Cultural Heritage Domain Research Articles

An Analysis of Research Trends for Using Artificial Intelligence in Cultural Heritage

Artificial intelligence (AI) techniques have been increasingly applied in assisting various cultural heritage (CH)-related tasks. The aim of this study is to examine the research trends and current applications of AI in this vast domain. After obtaining a dataset from the Web of Science and Scopus databases, a scientometric analysis of research publications from 2019 to 2023 related to the use of AI in CH was conducted. The trending topics based on the author’s keywords were identified by using the ScientoPy v2.1.3 software. Through this approach, five main topics were identified: classification, computer vision, 3D reconstruction, recommender systems, and intangible cultural heritage. The analysis highlights the upward trend in publications in this field since 2019, indicating a growing interest in the application of AI techniques in CH. By analyzing the latest research in the field, it is observed that AI techniques are mostly applied to assist CH in the discovery, description, classification, and preservation tasks. The report gives insights into the main research areas and developing trends in the field of artificial intelligence and machine learning. The study offers important information about the key research areas and emerging trends related to using AI techniques in the CH field. This helps to recognize the potential, development, and increasing influence of these technologies within the CH domain. The findings of this study contribute to the future development of AI applications in CH, enabling professionals to use the advantages of these technologies.

A Systematic Literature Review of Handicraft Heritage Co-design Towards Sustainable Development

This systematic literature review (SLR) explores the integration of co-design within the domain of intangible cultural heritage (ICH) handicrafts to address Sustainable Development Goals (SDGs). Traditional handicrafts, enriched with cultural significance and economic potential, face challenges such as competition with mass-produced goods, loss of intergenerational skills, and difficulties in integrating modern design practices. Co-design, a collaborative process involving multiple stakeholders, offers a potential solution to these challenges. This review synthesizes findings from various studies to identify key themes, trends, and gaps in the literature. It aims to provide insights for policymakers, designers, and cultural practitioners to enhance the sustainability and cultural relevance of traditional handicrafts through co-design.

Socio-cultural challenges in collections digital infrastructures

PurposeThis paper aims to explore the accelerations and constraints libraries, archives, museums and heritage organisations (“collections-holding organisations”) face in their role as collection data providers for digital infrastructures. To date, digital infrastructures operate within the cultural heritage domain typically as data aggregation platforms, such as Europeana or Art UK.Design/methodology/approachSemi-structured interviews with 18 individuals in 8 UK collections-holding organisations and 2 international aggregators.FindingsDiscussions about digital infrastructure development often lay great emphasis on questions and problems that are technical and legal in nature. As important as technical and legal matters are, more latent, yet potent challenges exist too. Though less discussed in the literature, collections-holding organisations' capacity to participate in digital infrastructures is dependent on a complex interplay of funding allocation across the sector, divergent traditions of collection description and disciplinaries’ idiosyncrasies. Accordingly, we call for better social-cultural and trans-sectoral (collections-holding organisations, universities and technological providers) understandings of collection data infrastructure development.Research limitations/implicationsThe authors recommend developing more understanding of the social-cultural aspects (e.g. disciplinary conventions) and their impact on collection data dissemination. More studies on the impact and opportunities of unified collections for different audiences and collections-holding organisations themselves are required too.Practical implicationsSustainable financial investment across the heritage sector is required to address the discrepancies between different organisation types in their capacity to deliver collection data. Smaller organisations play a vital role in diversifying the (digital) historical canon, but they often struggle to digitise collections and bring catalogues online in the first place. In addition, investment in existing infrastructures for collection data dissemination and unification is necessary, instead of creating new platforms, with various levels of uptake and longevity. Ongoing investments in collections curation and high-quality cataloguing are prerequisites for a sustainable heritage sector and collection data infrastructures. Investments in the sustainability of infrastructures are not a replacement for research and vice versa.Social implicationsThe authors recommend establishing networks where collections-holding organisations, technology providers and users can communicate their experiences and needs in an ongoing way and influence policy.Originality/valueTo date, the research focus on developing collection data infrastructures has tended to be on the drive to adopt specific technological solutions and copyright licensing practices. This paper offers a critical and holistic analysis of the dispersed experience of collections-holding organisations in their role as data providers for digital infrastructures. The paper contributes to the emerging understanding of the latent factors that make infrastructural endeavours in the heritage sector complex undertakings.

