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Digital preservation inherently involves multigenerational projects, necessitating consideration of intergenerational justice. However, there have been few discussions about this topic in the field of digital preservation. This study aimed to lay the groundwork for future theoretical research by investigating the concept of generativity proposed by Erikson. It specifically investigates the factors that influence individuals’ willingness to donate personal photographs to preservation institutions, with a particular focus on generativity. The results indicate that, while shared and loss experiences have a greater influence, generativity also has a significant impact on individuals’ attitudes towards photo donation. The results suggest that an intergenerational perspective is indeed applicable and valuable for digital preservation. [ABSTRACT FROM AUTHOR]

The fine-grained mining and construction of semantic associations within multimodal intangible cultural heritage (ICH) resources are crucial for deepening our understanding of their knowledge content and ensuring their systematic protection and transmission in the digital and intelligent era. This paper addresses the urgent need for the digital preservation and transmission of ICH resources. Following a review of current research on Qingyang sachets and ICH, the study introduces an ontology-based approach to constructing a semantic description model for the multimodal digital resources related to Qingyang sachets. By acquiring and processing multimodal resources concerning the craftsmanship and associated customs of Qingyang sachets, the study reorganizes the corresponding textual and visual knowledge. Utilizing knowledge graphs, the research explores multidimensional pathways for delivering knowledge services related to the multimodal digital resources of Qingyang sachets. Empirical research confirms the applicability and feasibility of the proposed semantic association scheme for multimodal ICH digital resources. The findings provide valuable insights for multidimensional organization and integration across scenarios, time periods, and resources within the ICH domain, offering a reference for digital solutions aimed at the systematic protection of ICH. [ABSTRACT FROM AUTHOR]

This study introduces a design transformation model for AI-generated Chinese traditional architectural images (SD Lora&Canny) based on Stable Diffusion (SD). By integrating parameterization techniques such as Low-Rank Adaptation (Lora) and edge detection algorithms (Canny), the model achieves precise restoration of the architectural form, color elements, and decorative symbols in Chinese traditional architecture. Using the Beijing Drum Tower as the experimental subject, statistical analysis software (SPSS V28.0) was employed to conduct a quantitative evaluation and comparative analysis of architectural images generated by the DALL-E, MidJourney, SD, and SD Lora&Canny models. The results demonstrate that the SD Lora&Canny model significantly outperforms traditional generation tools in restoration accuracy and visual fidelity. Finally, this study applied the SD Lora&Canny model to create the digital cultural product AR Drum and Bell Tower Fridge Magnet, showcasing its practical application in digital cultural creation and verifying its innovative potential in the digital preservation and transmission of Chinese traditional architecture. [ABSTRACT FROM AUTHOR]

This study aims to investigate the key factors influencing user experience in the design of virtual interactive platforms for the preservation of industrial heritage within the context of digitalization. In the literature review, this paper introduces a theoretical model comprising five latent variables: cultural identity, functional clarity, scenario interactivity, narrative quality, and user experience. To construct and validate the model, the author employed structural equation modeling (SEM) to analyze data from 323 valid questionnaires collected in China. The validation of the SEM model led to conclusions regarding the impact of each latent variable on user experience. The results indicate that cultural identity, functional clarity, scene interactivity, and narrative quality significantly affect user experience and play a critical role in enhancing user experience on virtual platforms. To validate this theoretical framework, the study employs the virtual interactive platform of Hanyang Ironworks as a case study, examining how these factors manifest in practical scenarios and their specific impact on platform design. The findings reveal that a strong sense of cultural identity, clear functional design, interactive scenes, and a well-structured narrative are the core factors that enhance user experience on virtual industrial heritage platforms. This research provides both theoretical support for the digital preservation of industrial heritage and practical insights for the design of virtual platforms. The study improves virtual interactions with industrial heritage and informs future research and applications. [ABSTRACT FROM AUTHOR]

Multistage text-to-image generation algorithms have shown remarkable success. However, the images produced often lack detail and suffer from feature loss. This is because these methods mainly focus on extracting features from images and text, using only conventional residual blocks for post-extraction feature processing. This results in the loss of features, greatly reducing the quality of the generated images and necessitating more resources for feature calculation, which will severely limit the use and application of optical devices such as cameras and smartphones. To address these issues, the novel High-Detail Feature-Preserving Network (HDFpNet) is proposed to effectively generate high-quality, near-realistic images from text descriptions. The initial text-to-image generation (iT2IG) module is used to generate initial feature maps to avoid feature loss. Next, the fast excitation-and-squeeze feature extraction (FESFE) module is proposed to recursively generate high-detail and feature-preserving images with lower computational costs through three steps: channel excitation (CE), fast feature extraction (FFE), and channel squeeze (CS). Finally, the channel attention (CA) mechanism further enriches the feature details. Compared with the state of the art, experimental results obtained on the CUB-Bird and MS-COCO datasets demonstrate that the proposed HDFpNet achieves better performance and visual presentation, especially regarding high-detail images and feature preservation. [ABSTRACT FROM AUTHOR]

Ancient murals, as invaluable cultural artifacts, have profound historical and cultural significance. However, these murals often face degradation phenomena such as peeling, fading, and cracking, which compromises their preservation. Conventional methodologies for protection and restoration exhibit limitations and do not adequately address multifaceted damage conditions, thus necessitating the integration of advanced technological interventions to enhance restoration effectiveness.This paper delineates a framework for the preservation and restoration of cultural heritage buildings that uses Internet of Things (IoT) technology and Artificial Intelligence (AI). Using real-time environmental and structural health surveillance, in conjunction with security mechanisms, this framework markedly improves precision and efficiency in forecasting and identifying potential risks.Furthermore, in the context of mural restoration, this paper introduces the ArtDiff model. This model amalgamates a modified U-Net for initial crack detection with an edge-guided restoration technique, employing a diffusion model for meticulous restoration. Empirical results substantiate the superiority of the ArtDiff model in crack detection and mural restoration, delivering a greater precision and efficacy relative to existing approaches. Through the implementation of multilevel supervision strategies and an avant-garde model architecture, this study offers a sophisticated mural restoration solution, furnishing novel technological support for the preservation of cultural heritage. [ABSTRACT FROM AUTHOR]

