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Cultural heritage archiving is experiencing an increase in digitalisations of artefacts in the last 15 years. The reason behind this trend is a demand for providing information about the artefact in a more accessible way to the audience, for example, through online delivery or virtual reality. Other reasons might be to simplify and automate the management of artefacts. Having a ‘digital copy’ of artefacts, allows one to search an archive and plan its storage and dissemination in a comprehensive manner. With the increased digitalisation comes an increased use of artificial intelligence [AI] applications. AI can be very beneficial in classifying artefacts automatically through machine learning [ML] and natural language processing [NLP]. For example, an algorithm can identify the source and age of artefacts based on an image and can do this much faster for a large collection of photos than a human. Although AI provides many benefits, it also presents challenges: Sophisticated AI techniques require certain insights on how they work, need specialists to customise a solution, and require an existing large dataset to train an algorithm. Another challenge is that typical AI techniques are regarded as black boxes, which means they decide, but it is not obvious why a decision has been made. This chapter describes a project in collaboration with the South Australian Museum [SAM] on the application of AI to extract material lists from a description of artefacts. A large dataset to train an algorithm did not exist, and hence, a customised approach was required. The outcome of the project was the application of NLP in combination with easy-to-customise rules that can be applied by non-IT specialists. The resulting prototype achieved the extraction of materials from a large list of artefacts within seconds and a flexible solution that can be applied on other collections in the future.

In this study, the distinctive functional features of linked data (LD) catalogues were investigated to contrast with existing online public access catalogues (OPACs) and discovery systems using a checklist approach. The checklist was derived from a literature review and is composed of 10 items as follows: self-descriptive and dynamic content for resource description, linkage to external LD sources and online services, aggregation of knowledge contexts into knowledge graphs (KGs), URI-based link discovery, representation and query of LD relationships, URI-based serendipitous discovery, keyword recommendation, faceted limitation and browsing, visualization and openness of data.

Ten functional features derived from the literature were checked against existing LD catalogues offered by libraries, archives and museums (LAMs). The LD catalogues were regarded as qualified subjects if they offered functional features that were distinct from current OPACs and discovery systems through URI-based enrichment and aggregation from various LD sources. In addition to individual organizations, LD union catalogues were also included. However, LD hubs, such as ISNI, OCLC WorldCat Entities, VIAF and Wikidata, were excluded. In total, six LD catalogues from LAMs were selected as subjects for examination.

First, LD catalogues provide similar KG information through URI combination, and KGs also facilitate information serendipity, including social-document, intellectual, conceptual, spatial and temporal contexts and networks of corporate bodies, persons and families (CPFs). Second, LD catalogues have transformed the “seek first and browse later” paradigm into a “seek or browse” paradigm by refreshing the browsing function of traditional card catalogues with preview and new options to facilitate LD identification and discovery. Third, LD catalogues have refined keyword recommendation with the addition of the following fields: person’s title, CPF relationships, entity type and LD source. Lastly, a virtual union LD catalogue is offered.

The proposed checklist revealed the unique/improved functional features of LD catalogues, allowing further investigation and comparison. More cases from the fields of medicine, engineering science and so on will be required to make revisions to fine-tune the proposed checklist approach.

To the best of the author’s knowledge, this is the first study to propose a checklist of functional features for LD catalogues and examine what the results and features of LD catalogues have achieved and are supported by from ontologies across LAMs. The findings suggest that LD provides a viable alternative to catalogues. The proposed checklist and results pave the way for the future development of LD catalogues and next-generation catalogues and also provide a basis for the future study of LD catalogues from other fields to refine the proposed checklist.

Engaging with digital heritage requires understanding not only to comprehend what is simulated but also the reasons leading to its creation and curation, and how to ensure both the digital media and the significance of the cultural heritage it portrays are passed on effectively, meaningfully, and appropriately. The United Nations Educational, Scientific, and Cultural Organization defines ‘digital heritage’ to comprise of computer-based materials of enduring value some of which require active preservation strategies to maintain them for years to come.