Archaeometa: leveraging blockchain for secure and scalable virtual museums in the metaverse

The rapid evolution of the digital landscape has catalyzed the integration of blockchain technology within the domain of cultural heritage, particularly in virtual museums within the Metaverse. This study introduces ArchaeoMeta, a novel framework designed to leverage blockchain technology to enhance security, authenticity, and visitor interaction in a virtual museum environment. Utilizing smart contracts deployed on the Ethereum Sepolia testnet, the framework manages visitor interactions and secures digital artifacts, addressing challenges associated with scalability and user experience under varying loads. The performance evaluation involved simulating user interactions, scaling up to ten thousand concurrent users, to assess the impact on transaction latency, gas usage, and blockchain size. Findings reveal significant scalability challenges, as transaction latency and blockchain size increased with the number of users, highlighting areas for optimization in managing high user traffic within the blockchain infrastructure. This study contributes to the understanding of blockchain applications in cultural heritage, suggesting that while ArchaeoMeta offers a robust platform for virtual museums, enhancements in scalability through layer-2 solutions or alternative blockchain platforms are essential for its practical implementation. The framework sets a precedent for future research in the convergence of blockchain technology and cultural heritage preservation, promising a transformative impact on how digital cultural experiences are curated and consumed.

The Role of Audio in Immersive Storytelling: a Systematic Review in Cultural Heritage

AbstractNowadays, Virtual and Augmented Reality technologies play a supportive role in many research fields. In cultural heritage, various examples are available, including storytelling and narratives, where they can provide immersive and enhanced experiences to visitors and tourists, especially for entertainment and educational purposes. This review aims to investigate the opportunities that soundscape design and advanced sonic interactions in virtual and augmented environments can bring to cultural heritage sites and museums in terms of presence, emotional content, and cultural dissemination. Nineteen-two papers have been identified through the PRISMA methodology, and a promising positive effect of sonic interaction on user experience in a virtual environment can be observed in various studies, notwithstanding a general lack of specific contributions on the use of sound rendering and audio spatialisation for improving such experiences. Moreover, this work identifies the main involved research areas and discusses the state-of-the-art best practices and case studies where sonic interactions may assume a central role. The final part suggests possible future directions and applications for more engaging and immersive storytelling in the cultural heritage domain.

Classifying deceptive reviews for the cultural heritage domain: A lexicon-based approach for the Italian language

Nowadays, the spread of deceptive reviews is a problem that has reached critical dimensions, having a significant economic impact on business activities. This paper aims to estimate – at the quantitative and qualitative levels – the possibility of using particular words to disambiguate between truthful and deceptive text, focusing on reviews produced in the cultural heritage domain. For this purpose, a lexicon-based methodology has used two different lexicons: sentiment information, intensifiers, downtoners, and negation operators. As known in the literature, these elements are crucial in a classification process related to deceptiveness. The evaluation phase has considered quantitative metrics such as accuracy and F1 score and ad hoc developed metrics that consider specific linguistic parameters such as polarity and tone of voice intensifiers. A qualitative analysis of a subset of the corpus has also been carried out to understand better factors that impact the classification of deceptive review. Several linguistic features have been considered, ranging from the number of intensifiers to their type and position in phrases and sentences. A comparison between the performances of two different lexicons used has been added to the analysis.

GNSS ASSISTED PHOTOGRAMMETRIC RECONSTRUCTION FROM COMBINED 360° VIDEOS AND UAV IMAGES

Abstract. This paper introduces an integrated approach utilizing ground data consists of videos captured with a 360° (spherical) camera and aerial data acquired with a UAV equipped with a RTK GNSS module to reconstruct a portion of a small-town city center and/or a cultural heritage site. Previous research has demonstrated that image blocks oriented with RTK data on camera position can reach centimeter accuracies and can be efficiently used to reconstruct large areas and single monuments. However, some areas like porches, narrow passages and streets cannot be properly reconstructed from an aerial point of view. Conversely, ground-based 360° images offer detailed insights into the terrain and features that may be obscured from an aerial perspective. Integration of those two points of view can increase spatial resolution and coverage for 3D reconstruction. Indeed, the UAV captures large-scale features and topography, while ground-based 360° images focus on intricate details and ground-level characteristics. The possibility to exploit GNSS data acquired by UAV may also be used for GNSS-assisted image orientation with the aim of reducing or even avoiding, in specific situations, the need for GCPs. The paper explores practical applications of such data integration in the cultural heritage domain demonstrating the efficacy of the integrated approach in scenarios with complex architectures and inaccessible areas.