The paper explores two fortified systems, as case studies, to evaluate different modelling approaches, the parameterisation of architectural components, and semantic interpretation, to define a repeatable methodology for classifying, accessing, and sharing architectural information. The use of informational structures to categorise data and relations through semantic attributes addresses the need to make data queryable and interoperable. In architectural documentation, this practice opens up new perspectives for creating and sharing collaborative repositories, radically transforming the way of disseminating and accessing knowledge. Linking qualitative data information with 3D models enables the development of semantic structures that provide a deeper understanding of intrinsic characteristics, historical transformations of architectural complexes, and their cultural context. While databases effectively manage structured information and relationships between different signifiers, semantically enriched 3D modelling, through the management of surfaces or parameters, offers an accurate and flexible representation of each component. The evaluation of these case studies not only improves the ability to understand and appreciate built heritage but also provides new opportunities for researchers in architectural documentation and history. Semantic subdivision processes of built complexes into individual components facilitate the analysis and the digital preservation of heritage, enabling more precise interpretations and faithful reconstructions. [ABSTRACT FROM AUTHOR]

This paper tackles the challenge of accurately segmenting images of Ming-style furniture, an important aspect of China's cultural heritage, to aid in its preservation and analysis. Existing vision foundation models, like the segment anything model (SAM), struggle with the complex structures of Ming furniture due to the need for manual prompts and imprecise segmentation outputs. To address these limitations, we introduce two key innovations: the material attribute prompter (MAP), which automatically generates prompts based on the furniture's material properties, and the structure refinement module (SRM), which enhances segmentation by combining high- and low-level features. Additionally, we present the MF2K dataset, which includes 2073 images annotated with pixel-level masks across eight materials and environments. Our experiments demonstrate that the proposed method significantly improves the segmentation accuracy, outperforming state-of-the-art models in terms of the mean intersection over union (mIoU). Ablation studies highlight the contributions of the MAP and SRM to both the performance and computational efficiency. This work offers a powerful automated solution for segmenting intricate furniture structures, facilitating digital preservation and in-depth analysis of Ming-style furniture. [ABSTRACT FROM AUTHOR]

The Xiaohualou loom for Song brocade as a typical representative of ancient Chinese pattern-weaving looms with harnesses carries rich historical cultural and artistic value. It is not only part of China's textile cultural heritage but its manufacturing and weaving techniques are also precious intangible cultural heritage of China. With the acceleration of modernization the protection of the Song brocade Xiaohualou loom and its manufacturing and weaving techniques face severe challenges. Currently research on the loom mainly focuses on literature records and physical preservation lacking systematic digital restoration studies which limits its digital inheritance and protection. Traditional preservation methods while able to retain some information about the loom cannot fully reproduce its complex structure and the manufacturing and weaving processes. Modern digital image processing technology has improved the current situation to some extent but still falls short in dynamically simulating the weaving process and displaying fabric effects. Therefore to better achieve digital preservation and dissemination of the Song brocade Xiaohualou loom and its manufacturing and weaving techniques a digital virtual restoration method based on three-dimensional modeling technology was proposed. First field survey methods were employed to measure various data of the Song brocade Xiaohualou loom and AUTO CAD software was utilized to draw its form structure and linkage mechanism. Next Autodesk 3dsmax three-dimensional modeling technology was used for digital modeling of the loom and digital dynamic restoration of its manufacturing and weaving processes. Subsequently VRay software was employed for material and scene rendering of the restored loom to enhance visual effects and realism. Finally a comprehensive evaluation of the digital restoration results was conducted using a combination of AHP hierarchical analysis and fuzzy comprehensive evaluation methods. The digital dynamic restoration of the Song brocade Xiaohualou loom and its manufacturing and weaving techniques based on 3D technology can effectively address the challenges of digital preservation of cultural relics and the dissemination of ancient loom manufacturing and traditional weaving techniques. This method not only preserves precious cultural heritage but also showcases the essence of ancient weaving craftsmanship in a vivid and intuitive manner allowing more people to understand and appreciate this traditional skill. Experimental results show that the membership degree of "very poor" poor "average" good and "very good" for the digital restoration of the Song brocade Xiaohualou loom is 5. 1% 4. 6% 16. 3% 38. 1% and 35. 8% respectively. According to the maximum membership principle the digital restoration effect of the Song brocade Xiaohualou loom is "good". This result indicates that the method has achieved significant success in restoring the loom providing valuable reference for future digital preservation work of similar cultural relics. The digital restoration method presented in this paper can effectively complete high-precision digital restoration of the Song brocade Xiaohualou loom while also more accurately reproducing the dynamic display of the loom and its manufacturing and weaving processes further proving the reliability of this method. The digitally restored Song brocade Xiaohualou loom presents a novel approach to the preservation and exhibition of traditional ancient looms enabling the dissemination of their historical cultural and artistic value through more diverse channels. The research outcome will not only contribute to improving the quality of digital restoration of traditional ancient looms but also offer a referenceable technical roadmap for their digital reconstruction. [ABSTRACT FROM AUTHOR]

For the long-term preservation of the digital records created in organizations that have archival value, digital preservation techniques are used. These techniques also contribute to the preservation of the trustworthiness of the records. In order to assess the situation of organizations in the implementation of their digital preservation activities, there is a need for an analysis tool. Many models have been prepared to meet this need. One is the Levels of Preservation (LoP) developed by the National Digital Stewardship Alliance (NDSA). The LoP provides guidance to organizations in their digital preservation activities. Therefore, it is thought that the LoP can be associated with trustworthiness which aims at long-term preservation of the records. This study examines the levels of digital preservation specified in the LoP in terms of the trustworthiness of digital records. As a result of this research, the goal is to address theoretically how the trustworthiness of digital records can be preserved through the LoP. Consequently, it is feasible for organizations to align their digital preservation capabilities with trustworthiness. The study has revealed that the LoP can be employed in the analysis of the trustworthiness of the records. [ABSTRACT FROM AUTHOR]

