possibilities in manufacturing, production and scaling of models’ applications. However, there are few examples of the application of model digitization technologies [...] Read more.
Recent development of methodologies based on digital twins through 3D scanning and 3D printing has increased over the past decade, offering new possibilities in manufacturing, production and scaling of models’ applications. However, there are few examples of the application of model digitization technologies for the restoration of ceramic-built heritage by means of 3D modelling. That is why this research focuses on the application of these advanced methodologies to the recovery of architectural ceramic ornamental objects in heritage buildings. Deteriorated ceramic pieces are selected and scanned during field campaigns using 3D scanning technology in early 20th century heritage sites in Seville (Spain). The aim is to create accurate replicas of these damaged objects by 3D printing with clay using non-invasive techniques. The study stands out for its practical approach and its implications for the conservation of built cultural heritage. The results proved effective for replacing lost or damaged elements in a heritage context. Once the investment in the necessary equipment and technologies has been made, the use of clay as a material for 3D printing not only proves feasible but also offers advantages in terms of cost and time savings for repairs compared to traditional restoration techniques. In the present investigation the production time of similar pieces using 3D printing took 6.3–10.9 h while traditional methods take over a week. The application of these technologies represents an advancement in integrating modern methods into cultural heritage conservation, opening new possibilities for the preservation of history and art worldwide. Full article
(This article belongs to the Special Issue Application of Digital Technology in Cultural Heritage)
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32 pages, 5049 KiB  
Article
Digital Technology in Cultural Heritage: Construction and Evaluation Methods of AI-Based Ethnic Music Dataset
by Dayang Chen, Na Sun, Jong-Hoon Lee, Changman Zou and Wang-Su Jeon
Appl. Sci. 2024, 14(23), 10811; https://doi.org/10.3390/app142310811 - 22 Nov 2024
Cited by 3 | Viewed by 1842
Abstract
This study focuses on the construction and evaluation of a high-quality Chinese Manchu music dataset designed to facilitate Artificial Intelligence (AI) research and applications within cultural heritage and ethnomusicology. Through a systematic collection and organization of diverse Manchu music resources, including folk songs, [...] Read more.
This study focuses on the construction and evaluation of a high-quality Chinese Manchu music dataset designed to facilitate Artificial Intelligence (AI) research and applications within cultural heritage and ethnomusicology. Through a systematic collection and organization of diverse Manchu music resources, including folk songs, dance music, and ceremonial pieces, this dataset effectively represents the cultural breadth of Manchu music. The dataset includes digitized and preprocessed audio data, with comprehensive metadata annotations, such as essential information, musical features, and cultural context, creating a robust foundation for AI-based analysis. Experimental evaluations highlight the dataset’s utility across various AI-driven applications: in music classification, using a CNN model, an accuracy of 90% was achieved in the “folk ensemble” category, with an overall accuracy of 85.7% and a precision of 82.3%. For music generation, a Generative Adversarial Network (GAN) model yielded a quality score of 7.8/10 and a Fréchet Audio Distance (FAD) of 0.32. In emotion recognition, the Random Forest model achieved 87% accuracy in identifying the emotion “joy”. These results underscore the dataset’s potential in supporting digital preservation and expanding AI applications in ethnic music classification, generation, and emotional analysis, contributing to both cultural heritage preservation and AI advancement in ethnomusicology. Full article
(This article belongs to the Special Issue Application of Digital Technology in Cultural Heritage)
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