Comparative Assessment of Neural Radiance Fields and Photogrammetry in Digital Heritage: Impact of Varying Image Conditions on 3D Reconstruction

This paper conducts a comparative evaluation between Neural Radiance Fields (NeRF) and photogrammetry for 3D reconstruction in the cultural heritage domain. Focusing on three case studies, of which the Terpsichore statue serves as a pilot case, the research assesses the quality, consistency, and efficiency of both methods. The results indicate that, under conditions of reduced input data or lower resolution, NeRF outperforms photogrammetry in preserving completeness and material description for the same set of input images (with known camera poses). The study recommends NeRF for scenarios requiring extensive area mapping with limited images, particularly in emergency situations. Despite NeRF’s developmental stage compared to photogrammetry, the findings demonstrate higher potential for describing material characteristics and rendering homogeneous textures with enhanced visual fidelity and accuracy; however, NeRF seems more prone to noise effects. The paper advocates for the future integration of NeRF with photogrammetry to address respective limitations, offering more comprehensive representation for cultural heritage preservation tasks. Future developments include extending applications to planar surfaces and exploring NeRF in virtual and augmented reality, as well as studying NeRF evolution in line with emerging trends in semantic segmentation and in-the-wild scene reconstruction.

Women's Activities and the Preservation of Intangible Cultural Heritage in the Gorani Community

Research endeavors within the domain of intangible cultural heritage, conducted within the Gorani community, highlight, among various aspects, the involvement of women in creating and transmitting knowledge and skills, which are perceived by the Gorani populace as a particularly important component of the Gorani tradition. Women are ascribed a key role in preserving Gorani cultural heritage. This study examines the activities of women in the Gorani community within the UNESCO Convention for the Safeguarding of the Intangible Cultural Heritage framework. The research is focused on knowledge, skills, and practices carried out by women, which unfold continually within the Gorani community during the twentieth and twenty-first centuries. It primarily concerns the knowledge and skills of women manifested through the tradition of designing and wearing clothing items, especially those pieces that have become over time an indispensable part of women's ceremonial attire. The empirical data also encourages an examination of the role of women in shaping identity paradigms and symbols in the Gorani community, as well as their expression, transmission, and the assurance of the continuity of these practices. The analysis of women’s contribution to safeguarding the intangible cultural heritage of the Gorani community indicates that the preservation and protection of Gorani tradition, as understood and recognized by the participants in accordance with the UNESCO Convention defining heritage, are conditioned by the social, economic, and political circumstances shaping daily activities and everyday lives of the people in Gora, both within and beyond their native local environment. It is also obvious that Gorani’s interest in their own intangible cultural heritage is unmistakable, as demonstrated by social and cultural practices that would be impracticable without the existence of this heritage. The Gorani people's aspiration to safeguard their own cultural heritage is viewed in the context of its contribution to the preservation and continuity of the Gorani identity, namely the identity of the Gorani community, which holds minority status in the Republic of Serbia.

문화적 도시경쟁력 강화를 위한 문화정책 연구

This study focused on examining recent trends and solutions for urban revitalization through cultural means, responding to the heightened concerns and growing interests of many cities in augmenting the value and competitiveness of city. Accordingly,a case study of the Gongju Cultural City Center was conducted as a model to address the enhancement of urban competitiveness through cultural means, focusing on aspects such as facility expansion, population growth, and the activation of economic activities from a problem-solving perspective. Gongju City was designated as a cultural city by the Ministry of Culture, Sports, and Tourism(2021). Leveraging preliminary investigations and specialized textual studies, it has spearheaded specific projects focusing on future cultural heritage domains. As a core project, efforts were made to enhance the competitiveness of the region and the city through initiatives such as the Gongju Art Shop Street and the Gallery Weekly Project. Analytical results revealed significant achievements across all aspects related to urban competitiveness, including the expansion of cultural facilities, population growth and development, and the activation of economic activities. To enhance the role and sustainability of the Cultural City Center, it is considered essential to facilitate diverse collaboration among various stakeholders and engage in multifaceted consultations with administrative bodies from the planning to the execution stages of a broader spectrum of initiatives. This study is considered valuable not only for establishing theoretical frameworks but also as foundational data that can be utilized in the field for deriving future directions and advancements in the Cultural City project.