Purpose: In South Africa, public institutions face challenges in transitioning their digital records to trusted digital repositories due to a deficiency in skills, infrastructure and systems. Free and open-source software (FOSS) presents a viable solution for facilitating the transfer of digital archives for permanent preservation. Despite the existence of FOSS policy in South Africa, the public sector has yet to fully use it to engage in the development and implementation of products for records management and archive preservation using open-source software. This study aims to explore the ingestion of digital archives into an approved long-term storage system through FOSS in South Africa with the view of developing a framework. Design/methodology/approach: The study adopted a qualitative research approach to collect data through interviews with purposively selected participants (records managers, archivists and IT officials) from national government departments that have implemented records management systems for digital curation of archives, as well as the National Archives and Records Services of South Africa (NARSSA), which regulates archives and records management, and the State Information Technology Agency, which regulates information technology in government. Findings: The findings of the study suggest that the systematic transfer of digital materials from public entities to NARSSA, as required by statute, has not taken place. Research limitations/implications: The study specifically targeted national government departments that have implemented digital archives and records management systems. Consequently, perspectives from departments that have not implemented these solutions were excluded. Originality/value: A framework is proposed for the transfer of digital archives, using interoperable FOSS, from government agencies responsible for records management to NARSSA for archival preservation. This framework, it is hoped, will facilitate infrastructure and skills development in the management of records and preservation of archives through open platforms. [ABSTRACT FROM AUTHOR]

We investigate in this article how repository platforms change the sharing and preservation of digital objects in academic libraries. We use evidence drawn from semi-structured interviews with 31 data repository managers working at 21 universities using the product Figshare for institutions. We first show that repository managers use this platform to bring together actors, technologies, and processes usually scattered across the library to assign to them the tasks that they value less—such as data preparation or IT maintenance—and spend more time engaging in activities they appreciate—such as raising awareness of data sharing. While this platformization of data management improves their job satisfaction, we reveal how it simultaneously accentuates the outsourcing of libraries' core mission to private actors. We eventually discuss how this platformization can deskill librarians and perpetuate precarity politics in university libraries. [ABSTRACT FROM AUTHOR]

This paper addresses the preservation approach chosen for a selected group of born-digital artworks connected to the web, here categorized under the term internet art. The three first cases that are part of the project Infrastructuur Duurzame Toegankelijkheid Digitale Kunst (Collaborative Infrastructure for Sustainable Access to Digital Art) researched by LIMA (a platform for media art based in Amsterdam) focused on how to analyse internet artworks. This case study-based research was conducted in collaboration with 16 collecting institutions based in The Netherlands. The growing number of internet artworks in collections has pushed the development of preservation initiatives that consider these works' fleeting nature, a consequence of their technical build and time-sensitive characteristics. The project aims to produce and share knowledge for these artworks' preservation and overall sustainability while making it available for other similar works. This paper addresses the research steps while assessing its rationale and utility. It starts by describing the case study and assesses how the methodology serves conservation standards. The paper documents an overall evaluation of methods and results, pointing out the applicability and practical relevance of this initiative, here evaluated with positive conclusions. This paper fits the project's mission concerning knowledge sharing and raising awareness for the preservation of internet artworks and is authored by a short-term PhD fellow at LIMA. [ABSTRACT FROM AUTHOR]

Copyright of Arab International Journal of Information Technology & Data is the property of Arab Institution of Knowledge Management and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, deep-network-based hashing has gained prominence in image retrieval for its ability to generate compact and efficient binary representations. However, most existing methods predominantly focus on high-level semantic features extracted from the final layers of networks, often neglecting structural details that are crucial for capturing spatial relationships within images. Achieving a balance between preserving structural information and maximizing retrieval accuracy is the key to effective image hashing and retrieval. To address this challenge, we introduce Multiscale Deep Feature Fusion for Supervised Hashing (MDFF-SH), a novel approach that integrates multiscale feature fusion into the hashing process. The hallmark of MDFF-SH lies in its ability to combine low-level structural features with high-level semantic context, synthesizing robust and compact hash codes. By leveraging multiscale features from multiple convolutional layers, MDFF-SH ensures the preservation of fine-grained image details while maintaining global semantic integrity, achieving a harmonious balance that enhances retrieval precision and recall. Our approach demonstrated a superior performance on benchmark datasets, achieving significant gains in the Mean Average Precision (MAP) compared with the state-of-the-art methods: 9.5% on CIFAR-10, 5% on NUS-WIDE, and 11.5% on MS-COCO. These results highlight the effectiveness of MDFF-SH in bridging structural and semantic information, setting a new standard for high-precision image retrieval through multiscale feature fusion. [ABSTRACT FROM AUTHOR]

The main objective of this study is to reduce CO2 emissions resulting from rapidly increasing cement production and utilization rates worldwide. For this purpose, the effects of NS (nano-silica) and SF (silica fume) materials, which are the post-production wastes of industrial products, the substitute material obtained by grinding SG (silica gel) wastes used for packaging purposes in the preservation of industrial electronic products and many other areas, and MLS (micritic limestone) obtained by grinding limestone, a natural resource, on mortars after cement substitutions were evaluated. MLS and SG contents were sieved through a 0.063 mm sieve and substituted into the mixtures, while specific surface area values for SF and NS were obtained as 23 m2/g and 150 m2/g. Each of these materials was used in mortars by substituting between 0% and 10% cement by weight. The samples were subjected to consistency determination and then evaluated for setting time. Subsequently, flexural tests were carried out on 40 mm × 40 mm × 160 mm specimens placed in molds, and compressive tests were carried out on prism fragments broken after flexural tests. The experimental results showed that substitution of SG substitutes with cement at 3–10 wt% was highly effective against SF, NS and MLS in terms of strength and workability properties. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Arqueologia is the property of Revista de Arqueologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study presents the implementation of an AI-based prototype for recognizing Korean traditional dance movements using a metadata-enhanced dataset. The research was conducted in three stages. First, a classification framework was developed to reflect the unique characteristics of Korean traditional dance. Second, video data were collected from existing and newly filmed sources, and a metadata set was created by labeling five fundamental movements for training. Third, the BlazePose model was applied to generate real-time skeletal key points, which were integrated with the metadata-enhanced dataset and processed using a customized approach to recognize dance movements in real time. The developed prototype successfully recognizes five fundamental Korean traditional dance movements and demonstrates the potential of AI technology in analyzing complex motion patterns. By integrating existing AI models with a domain-specific dataset, this study provides a systematic approach to the digital preservation and modern reinterpretation of traditional arts. Furthermore, the methodology can be extended to recognize dance movements from other cultures, offering new possibilities for the preservation and transmission of intangible cultural heritage through digital technology. [ABSTRACT FROM AUTHOR]

