ABSTRACT. Patent documents serve as a valuable source of information for companies and researchers when making decisions. Therefore, there is a demand for classifying patent documents and analyzing them. Topic modeling is a major approach to automatically extracting topics from documents, and it can be used for document classification. Although we can apply existing topic modeling methods to patent documents for our intended purpose, most models do not fully take into account the relationships between patent documents and their metadata, such as titles, abstracts, and classification codes. This paper explores a topic modeling approach that considers the relationships between patent documents and their metadata, by developing and evaluating a novel method, named Metadata-Assisted Topic Modeling (MATopic). MATopic (1) generates more coherent and diverse topics by considering both the metadata of patents and their context, and (2) infers evidence about what components make up the topics by representing the detected topics as nodes in a knowledge graph. The experiments using real-world patent document datasets show that MATopic outperforms existing methods in both topic diversity and coherence.

ABSTRACT. As knowledge recombination increasingly shapes technological advancement, scholarly efforts have focused on how integrating knowledge elements can enhance technological innovation performance. Our study con-tributes to this literature by adopting a network perspective and assessing the predictive value of various knowledge linkage features. Using granted patents in the pharmaceutical field, we constructed the annual International Patent Classification (IPC) co-occurrence network and extracted the real-time linkage features of pairwise co-occurring IPCs, including tie strength, knowledge distance, node assortativity, and betweenness centrality. Based on explainable machine learning, we found that XGBoost outperformed in predicting both patent impact and patent disruptiveness. More importantly, feature interpretation based on the Shapley value illustrates that patent impact and patent disruptiveness have different determinants, implicating different knowledge combinative strategies. Specifically, we found that betweenness centrality and node assortativity contribute significantly in predicting patent impact, suggesting that localized search combining hotspot and marginal knowledge components are more likely to produce impactful inventions. Conversely, tie strength between combined knowledge components is the most important predictor for patent disruptiveness, indicating that deeper exploitation along existing technology portfolios can effectively enhance patent disruptiveness. These results provide new insights into how knowledge recombination fuels technological innovation and offer practitioners valuable strategies for developing target technologies.

ABSTRACT. In research, measuring instruments play a crucial role in producing the data that underpin scientific discoveries. Information about instruments is essential in data interpretation and, thus, knowledge production. However, if at all available and accessible, such information is scattered across numerous data sources. Relating the relevant details, e.g. instrument specifications or calibrations, with associated research assets (data, but also operating infrastructures) is challenging. Moreover, understanding the (possible) use of instruments is essential for researchers in experiment design and execution. To address these challenges, we propose a Knowledge Graph (KG) based approach for representing, publishing, and using information, extracted from various data sources, about instruments and associated scholarly artefacts. The resulting KG serves as a foundation for exploring and gaining a deeper understanding of the use and role of instruments in research, discovering relations between instruments and associated artefacts (articles and datasets), and opens the possibility to quantify the impact of instruments in research.

ABSTRACT. Open repository projects serve as valuable resources for scholarly communication and knowledge dissemination. However, interacting with these repositories can be challenging due to the vast amount of data, the restriction of browsing features, and the limitation of relational database queries. This paper presents a technical procedure and coding details that leverage Retrieval-augmented Generation (RAG), Large Language Models (LLMs), embeddings, and LangChain to develop an AI-enhanced conversation application tailored for communication with open repository systems, specifically focusing on DSpace. The chatbot uses RAG to enhance response generation by integrating relevant information retrieved from repository structural data and text documents. LLMs form the chatbot's core generation capabilities, ensuring coherent and contextually appropriate interactions. Embeddings are used to semantically enrich queries and responses, thereby enhancing understanding and relevance. LangChain coordinates among these components, managing the information flow and interaction between users and repositories.

ABSTRACT. With the growing prevalence of generative artificial intelligence (GenAI), its impact on digital libraries and archives has become increasingly significant. This research explores the role of GenAI in enhancing digital cultural memory initiatives at museums and art galleries in Indonesia, aligning with the theme of "Sustainability and Empowerment." The study investigates how the integration of augmented reality (AR) and virtual reality (VR) technologies can advance the preservation, accessibility, and engagement of cultural artifacts and exhibitions. ImersifA, a 360-degree permanent video mapping installation at the National Museum of Indonesia, exemplifies these efforts. Utilizing AR mode, ImersifA animates cultural artifacts, providing contextual information and interactive elements that deepen visitor understanding and experience. Additionally, virtual tours of permanent exhibitions at the National Gallery of Indonesia enable remote exploration of artworks and cultural heritage, overcoming geographical barriers and expanding public access. Employing qualitative methods with direct observation, this study reveals that AR and VR significantly contribute to the sustainability and empowerment of cultural preservation, accessibility, and audience engagement in the digital age.