Redefining User Expectations: The Impact of Adjustable Social Autonomy in Human–Robot Interaction

To promote the acceptance of robots in society, it is crucial to design systems exhibiting adaptive behavior. This is particularly needed in various social domains (e.g., cultural heritage, healthcare, education). Despite significant advancements in adaptability within Human-Robot Interaction and Social Robotics, research in these fields has overlooked the essential task of analyzing the robot’s cognitive processes and their implications for intelligent interaction (e.g., adaptive behavior, personalization). This study investigates human users’ satisfaction when interacting with a robot whose decision-making process is guided by a computational cognitive model integrating the principles of adjustable social autonomy. We designed a within-subjects experimental study in the domain of Cultural Heritage, where users (e.g., museum visitors) interacted with the humanoid robot Nao. The robot’s task was to provide the user with a museum exhibition to visit. The robot adopted the delegated task by exerting some degree of discretion, which required different levels of autonomy in the task adoption, relying on its capability to have a theory of mind. The results indicated that as the robot’s level of autonomy in task adoption increased, user satisfaction with the robot decreased, whereas their satisfaction with the tour itself improved. Results highlight the potential of adjustable social autonomy as a paradigm for developing autonomous adaptive social robots that can improve user experiences in multiple HRI real domains.

Automatic generation of synthetic heritage point clouds: Analysis and segmentation based on shape grammar for historical vaults

Historical heritage is demanding robust pipelines for preserving, enhancing, and disseminating its prominent value. Semantic segmentation of 3D Point Clouds has gained increasing attention over the years, since it might assist in automati­cally recognizing historical architectural elements, thus facilitating large dataset management. Nonetheless, semantic segmentation is particularly challenging in Cultural Heritage (CH) domain, due to the shapes complexity and the limited repeatability of elements across different architectures, which strengthens the difficulty to define common patterns within the same class of elements. Besides, as Deep Neural Networks demand an appreciably amount of labelled data to be trained, the lack of available annotated heritage point clouds prevent the research in this direction. To tackle these issues, in this paper it is proposed a Deep Learning system able to recognize historical building elements by lever­aging synthetic point cloud. The generation of the 3D models, vaults, is based on a procedural modeling approach that follows the ideal shapes, according to the rules of descriptive geometry for the main types of vaults. The approach has been applied to a newly synthetic dataset which is publicly available. This dataset comprises 6 labelled points clouds, derived from a comprehensive on­tological taxonomy in order to describe an univocal and robust architectural hierarchy: barrel vaults, groined vaults, mirror vaults, barrel vaults with clois­ter heads and lunettes, barrel vaults with lunettes, sail vaults. The experiments yield high accuracy, demonstrating the effectiveness and suitability of the pro­posed approach.

Knowledge Organisation Systems in the Humanities—Semantic Interoperability in Practice

ABSTRACTWe observe a growing universe of machine‐readable knowledge organisation systems (KOS) or even wider ‘semantic artifacts. We see at the same time, various attempts to bring semantic artifacts together via registries, catalogues and via cross‐walks among ontologies. This poster reflects how newest research on semantic interoperability informs current practice for research data repositories and registry service providers. We focus on the domain of humanities and cultural heritage, using different examples from Europe and the Netherlands: The European Archaeological Data Infrastructure Ariadne, services of the Dutch Cultural Heritage Network and two Data Stations (for Archaeology and for SSH) hosted at DANS‐KNAW. For those cases we report on current efforts to include ‘semantic artifacts’, together with opportunities and challenges. This poster is a practice report combined with an invitation to reflect about the context of semantic interoperability itself.