This article explores recent advancements in non-destructive spectroscopic techniques for identifying pigments in polychrome cultural relics, emphasizing their significance for sustainability in cultural heritage preservation. Techniques such as infrared spectroscopy, Raman spectroscopy, and X-ray fluorescence spectroscopy facilitate the accurate identification of pigment compositions while ensuring the integrity of the artifacts is maintained. Our findings indicate that integrating multiple spectroscopic methods enhances the accuracy of pigment identification and deepens our understanding of the structural and preservation status of historical artifacts. We also outline future directions for spectroscopic analysis in the field of cultural heritage, including micro-area analysis, data fusion, and intelligent data processing, aimed at improving the efficiency and effectiveness of pigment identification, ultimately contributing to the sustainable preservation of cultural assets. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Contemporary Humanities & Educational Science is the property of International Journal of Contemporary Humanities & Educational Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The notion ‘Convexity’ is applied in various areas of mathematics particularly in optimization techniques. It is known that this concept is applied in fuzzy sets, which is studied by many authors. This article deals with convexity utilized for neutrosophic and interval valued neutrosophic sets which is a generalization of intuitionistic fuzzy sets. Also some interesting preservation properties of convexity under intersection operators in interval valued neutrosophic sets are discussed. Adding to the discussion, preservation property of digital convexity under intersection using deformation and other techniques are touched upon. Eventually the application of convexity to decision making are illustrated using examples. [ABSTRACT FROM AUTHOR]

Knowledge about seafloor depth, or bathymetry, is crucial for various marine activities, including scientific research, offshore industry, safety of navigation, and ocean exploration. Mapping the central Arctic Ocean is challenging due to the presence of perennial sea ice, which limits data collection to icebreakers, submarines, and drifting ice stations. The International Bathymetric Chart of the Arctic Ocean (IBCAO) was initiated in 1997 with the goal of updating the Arctic Ocean bathymetric portrayal. The project team has since released four versions, each improving resolution and accuracy. Here, we present IBCAO Version 5.0, which offers a resolution four times as high as Version 4.0, with 100 × 100 m grid cells compared to 200 × 200 m. Over 25% of the Arctic Ocean is now mapped with individual depth soundings, based on a criterion that considers water depth. Version 5.0 also represents significant advancements in data compilation and computing techniques. Despite these improvements, challenges such as sea-ice cover and political dynamics still hinder comprehensive mapping. Measurement(s) Depth Technology Type(s) Digital curation Factor Type(s) Geographic location Sample Characteristic - Environment Ocean floor Sample Characteristic - Location Arctic Ocean [ABSTRACT FROM AUTHOR]

Background: Adults classified as immunosuppressed have been disproportionately affected by the COVID-19 pandemic. Compared to the immunocompetent, certain patients are at increased risk of suboptimal vaccine response and adverse health outcomes if infected. However, there has been insufficient work to pinpoint where these risks concentrate within the immunosuppressed spectrum; surveillance efforts typically treat the immunosuppressed as a single entity, leading to wide confidence intervals. A clinically meaningful and computerised medical record (CMR) compatible method to subdivide immunosuppressed COVID-19 data is urgently needed. Methods: We conducted a rapid scoping review into COVID-19 mortality across UK immunosuppressed categories to assess if differential mortality risk was a viable means of subdivision. We converted the risk hierarchy that surfaced into a pilot digital phenotype—a valueset and series of ontological rules ready to extract immunosuppressed patients from CMR data and stratify outcomes of interest in COVID-19 surveillance dataflows. Results: The rapid scoping review returned COVID-19 mortality data for all immunosuppressed subgroups assessed and revealed significant heterogeneity across the spectrum. There was a clear distinction between heightened COVID-19 mortality in haematological malignancy and transplant patients and mortality that approached the immunocompetent baseline amongst cancer therapy recipients, autoimmune patients, and those with HIV. This process, complemented by expert clinical input, informed the curation of the five-part digital phenotype now ready for testing in real-world data; its ontological rules will enable mutually exclusive, hierarchical extraction with nuanced time and treatment conditions. Unique categorisations have been introduced, including 'Bone Marrow Compromised' and those dedicated to differentiating prescriptions related and unrelated to cancer. Codification was supported by existing reference sets of medical codes; absent or redundant codes had to be resolved manually. Discussion: Although this work is in its earliest phases, the development process we report has been highly informative. Systematic review, clinical consensus building, and implementation studies will test the validity of our results and address criticisms of the rapid scoping exercise they are predicated on. Conclusion: Comprehensive testing for COVID-19 has differentiated mortality risks across the immunosuppressed spectrum. This risk hierarchy has been codified into a digital phenotype for differentiated COVID-19 surveillance; this marks a step towards the needs-based management of these patients that is urgently required. [ABSTRACT FROM AUTHOR]

With the development of society, modern design elements are increasingly integrated into traditional garden design, forming a novel style fusion that improves both aesthetics and the sustainability of the social-ecological system. This study explores the application of style transfer algorithms to seamlessly integrate the aesthetics of traditional landscape paintings with virtual scenes of classical private gardens. The effectiveness of the method is verified through a series of experiments using virtual scenes of the Humble Administrator's Garden and various landscape paintings representing different artistic styles. The experimental results demonstrate that the style transfer technique can accurately replicate the aesthetic features of traditional paintings and integrate them into the virtual garden environment. This approach highlights the potential of combining cultural heritage with advanced technological methods, indicating that the technology has great potential to innovate garden design by promoting the synergy between cultural heritage and technological innovation. By promoting the integration of traditional aesthetics and modern design principles, we contribute to the sustainability and richness of the social-ecological system and provide a framework for future digital preservation and restoration applications of urban cultural heritage. The code for implementing TRD-Net is available at https://github.com/huangbei029/Hybrid-Garden-StyleNet-dd/tree/main. [ABSTRACT FROM AUTHOR]