With the proliferation of digital technologies and digital media, computer games have increasingly been seen as not only depicters of cultural heritage and platforms for virtual heritage scholarship and dissemination but also as digital cultural artefacts worthy of preservation. In this chapter, we examine how games (both digital and non-digital) can communicate cultural heritage in a galleries, libraries, archives, and museums [GLAM] setting. We also consider how they can and have been used to explore, communicate, and preserve heritage and, in particular, Indigenous heritage. Despite their apparently transient and ephemeral nature, especially compared to conventional media such as books, we argue computer games can be incorporated into active preservation approaches to digital heritage. Indeed, they may be of value to cultural heritage that needs to be not only viewed but also viscerally experienced or otherwise performed.

Social media sites contribute significantly to nature conservation in, that they enlighten and educate those members of the public who would ordinarily not be in a position, or would not be fortunate enough to visit the park and experience the various aspects first-hand. The purpose of this paper is to showcase social media pages related to a national game reserve in South Africa. This game reserve is the largest in the country and has a wide variety of conserved fauna and flora.

The theoretical framework used is the SCOPE framework that streamlines strategy development, content choice, refinement of online engagement, choice of social media platform and evaluations of social media campaigns.

The findings relate to the content found on these social media pages, as well as how members of the public interact with each other and officials from the game reserve in sharing experiences related to this wilderness area.

The research is related to the Kruger National Park in South Africa and is limited to three social media sites.

Through its social media presence, this South African game reserve is able to share experiences from what is effectively a living museum, as well as from its library and archives, with members of the public and allowing individual members to share their encounters with wildlife and their historical memories of this wilderness area.

Archives and records are important resources for individuals, organizations and the country. The academic archives are created and maintained for the effective execution of university educational and corporate functions. The archives management practices in universities are being studied in the developed countries; however, a scarcity of empirical research is observed in the context of developing countries, for instance, Pakistan. Thus, the purpose of this study is to assess the archives management practices performed in the archival units of University of the Punjab (UoP), Lahore, in association with the successful execution of university educational functions.

A structured survey questionnaire was developed to collect responses from the record-keepers and archives monitoring staff using a complete enumerative (census) approach. The collected data were analyzed in SPSS 23.0 in addition to structural equation modeling (SEM) run in AMOS 22v.

The findings of this study revealed an inconsistency regarding the policies and procedures, arrangement and filing records and access and retrieval due to the practice of self-developed procedures in the UoP archival units. Although archives management practices have significant impact on university academic as well as research-related functions, however, there is lack of centralized and standardized practices for archiving records in the UoP. Lack of professional/trained staff and policy document are key limitations in building systematic and standardized archives management system in academic intuitions, particularly in the UoP.

To the best of the authors’ knowledge, this is the first empirical study in Pakistan that has explored archives management practices used in university archives. It also contributes theoretically and methodologically through the underpinnings of archival principles in association with university functions and developing a validated scale to explore archives management practices in universities. The findings of this study may be helpful for the concerned bodies, university administrations and archives managers to establish, manage and improve the academic archives systematically.

Despite ongoing research into archival metadata standards, digital archives are unable to effectively represent records in their appropriate contexts. This study aims to propose a knowledge graph that depicts the diverse relationships between heterogeneous digital archive entities.

This study introduces and describes a method for applying knowledge graphs to digital archives in a step-by-step manner. It examines archival metadata standards, such as Records in Context Ontology (RiC-O), for characterising digital records; explains the process of data refinement, enrichment and reconciliation with examples; and demonstrates the use of knowledge graphs constructed using semantic queries.

This study introduced the 97imf.kr archive as a knowledge graph, enabling meaningful exploration of relationships within the archive’s records. This approach facilitated comprehensive record descriptions about different record entities. Applying archival ontologies with general-purpose vocabularies to digital records was advised to enhance metadata coherence and semantic search.