Clustering Heterogeneous Data Values for Data Quality Analysis

Data is of high quality if it is fit for its intended purpose. Data heterogeneity can be a major quality problem, as quality aspects such as understandability and consistency can be compromised. Heterogeneity of data values is particularly common when data is manually entered by different people using inadequate control rules. In this case, syntactic and semantic heterogeneity often go hand in hand. Heterogeneity of data values may be a direct result of problems in the acquisition process, quality problems of the underlying data model, or possibly erroneous data transformations. For example, in the cultural heritage domain, it is common to analyze data fields by manually searching lists of data values sorted alphabetically or by number of occurrences. Additionally, search functions such as regular expression matching are used to detect specific patterns. However, this requires a priori knowledge and technical skills that domain experts often do not have. Since such datasets often contain thousands of values, the entire process is very time-consuming. Outliers or subtle differences between values that may be critical to data quality can be easily overlooked. To improve this process of analyzing the quality of data values, we propose a bottom-up human-in-the-loop approach that clusters values of a data field according to syntactic similarity. The clustering is intended to help domain experts explore the heterogeneity of values in a data field and can be configured by domain experts according to their domain knowledge. The overview of the syntactic diversity of the data values gives an impression of the rules and practices of data acquisition as well as their violations. From this, experts can infer potential quality issues with the data acquisition process and system, as well as the data model and data transformations. We outline a proof-of-concept implementation of the approach. Our evaluation found that clustering adds value to data quality analysis, especially for detecting quality problems in data models.

Dunhuang Dreamscape: A Study and Exploration of Dunhuang Art in Modern Interior Design based on Virtual Reality Technology

In the context of the national initiative of the "Belt and Road" policy and the vigorous promotion of cultural soft power, interior design products infused with cultural creativity have emerged as significant carriers of cultural development and heritage. This paper explores the innovative application of virtual reality technology in the field of interior design, with a special focus on the integration of Dunhuang elements in design practices. By combining virtual reality technology with Dunhuang art, a novel paradigm for interior design is proposed, blending ancient murals, patterns, and colors with modern computer graphics technology, infusing spaces with a unique historical charm and cultural significance. From the perspectives of virtual reality technology, inheritance of Dunhuang artistic elements, Dunhuang-style spatial design based on virtual reality, user experience, and emotional resonance, this paper delves into an in-depth exploration. Its aim is to expand innovative paths within interior design, while simultaneously providing new ideas and methods for cultural heritage and spatial perception domains.

Novel Video Benchmark Dataset Generation and Real-Time Recognition of Symbolic Hand Gestures in Indian Dance Applying Deep Learning Techniques

A computational approach towards promoting, preservation, and dissemination of knowledge in the domain of cultural heritage, is one of the research areas that has a wide scope. There has been a seismic shift in the way many sectors in society have adapted themselves to the pandemic situation, be it healthcare, food, education, diplomacy, and performing arts. Virtual learning and performing have become the need of the hour in the field of performing arts as well. The objective of this work is threefold; first, this creates benchmark datasets to be shared to make a beneficial impact and for a meaningful engagement by capturing, recognising, and classifying the multimedia content for hastamudras (hand poses) in Bharatanatyam, an Indian classical dance form, which plays a significant role in the conservation of intangible cultural heritage, second, as tutoring system to aspiring learners and third, to build video recommendation systems to promote art as a tool for building an international relationship and further elevate the significance of soft-power through performing arts. This article proposes applying the deep-learning techniques of CNNs as a critical technology to recognise the correct mudra. Experimental results on our challenging mudra dataset through the MobileNet architecture show 85%–95% accuracy in real-time, which outperforms the Sebastien-Marcel dataset. The time taken to process an image is 0.172 seconds, and the result is significant considering that the images are dynamic. This work proves the accuracy of the proposed method, which significantly outperforms another CNN-based Inception v3 model.

The Facets of Intangible Heritage in Southern Chinese Martial Arts: Applying a Knowledge-driven Cultural Contact Detection Approach