Ancient murals, invaluable cultural artifacts, frequently suffer damage from environmental and human factors, necessitating effective restoration techniques. Traditional methods, which rely on manual skills, are time-consuming and often inconsistent. This study introduces an innovative mural restoration approach using a generative adversarial network (GAN) within a UNet architecture. The generator integrates Transformer and convolutional neural network (CNN) components, effectively capturing and reconstructing complex mural features. This work's novelty lies in integrating the Group-wise Multi-scale Self-Attention (GMSA), an Encoder-Decoder Feature Interaction (EDFI) module, and a Local Feature Enhancement Block (LFEB). These components allow the model to better capture, reconstruct, and enhance mural features, leading to a significant improvement over traditional restoration methods. Tested on a dataset of Tang Dynasty murals, the method demonstrated superior performance in PSNR, SSIM, and LPIPS metrics compared to seven other techniques. Ablation studies confirmed the effectiveness of the heterogeneous network design and the critical contributions of the GMSA, EDFI, and LFEB modules. Practical restoration experiments showed the method's ability to handle various types of mural damage, providing seamless and visually authentic restorations. This novel approach offers a promising solution for the digital preservation and restoration of cultural heritage murals, with potential applications in practical restoration projects. [ABSTRACT FROM AUTHOR]

Every five to seven years, the Intergovernmental Panel on Climate Change (IPCC) convenes the climate science community to assess the latest knowledge on climate change relevant to policy-makers. This generally takes the form of Assessment Reports (AR) covering the scientific basis of climate change, its impacts and future risks, and options for adaptation and mitigation. With each cycle, these reports have grown in scope, length, number of referenced papers, and underpinning datasets. During the sixth assessment cycle, a large-scale collective effort went into archiving digital products assessed and generated through the IPCC process. The main objectives driving this initiative are making IPCC's work more transparent, improving the reproducibility and reusability of the assessment outcomes, better utilization of the services of the IPCC Data Distribution Centre (DDC), and, more generally, compliance with best practices in open science. This paper expands on the motivations for the curation and preservation of digital objects in the IPCC. It gives an overview of how FAIR (Findable, Accessible, Interoperable, Reusable) and open data principles have been implemented in practice and explores some of the successes and setbacks of the AR6 experience. It concludes with recommendations for consolidation and expansion of the approach for AR7. These include a tighter integration of digital curation activities in the IPCC timeline and workflows, better support of IPCC authors and contributors through early training and use of suitable software, improved standardization and harmonization of data and software handling across Working Groups (WGs), and close collaboration with key external data providers and research organizations. [ABSTRACT FROM AUTHOR]

The concept of electronic evidence is one of the most fundamental categories in the administrative process. After all, the ability to use and evaluate them in the process of establishing the truth depends on the correct understanding of this concept. Evaluation of electronic evidence is a mental and procedural activity of the court and participants in an administrative case aimed at forming a final conclusion on the confirmation or refutation of the facts to be proved with the help of electronic evidence. The court's activities in assessing electronic evidence include a number of specific steps and actions aimed at the correct resolution of the dispute in accordance with the princi ples of administrative proceedings. The current Code of Administrative Procedure of Ukraine provides for the procedure for the evaluation of evidence by the court, but to date, the scientific doctrine and practice do not address the question of what criteria for evaluating evidence should be applied to electronic evidence. The Guidelines "Electronic Evidence in Civil and Administrative Proceedings" adopted by the Committee of Ministers of the Council of Europe on January 30, 2019, state that electronic evidence should be evaluated in the same way as other types of evidence, in particular with regard to its admissibility, authenticity, accuracy and integrity. Based on the analysis of the current legislation of Ukraine, the said Guidelines and case law, the author of the article reveals the essence of four key criteria of electronic evidence: reliability, relevance, admissibility, sufficiency, and additionally identifies such a criterion as ensuring the integrity of evidence, which includes preservation of the original electronic evidence and recording. The author formulates the definition of the concept of criteria for evaluation of electronic evidence, which is considered to be the mental and procedural activity of a court and participants to an administrative case aimed at forming a final conclusion on confirmation or refutation of the facts to be proved by means of electronic evidence. The author believes that a clear definition of the essence of the criteria for evaluation of electronic evidence is important for the formation of a new theory of electronic evidence evaluation and a new technology for practical implementation of the provisions of this theory. [ABSTRACT FROM AUTHOR]

Protection of archival materials from natural disasters is crucial for ensuring the accessibility, durability and integrity of stored data. Natural disasters such as floods, fires, earthquakes and storms can cause damage or even loss, not only of archival materials in physical form, but increasingly also in digital form. Therefore, every creator of public archival materials and those who store such materials must prepare and adopt a comprehensive approach to the protection of archival materials. In the article, the author presents a key tool for ensuring the safe long-term preservation of materials in digital form, namely risk assessment as a key integral part of internal rules for the capture and storage of materials in digital form. With a focus on environmental risk management, the article also provides some fundamental starting principles for creating a risk assessment and risk management measures. [ABSTRACT FROM AUTHOR]

After a boom that coincided with the advent of the internet, digital cameras, digital video and audio storage and playback devices, the research on data compression has rested on its laurels for a quarter of a century. Domain-dependent lossy algorithms of the time, such as JPEG, AVC, MP3 and others, achieved remarkable compression ratios and encoding and decoding speeds with acceptable data quality, which has kept them in common use to this day. However, recent computing paradigms such as cloud computing, edge computing, the Internet of Things (IoT), and digital preservation have gradually posed new challenges, and, as a consequence, development trends in data compression are focusing on concepts that were not previously in the spotlight. In this article, we try to critically evaluate the most prominent of these trends and to explore their parallels, complementarities, and differences. Digital data restoration mimics the human ability to omit memorising information that is satisfactorily retrievable from the context. Feature-based data compression introduces a two-level data representation with higher-level semantic features and with residuals that correct the feature-restored (predicted) data. The integration of the advantages of individual domain-specific data compression methods into a general approach is also challenging. To the best of our knowledge, a method that addresses all these trends does not exist yet. Our methodology, COMPROMISE, has been developed exactly to make as many solutions to these challenges as possible inter-operable. It incorporates features and digital restoration. Furthermore, it is largely domain-independent (general), asymmetric, and universal. The latter refers to the ability to compress data in a common framework in a lossy, lossless, and near-lossless mode. COMPROMISE may also be considered an umbrella that links many existing domain-dependent and independent methods, supports hybrid lossless–lossy techniques, and encourages the development of new data compression algorithms. [ABSTRACT FROM AUTHOR]