Most digital archives serviced in Korea are limited in the proper use of archival metadata standards. The contribution of this study is to propose a practical application of knowledge graph technology for linking and exploring digital records. This study details the process of collecting raw data on archives, data preprocessing and data enrichment, and demonstrates how to build a knowledge graph connected to external data. In particular, the knowledge graph of RiC-O vocabulary, Wikidata and Schema.org vocabulary and the semantic query using it can be applied to supplement keyword search in conventional digital archives.

Despite being an authentic carrier of various cultural practices, the human body is often underutilised to access the knowledge of human body. Digital inventions today have created new avenues to open up cultural data resources, yet mainly as apparatuses for well-annotated and object-based collections. Hence, there is a pressing need for empowering the representation of intangible expressions, particularly embodied knowledge within its cultural context. To address this issue, the authors propose to inspect the potential of machine learning methods to enhance archival knowledge interaction with intangible cultural heritage (ICH) materials.

This research adopts a novel approach by combining movement computing with knowledge-specific modelling to support retrieving through embodied cues, which is applied to a multimodal archive documenting the cultural heritage (CH) of Southern Chinese martial arts.

Through experimenting with a retrieval engine implemented using the Hong Kong Martial Arts Living Archive (HKMALA) datasets, this work validated the effectiveness of the developed approach in multimodal content retrieval and highlighted the potential for the multimodal's application in facilitating archival exploration and knowledge discoverability.

This work takes a knowledge-specific approach to invent an intelligent encoding approach through a deep-learning workflow. This article underlines that the convergence of algorithmic reckoning and content-centred design holds promise for transforming the paradigm of archival interaction, thereby augmenting knowledge transmission via more accessible CH materials.

Records are current documents containing crucial personal, legal, financial and medical information, while archives house non-current documents with the same details. This study specifically aims to measure existing research in records and archives management with various scientific indicators.

Data extraction was conducted using the Web of Science, resulting in a data set of 2003 records for further analysis. Biblioshiny and VOSviewer have been used for mapping and visualization of the extracted data.

Managing and organizing this essential information is equally vital to maintaining records and archives. The findings encompass various aspects such as publications and citations, influential authors, source impact factors, relevant articles, affiliations, co-authorship trends across the top 10 countries and regions, references, publication year spectroscopy, keyword co-occurrence and historiography. The study concludes that medical records management prominently dominates the selected research area.

The study reflects the advancements in management systems and continues to emerge as research on the management of records and archives has gained significance.

Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between resources. Therefore, this study aims to propose a multidimensional knowledge discovery solution for Tang tomb mural cultural relic resources.

Taking the Tang tomb murals collected by the Shaanxi History Museum as an example, based on clarifying the relevant concepts of Tang tomb mural resources and considering both dynamic and static dimensions, a top-down approach was adopted to first construct an ontology model of Tang tomb mural type cultural relics resources. Then, the actual case data was imported into the Neo4J graph database according to the defined pattern hierarchy to complete the static organization of knowledge, and presented in a multimodal form in knowledge reasoning and retrieval. In addition, geographic information system (GIS) technology is used to dynamically display the spatiotemporal distribution of Tang tomb mural resources, and the distribution trend is analysed from a digital humanistic perspective.

The multi-dimensional knowledge discovery of Tang tomb mural cultural relics resources can help establish the correlation and spatiotemporal relationship between resources, providing support for semantic retrieval and navigation, knowledge discovery and visualization and so on.

This study takes the murals in the collection of the Shaanxi History Museum as an example, revealing potential knowledge associations in a static and intelligent way, achieving knowledge discovery and management of Tang tomb murals, and dynamically presents the spatial distribution of Tang tomb murals through GIS technology, meeting the knowledge presentation needs of different users and opening up new ideas for the study of Tang tomb murals.