Volume 54, Issue 3

The article discusses the reality of information for archivists in an era when information is not primarily shaped in documentary form. The situation in which contemporary administrative, business, and private information is organized in various formats necessitates a reexamination of the subject of archival science and practice. The author focuses on the ontology of the new professional standard, Records in Contexts, using it to redefine essential professional concepts and develop archival descriptions. As it relies on Description Logics, Records in Contexts introduces two new functions in addition to the existing functions. The author presents the first, terminology and discourse-related function by disassembling archival terminology into simpler, more straightforward concepts or their constituents, and analyzing them through the lenses of Description Logics. This function acknowledges today’s new reality, where information is spread in more forms than just documents. The second function is related to a Description Logics reasoning engine that supports the RiC ontology, allowing for the creation of information that does not need to be anticipated by archivists. This liberates archivists from the Schellenbergian illusion of anticipating users’ needs. The article offers an example of a practical exercise for students in archival science, showing how description is powerful when formatted as data according to the new standard. The two functions discussed are interconnected, and a comprehensive approach would have archivists manage all types of information and organize their output more semantically. The conclusion indicates such a direction, a broader application of the new archival standard compared to the previous one.

Podcasts are a digital technology that librarians and historians can leverage to share content from their archival collections with users who may not otherwise have access. In addition to the preservation and dissemination of oral history transcripts and audio files within a library collection, this pilot research project added a novel outreach dimension through podcasting. Unedited oral history audio of rock climbers and mountaineers from two digital library collections were published to a podcast, Ascent Archive . This study evaluates whether people would listen to full-length oral history interviews and if the podcast would increase access to the corresponding digital library item and the entire oral history collection. Usage data from Simplecast, the chosen podcast hosting, distribution, and analytics platform, and the University of Utah’s (USA) digital library were analyzed. The Ascent Archive podcast had over 1,670 downloads with over 815 unique listeners from around the world, with 90 % in the United States. The Simplecast and digital library analytics data suggest that a podcast episode increases use of the corresponding digital library item but not the remainder of the collection. This is the first study to investigate and analyze the data from both a podcast and corresponding digital library collections. This study demonstrates a new outreach strategy to expand access to oral histories while meeting modern listening expectations.

Batik, a traditional textile art form, holds profound cultural and historical value in Indonesia, where its motifs are rich in symbolic meaning. As efforts to digitally preserve batik grow, there is an increasing need for accurate and scalable classification methods to analyze its intricate patterns. Manual classification remains labor-intensive and prone to subjectivity. This study investigates the use of machine learning and computer vision techniques to automate batik motif classification. By leveraging deep feature extraction through the VGG16 architecture and integrating it with machine learning classifiers such as Support Vector Machines (SVM), Multi-Layer Perceptron (MLP), Convolutional Neural Networks (CNN), and XGBoost, the study aims to improve classification performance. Experimental results demonstrate that the VGG16+XGBoost model achieves the highest performance with an average accuracy of 89.83 % across five-fold cross-validation, outperforming standalone models including SVM (64.29 %), CNN (65.76 %), and XGBoost without deep features (64.87 %). Meanwhile, the retrained VGG16 model attained an accuracy of 87.77 %, confirming the benefit of combining deep and traditional learning approaches. These findings highlight the effectiveness of deep feature extraction in capturing the fine-grained textures of batik motifs and demonstrate the potential of such hybrid approaches in supporting the digital preservation and classification of traditional cultural artifacts.

The relevance of this study is driven by the rapid development of artificial intelligence (AI) in the creative industries, particularly in the creation and editing of audiovisual content, necessitating a reassessment of its impact on the technological and ethical aspects of this field. The objective of the study was to analyze the key opportunities and challenges of using AI in audiovisual content production, as well as to outline recommendations for mitigating associated risks. The research was based on a review and comparative analysis of contemporary scientific studies. The findings demonstrated that AI enables significant reductions in production time and costs through the automation of routine tasks such as editing, video correction, and animation creation. Generative models, particularly generative adversarial networks (GANs), open new possibilities for creating realistic visual effects and three-dimensional objects that previously required considerable effort and resources. Deep learning algorithms improve the quality of sound and image, restore old materials, and adapt content for different target audiences through personalisation. However, certain risks have been identified, including content standardisation, threats of disinformation due to the spread of deepfake technologies, and copyright infringements. Thus, the study confirmed that the integration of AI into the audiovisual sector has a substantial impact and future potential for optimising production processes, yet it requires consideration of socio-ethical aspects.

Odisha, a state located in Eastern India, is renowned for its unique and indigenous folk performances. These performances are not merely sources of entertainment but repositories of the region’s culture, tradition, and heritage. Recognizing their culture significance, individuals and communities have taken initiatives to promote and preserve them through the social media platforms. Our article explores selected social media handles across three platforms, namely, YouTube, Facebook, and Instagram, to examine their role in preserving and promoting seven folk performances of Odisha: Odissi , Pala , Gotipua , Kandhei Nacha , Chaiti Ghoda , Ranapa , and Dasakathia . Through a qualitative content analysis of the selected social media handles and their content on folk performances, the study reveals that Odissi and Pala have strong visibility and engagement on social media, while the other five performances –  Gotipua , Kandhei Nacha , Chaiti Ghoda , Ranapa , and Dasakathia – have limited presence due to a decline in their physical practice and performances. Among the platforms, YouTube emerges as the most active in terms of documentation and promotion, while Facebook and Instagram demonstrated relatively lower engagement. Furthermore, the study finds that although these platforms offer numerous features, many of these are not actively utilized by the reviewed accounts. This paper offers recommendations for a more systematic and strategic use of digital media to ensure the long-term visibility and sustainability of these folk performances. This research contributes to the fields of folklore study, cultural studies, and media studies by highlighting the potential of digital platforms in promoting and preserving regional cultural assets in a rapidly evolving digital age.

Since March 2022 Saving Ukrainian Cultural Heritage Online (SUCHO) has preserved over 5,400 websites and more than 50 TB of data, creating secure backups outside Ukraine and facilitating future digital repatriation to Ukrainian institutions. The grassroots initiative stands out for its rapid mobilization, its scale, and innovative approach to safeguarding digital cultural heritage under threat. Its achievements include the preservation of vast amounts of digital material, empowerment and fostering of digitalization in Ukraine. SUCHO also highlighted the necessity of preemptive, distributed backups of digital heritage worldwide.

The cultural heritage, preservation, and academic sectors worldwide are facing an unprecedented crisis characterized by systematic budget cuts, staff reductions, project cancellations, and threats to scholarly freedom. This position paper, based on responses from Editorial Board members representing institutions across the United States, Europe, and Australia, documents the scope and severity of these challenges while highlighting the urgent need for coordinated international action.