Open Educational Resources (OER) are valuable tools for diversifying teaching practices, contributing to a quality, equitable, open, and participatory education. However, unlocking the full potential of OER requires overcoming challenges related to its widespread adoption. One key strategy is empowering teachers to actively participate in the collaborative construction of high-quality OER collections that directly address their specific needs. This paper presents the results of a survey (N = 84) and a semi-structured focus group interview (N = 5) designed to collect teachers' perceptions of the critical factors to consider in designing a Community of Practice (CoP) focused on promoting sharing and digital curation of OER. The results highlight the importance of peer open review of shared OER, community-based evaluation based on pedagogical, technical, and scientific criteria, and the inclusion of OER metadata that mimics teachers' natural thinking. Furthermore, participants believe private feedback should be prioritised within these systems, as they perceive publicly shared comments might discourage future contributions. Although an expert's involvement in resource validation is prized, participants stated that this should not be limited to OER publication. Finally, the paper puts forward some recommendations regarding the design of digital platforms that support the work of a CoP focused on creating an OER repository. [ABSTRACT FROM AUTHOR]

Background: Low‐dose computed tomography (LDCT) can mitigate potential health risks to the public. However, the severe noise and artifacts in LDCT images can impede subsequent clinical diagnosis and analysis. Convolutional neural networks (CNNs) and Transformers stand out as the two most popular backbones in LDCT denoising. Nonetheless, CNNs suffer from a lack of long‐range modeling capabilities, while Transformers are hindered by high computational complexity. Purpose: In this study, our main goal is to develop a simple and efficient model that can both focus on local spatial context and model long‐range dependencies with linear computational complexity for LDCT denoising. Methods: In this study, we make the first attempt to apply the State Space Model to LDCT denoising and propose a novel LDCT denoising model named Visual Mamba Encoder‐Decoder Network (ViMEDnet). To efficiently and effectively capture both the local and global features, we propose the Mixed State Space Module (MSSM), where the depth‐wise convolution, max‐pooling, and 2D Selective Scan Module (2DSSM) are coupled together through a partial channel splitting mechanism. 2DSSM is capable of capturing global information with linear computational complexity, while convolution and max‐pooling can effectively learn local signals to facilitate detail restoration. Furthermore, the network uses a weighted gradient‐sensitive hybrid loss function to facilitate the preservation of image details, improving the overall denoising performance. Results: The performance of our proposed ViMEDnet is compared to five state‐of‐the‐art LDCT denoising methods, including an iterative algorithm, two CNN‐based methods, and two Transformer‐based methods. The comparative experimental results demonstrate that the proposed ViMEDnet can achieve better visual quality and quantitative assessment outcomes. In visual evaluation, ViMEDnet effectively removes noise and artifacts, while exhibiting superior performance in restoring fine structures and low‐contrast structural edges, resulting in minimal deviation of denoised images from NDCT. In quantitative assessment, ViMEDnet obtains the lowest RMSE and the highest PSNR, SSIM, and FSIM scores, further substantiating the superiority of ViMEDnet. Conclusions: The proposed ViMEDnet possesses excellent LDCT denoising performance and provides a new alternative to LDCT denoising models beyond the existing CNN and Transformer options. [ABSTRACT FROM AUTHOR]

Image denoising has gained in relevance as a component of image preprocessing due to the increased use of digital images in a range of applications, as well as the degradation of image quality caused by noise introduced by unavoidable occurrences. This work suggests a novel two-stage filter to remove salt and pepper noise from the images. It operates in two stages, the first stage uses an enhanced adaptive type-2 fuzzy noise identifier to identify the corrupted pixel, and the second stage uses a simple linear regression-based approach filter to denoise the corrupted pixel. We first identify a pixel as corrupted or uncorrupted using an improved adaptive type-2 fuzzy-based Gaussian membership function with variables both mean and variance for a specific corrupted image frame. The second step is denoising the damaged pixel using a linear regression-based technique. Herein, we propose a novel co-design method that uses the Gaussian membership function for detection and a linear regression-based denoising technique without any parameter tuning, resulting in better time efficiency. We validate the proposed improved adaptive type-2 fuzzy detection and linear regression-based filter (IAFDLRBF) on a variety of standard images and real-time images with varying noise density. We compare the simulation results with various state-of-the-art methods in terms of various assessment metrics. The results demonstrate the effectiveness of the proposed filter even at high noise densities by providing better detail and edge preservation of an image. [ABSTRACT FROM AUTHOR]

How might the creation of digital research infrastructure for preserving archival materials in Latin America resemble the infrastructure of extractivism? This essay examines the development of a digital repository for one of the most important collections of Amazonian history, culture, and politics at the Biblioteca Amazónica in Iquitos, Peru. Funded in part by the Modern Endangered Archives Program (MEAP) at the University of California, Los Angeles, the project seeks to digitally catalog and preserve photographs, newspapers, maps, and local journals at risk of further damage by humidity, rodents, lack of funding, and potential fires. In dialogue with critical infrastructure studies, I consider how this otherwise altruistic project fits into the broader landscape of extractive infrastructure in the Amazon region. To problematize what materialities might be flattened in the process of digitalization and their implications for the potential digital colonialism of the project, I compare the MEAP research infrastructure to other infrastructural projects in the Iquitos area, with special emphasis on the kinds of relational encounters that Iquiteños improvise when infrastructure does not work as intended. I argue that creating similar opportunities to engage and struggle with digital research technologies has the potential to transform them for local use and complicate their potentially extractive qualities. [ABSTRACT FROM AUTHOR]

This paper is a short summary of the experiences from the first one and a half years of support to the Ukrainian cultural heritage sector from the international volunteer network SUCHO (Saving Ukrainian Cultural Heritage Online). The paper first outlines the current situation in Ukraine in the shadow of the full-scale Russian invasion and then focuses on the role of grassroots movements and the different forms of support provided by SUCHO. Finally, the paper discusses some key experiences from these efforts and addresses ideas for further support. [ABSTRACT FROM AUTHOR]