Investigating the intangible nature of a cultural domain can take multiple forms, addressing, for example, the aesthetic, epistemic, and social dimensions of its phenomenology. The context of Southern Chinese martial arts is of particular significance, as it carries immaterial components of all these aspects: The technical and stylistic framework of a martial art system; the imagery associated to movements; and the transmission of knowledge orally, practically, or through influence, are but examples of intangible characteristics that can and should be captured, not unlike cultural artifacts. The latter case—the one of formalizing cultural influence through its various forms of evidenceis emblematic as well as largely untrodden ground. A previous attempt at detecting cultural influence computationally was made in the context of Roman archaeology, though the binding of that early effort with the domain model was tight; also, there has hardly been any prior dedicated effort to model the martial arts domain through ontologies. In this article, we present the realization of the full cycle of a computational approach to investigating cultural contact in Southern Chinese martial arts. The entire approach is predicated upon the usage of standards and techniques of the Semantic Web and formal knowledge. Starting from a modular domain ontology, which models martial arts independently of the goal of capturing cultural influence, we perform knowledge extraction from archival material from the Hong Kong Martial Arts Living Archive and generate a dataset of the results modeled after said ontology. Then, we combine the resulting knowledge base with a rule model that represents ways to infer knowledge of potential contact between cultures based on the evidence present in the knowledge base. The results offer an insight into how an inference-based computational model can be applied to detect interesting facts even in the as-yet underexplored domain of intangible cultural heritage. The implemented workflow shows that the full-cycle employment of semantic technologies can offer the ground truth required for largely different approaches, such as statistical and machine learning ones, to operate.

CLEF. A Linked Open Data Native System for Crowdsourcing

Collaborative data collection initiatives are increasingly becoming pivotal to cultural institutions and scholars, to boost the population of born-digital archives. For over a decade, organisations have been leveraging Semantic Web technologies to design their workflows, ensure data quality, and a means for sharing and reusing (Linked Data). Crucially, scholarly projects that leverage cultural heritage data to collaboratively develop new resources would benefit from agile solutions to simplify the Linked Data production workflow via user-friendly interfaces. To date, only a few pioneers have abandoned legacy cataloguing and archiving systems to fully embrace the Linked Open Data (LOD) paradigm and manage their catalogues or research products through LOD-native management systems. In this article we present Crowdsourcing Linked Entities via web Form (CLEF) , an agile LOD-native platform for collaborative data collection, peer-review, and publication. We detail design choices as motivated by two case studies, from the Cultural Heritage and scholarly domains respectively, and we discuss benefits of our solution in the light of prior works. In particular, the strong focus on user-friendly interfaces for producing FAIR data, the provenance-aware editorial process, and the integration with consolidated data management workflows, distinguish CLEF as a novel attempt to develop Linked Data platforms for cultural heritage.

TTProfiler: Types and Terms Profile Building for Online Cultural Heritage Knowledge Graphs

As more and more knowledge graphs (KGs) are published on the Web, there is a need for tools that show their content. This implies showing the schema-level patterns instantiated in the graph, but also the terms used to qualify its entities. In this article, we present a new profiling tool that we call TTprofiler. It shows the predicates that relate types in the KG, and also the terms present in this KG, because of their paramount importance in most KGs, especially in the Cultural Heritage (CH) domain. We recall the role of terminologies and how they are implemented and used on the Web, we give the algorithm for building a TT profile from an online KG’s endpoint, and we report on experiments performed over a set of Cultural Heritage Web KGs. A tool for visualizing TT profiles is also provided.

Around the GLOBE: Numerical Aggregation Question-answering on Heterogeneous Genealogical Knowledge Graphs with Deep Neural Networks

One of the key AI tools for textual corpora exploration is natural language question-answering (QA). Unlike keyword-based search engines, QA algorithms receive and process natural language questions and produce precise answers to these questions, rather than long lists of documents that need to be manually scanned by the users. State-of-the-art QA algorithms based on DNNs were successfully employed in various domains. However, QA in the genealogical domain is still underexplored, and researchers in this field (and other fields in humanities and social sciences) can highly benefit from the ability to ask questions in natural language, receive concrete answers, and gain insights hidden within large corpora. While some research has been recently conducted for factual QA in the genealogical domain, to the best of our knowledge, there is no previous research on the more challenging task of numerical aggregation QA (i.e., answering questions combining aggregation functions, e.g., count, average, max). Numerical aggregation QA is critical for distant reading and analysis for researchers (and the general public) interested in investigating cultural heritage domains. Therefore, in this study, we present a new end-to-end methodology for numerical aggregation QA for genealogical trees that includes (1) an automatic method for training dataset generation, (2) a transformer-based table selection method, and (3) an optimized transformer-based numerical aggregation QA model. The findings indicate that the proposed architecture, GLOBE, outperforms the state-of-the-art models and pipelines by achieving 87% accuracy for this task compared to only 21% by current state-of-the-art models. This study may have practical implications for genealogical information centers and museums, making genealogical data research easy and scalable for experts as well as the general public.