Natural disasters, neglect and demolition continually exacerbate the dire state of heritage in New Zealand. This research investigates existing knowledge on heritage conservation in New Zealand and explores contemporary methods of digital preservation. The research involved a survey study of 156 responses from industry professionals, community members, government officials and academics. It was analysed using Braun and Clark's thematic analysis to understand the risks and benefits of digital tools in heritage conservation. The findings are organized into themes, sub-themes and codes. The paper is presented in three parts: (1) a review of heritage digitalisation methods and existing regulatory frameworks in New Zealand; (2) survey results and (3) a discussion on perceptions of using digital tools for conservation. Despite varying perceptions, the benefits of digitalisation outweigh the drawbacks. Through solutions outlined by professionals in the country, this paper highlights the potential of digitalisation to enhance heritage conservation efforts. [ABSTRACT FROM AUTHOR]

Digital preservation encompasses policies, technologies, and strategies to ensure that digital objects and collections will sustain for future use. This study aimed at investigating the trends toward digital preservation in terms of in-house activities versus outsourcing by systematically reviewing the extant literature. The relevant studies were identified by accessing multiple databases and indexing and abstracting services. After retrieving the relevant literature, necessary filtering was done by following the PRISMA protocols, and thereafter the selected studies were finalized for further review. The meta-analysis of the final studies affirms a strong global preference of libraries, archives, and other cultural and memory organizations toward in-house activities for the preservation of their digital objects and collections compared to outsourcing digital preservation activities by third parties. The results of this study provide a holistic view of how digital assets are being preserved in memory institutions across the world and underpin the global management (in-house or outsourced) approaches for digital preservation. [ABSTRACT FROM AUTHOR]

Purpose: The study examined the mediating and moderating roles of engagement and trust in the relationship between digital marketing and purchase intentions in the banking industry. Design/methodology/approach: The study was quantitative and cross-sectional and used a sample of 462 respondents drawn through a combination of purposive and convenience sampling techniques. The main method of data analysis was the covariance-based structural equation modeling used to assess the paths relationships, using the Amos v.23 software. Prior to that, a confirmatory factor analysis was done to assess the reliability and validity of the instrument. Findings: The empirical findings support the hypothesized relationship between digital marketing and purchase intention of banks' services. Consumer engagement partially was found to mediate the association between digital marketing and purchase intentions. Finally, consumer trust moderates the relationship between digital marketing and consumer engagement. Research limitations/implications: Given digital marketing is evolving with new tools and channels coming up by the day, we recommend that future studies should explore others such as search engine marketing, affiliate marketing, content marketing, display advertisement etc. These will help give a broader perspective to the digital marketing strategy and its effect on consumers' purchase intentions of banks' services. Practical implications: The study makes a strong case for the use of multi-channel and/or integrative approach, improving digital infrastructure and systems, adopting new and emerging digital tools/channels such as artificial intelligence, chatbots among others to facilitate digital marketing strategy implementation while ensuring active consumer engagement. It further underscores the need for managers to build trust and regularly engage consumers through their digital marketing channels. Originality/value: The integration of the variables in the study provides new empirical understanding and extends knowledge in digital marketing theory. It also serves as a foundation for future studies to explore other areas in the digital marketing, especially from a developing digital economies perspective. [ABSTRACT FROM AUTHOR]

With the advent of artificial intelligence digitization, intangible cultural heritage faces challenges in preservation and transmission. Utilizing modern technology to achieve digital protection and dissemination has become a crucial issue today. This study enhances the digital inheritance and development of Chinese intangible cultural heritage paper-cutting art through generative AI technologies, specifically Diffusion and LoRA models. The Analytic Hierarchy Process (AHP) was employed to categorize the cultural value of paper-cutting, selecting four core elements: "Spring Festival", "Chinese Zodiac", "Women", and "Birds and Flowers". Based on these, eight LoRA models were developed to generate paper-cutting-style patterns (using the FLUX.1-dev and Stable Diffusion 1.5 models). In the user satisfaction assessment, the Importance–Performance Analysis (IPA) method was used to analyze four dimensions of the model experience. The results indicate that the LoRA model excels in generating detailed paper-cutting patterns and accurately reproducing cultural elements, particularly in the generation of complex Chinese character designs. User feedback suggests that the LoRA model effectively enhances the digital representation and dissemination of paper-cutting art, though there is room for improvement in terms of generation speed and ease of operation. This study provides a new technological pathway for the digital preservation of intangible cultural heritage and promotes the modernization of paper-cutting art transmission. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This persuasive position paper aims to discuss the public policy gaps in digital preservation identified by UNESCO and persuade the development of the current digital public policies. To evidence these gaps, the principal topics of digital public policies (digital strategy) from four countries were analyzed: Brazil, France, Spain, and the United Kingdom. The analysis evidence that these digital public policies are focused on the modernization of public administration and cybersecurity; they do not contemplate digital preservation. To support the position, current legislation in record management is indicated to connect the preservation of physical and digital documents. The 2030 Agenda for Sustainable Development is also used to persuade because digital preservation is an indispensable component of sustainable development. That is because today, large amounts of cultural heritage are created and only available digitally, and never "fixed" in a physical form, museums, archives, and libraries, also embarking on an epic journey to digitization and "no development is sustainable without considering culture." Digital culture heritage must be available for future generations, and only digital preservation can guarantee that; therefore, digital preservation must be treated as a public policy. [ABSTRACT FROM AUTHOR]

Digital evidence processing can be more critical in the heterogeneous Internet-of-Things (IoT) paradigm due to the lack of transparency, trust, integrity, and immutability. Researchers have conducted a substantial range of research over the past few decades to improve the digital chain of custody and forensic investigation. In a digital forensic investigation, preserving the digital evidence chain of custody with end-to-end security, integrity, privacy, traceability, access control, provenance, transparency, and evidence verification presents several challenges. The present paper proposes a blockchain-based model for a smart IoT environment to address these challenges. The primary goal of this study is to ensure the integrity, confidentiality, trust, and privacy of vital digital evidence throughout the forensic investigation. We only insert or delete digital evidence after verifying the user's authentication. We have utilized a consortium blockchain-based secure system that harnesses the benefits of an interplanetary file system (IPFS) to enhance the security and integrity of digital evidence management and chain-of-custody. The proposed mechanism can achieve security, integrity, access control, immutability, and trust for a digital chain-of-custody. The integration of the Ethereum blockchain-based test network and IPFS facilitates the development, testing, and deployment of decentralized applications (dApps) with enhanced security, efficiency, and decentralization. We deployed smart contracts on Metamask and tested them on the Sepolia test network. The Ethereum network records different gas fees and transaction fees based on various timestamps, gas prices, and traffic. In different numbers and timestamps, gas prices vary between 2.50000001 Gwei and 13.559962651 Gwei. Compared to many other transactions, the reduction ranges from 10 to 20%. The proposed model provides the highest throughput, approximately 5% more transactions per second, as well as the lowest latency. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to document the creation of the Archivo del Paro #28A, a digital archive created in Colombia as a result of the social mobilizations that took place in 2021. To this end, we situate the cycle of protests that has been referred to as “social outburst” in a context of economic, political, and social crisis deepened by the effects of unequal management of the COVID-19 pandemic, but also in a context of political opening following the peace agreements between the State and the Revolutionary Armed Forces of Colombia—People’s Army (FARC-EP) in 2016. In this context, we argue that the social outburst of 2021 constituted a historical milestone in terms of democratic political participation and, consequently, we respond to the ethical and political duty of archiving it. We then show that the project for creating the Archivo del Paro #28A is inspired by other initiatives that have taken place in the international arena. Finally, we describe the process of creating the archive through the campaign “Hacer eterno lo efímero” [Making the ephemeral last forever], which framed the processes of gathering, classification, valuation, and dissemination of the collected documents as a strategy to achieve a broad diversity of voices. [ABSTRACT FROM AUTHOR]

This case study explores social innovation in Spanish rural areas, aiming to revive local culture, transmit heritage across generations, and tackle social isolation through technology-supported initiatives. The study involved an intergenerational classroom, located in the North of Spain, which involves a methodology of 11 sessions across four phases: digital literacy, technological experimentation, intergenerational evaluation, and personal feedback analysis. Participants engaged in technology experiments linked to documenting cultural heritage. Qualitative data from semi-structured interviews explored changes in social relationships and intergenerational learning impact, analyzed thematically based on project aims. Adults and youth valued interacting across generations, finding it rewarding. The project facilitated knowledge exchange, enriched social and cultural aspects, and reduced social isolation in dispersed communities, fostering new connections. Digital heritage efforts reclaimed local histories and traditions. Strengthening intergenerational bonds enhances rural community resilience. Such innovations bolster social networks, particularly for youth. Digital heritage preservation aids in conserving cultural legacy but requires robust infrastructure and comprehensive policies for sustainability. The study underscores the role of social innovation in revitalizing communities and advancing resilience efforts. [ABSTRACT FROM AUTHOR]

In this paper, we examine the role digital curation practices and practitioners played in facilitating open science (OS) initiatives amid the COVID‐19 pandemic. In Summer 2023, we conducted a content analysis of available information regarding 50 OS initiatives that emerged—or substantially shifted their focus—between 2020 and 2022 to address COVID‐19 related challenges. Despite growing recognition of the value of digital curation for the organization, dissemination, and preservation of scientific knowledge, our study reveals that digital curatorial work often remains invisible in pandemic OS initiatives. In particular, we find that, even among those initiatives that greatly invested in digital curation work, digital curation is seldom mentioned in mission statements, and little is known about the rationales behind curatorial choices and the individuals responsible for the implementation of curatorial strategies. Given the important yet persistent invisibility of digital curatorial work, we propose a shift in how we conceptualize digital curation from a practice that merely “adds value” to research outputs to a practice of knowledge production. We conclude with reflections on how iSchools can lead in professionalizing the field and offer suggestions for initial steps in that direction. [ABSTRACT FROM AUTHOR]

As cloud storage and multimedia communication continue to evolve, the preservation of image privacy is becoming increasingly important. Reversible data hiding in encrypted images (RDHEI) is an effective method for enhancing the protection of personal privacy. To improve the embedding capacity, this paper introduces a novel scheme for RDHEI using block-based bit-plane reallocation. First, an effective optimized prediction method is utilized to predict the value of each pixel, followed by the calculation of prediction errors (PEs). Then, block-based bit-planes of PEs are extracted, and ten different bit-plane types are categorized to facilitate bit-plane reallocation, thereby freeing up redundant space. Finally, an adaptive encryption procedure is employed to encrypt the reallocated bit-plane, excluding the flag-bits. Experimental results demonstrate that the proposed scheme achieves average embedding rates (ER) of 3.584 bpp, 3.501 bpp, and 2.985 bpp on the three experimental datasets, all of which are higher than those of other state-of-the-art RDHEI schemes while ensuring both reversibility and security. [ABSTRACT FROM AUTHOR]

Like in most bachelor engineering programs, the education of geomatics students typically begins with an extensive theoretical introduction covering fundamental subjects. The general objective of the bachelor program is to cultivate geomatics engineers with robust hands-on knowledge. Nevertheless, the progression to a stage where students can independently engage in exercises with minimal supervision is a long process. Although field work-based practices are dominant in this field, they often entail activities limited to testing, experimenting, and the application of basic theories. While this approach is efficient in imparting routine knowledge, it may lead to the fragmentation of acquired knowledge, thereby lacking a comprehensive understanding of the broader significance and context. Students often encounter more complex challenges when commencing work on their bachelor thesis, leading to a steep learning curve within a constrained timeframe. This late exposure to real-world tasks can be a limiting factor, hindering a smoother transition from education to professional work. This paper provides a case study of project-based learning (PjBL) within a geomatics bachelor program. Specifically, it discusses a digital heritage preservation project where students documented an old Norwegian log house throughout the autumn semester of 2023. The outcomes of this learning approach are analyzed with the help of the key features of the PjBL methodology, focusing on students' learning outcomes and their assessment measures. [ABSTRACT FROM AUTHOR]