ABSTRACT. Textual documents need to be of good quality to ensure effective asynchro-nous communication in remote areas, especially during the COVID-19 pan-demic. However, defining a preferred document structure (content and ar-rangement) for improving lay readers’ decision-making is challenging. First, the types of useful content for various readers cannot be determined simply by gathering expert knowledge. Second, methodologies to evaluate the doc-ument’s usefulness from the user’s perspective have not been established. This study proposed the experimental framework to identify useful con-tents of documents by aggregating lay readers’ insights. This study used 220 online recipes as research subjects and recruited 1,340 amateur cooks as lay readers. The proposed framework identified six useful contents of recipes. Multi-level modeling then showed that among the six identified contents, suitable ingredients or notes arranged with a subheading at the end of each cooking step significantly increased recipes’ usefulness. Our framework contributes to the communication design via documents.

ABSTRACT. Purpose: Digital library as an organization involves information system (DLMS), Content (digital resources), users (targeted populations), and services (Access methods such as browsing, searching, and downloading). To understand these components more, a model or theory that explain each component is needed to predict successful implementation of Digital library. Thus, the aim of this study is to examine digital library models in the literature and to develop overall Digital library model as a consolidation of examined existing digital library models. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 was followed. 16 Original articles published in English from 2019-2023 which are retrieved from Emerald, Google Scholar, IEEE, Springer, and Wiley online library are selected for final review. Different searching strategies such as advanced/filter searching provided by databases, phrase search and Boolean search are incorporated to refine the search result. Results: from the synthesis of 16 studies, Delone and McLean IS success model is most frequently adopted DL model. Overall, the dimensions of DL model are Organizational, Technological, Informational, Environmental and Social or user perspective. 12 constructs from overlap and combination of other constructs are significant for development of overall DL model. Facilitating condition is the base influencing factor of DL implementation and use. Conclusion: This study consolidates different findings of DL models by considering relationships among constructs and mapping them with each other to develop new overall DL model.

ABSTRACT. The Chinese National Agriculture Big Data and Information Service Alliance is a national professional library and information institution consortium in the field of agriculture, which was established in 2016. This paper makes clear the necessity for the consortium to conduct information resources co-construction and sharing, and introduces in detail its development history and matched information infrastructure. Then, using the SWOT method, the internal strengths and weaknesses as well as external opportunities and threats for the consortium to carry out information resources co-construction and sharing are analyzed, and the consortium should adhere to the diversified and reversal development strategies to promote information resource co-construction and sharing in the next step. The paper could give some suggestions for information resource co-construction and sharing development of Chinese National Agriculture Big Data and Information Service Alliance and other similar professional library and information institution consortia.

ABSTRACT. As part of our ongoing work on rich structures for representing complex knowledge, we have been exploring qualitative descriptions of systems which are composed of interacting flows of entities. Here we consider the issues in developing low-level descriptions of flows such as parsing flows, specifying constraints for transitions, and coordinating entities at different levels of granularity. We propose a unified Flow Model Framework for describing flows and illustrate how it can be used in an interactive visualization interface.

ABSTRACT. Japanese universities are strongly encouraged to formulate policies on research data and many have published research data polices in the last five years. When universities design their research data services, they must bear their institution’s research policy and the standard policy in Japan in mind. This study aimed to clarify the overall trends and characteristics of the research data policies developed by Japanese universities. This study presents a preliminary analysis of 70 research data policies that Japanese universities have formulated and published from March 2020 to June 2024. Policy titles, elements of structure, policy subjects, responsibility for data management, and terms used for researchers’ responsibilities and rights were examined. It transpired that while the elements described were generally common, there were differences in the policy names and terminology used. Most of the policies incorporated the management and sharing of data, but did not address the early stages of the research process, such as data management planning.

ABSTRACT. Named entity recognition (NER) is a particularly challenging task, especially for historical documents that lack extensive annotated datasets. The titles of ukiyo-e, a genre of Japanese artworks, contain a significant number of entities and are composed of short texts rich in historical information. The complexity and brevity of these titles pose considerable challenges for analysis. This paper presents the construction of an ukiyo-e NER dataset and introduces a BERT-based NER methodology that achieves notable success in entity recognition within ukiyo-e titles. The study underscores the effectiveness of BERT and its derivative models on the ukiyo-e NER dataset, proposing a viable NER solution for historical documents. The proposed approach demonstrates the capability to perform NER tasks on ukiyo-e titles using pre-trained models on a relatively small annotated dataset, achieving an accuracy exceeding 80\%. Furthermore, this paper examines the distinct characteristics of BERT and its derivative models, optimizing their application to the ukiyo-e NER dataset.

ABSTRACT. Despite the country’s cultural wealth, Indonesia is still struggling to identify and map its cultural heritage collections across the dispersed islands, as well as digitize and make them accessible online. This paper aims to identify and examine the provision and digitization of cultural collections carried by state libraries and archives in the 38 provinces across the archipelago. Out of 32 institutions, we obtained 65.6% responses which show that state libraries and archives in Indonesia hold a diverse range of cultural heritage collections that are being digitized and provide valuable resources which may not be found elsewhere. However, multiple layers of constraints ranging from policy and copyright issues, traditional beliefs and distrust of the local communities, and the lack and unequal development of digital infrastructures and skilled staffs challenge many digitization projects. Overcoming this complex situation requires a collaborative approach from different stakeholders to ensure these cultural resources are more widely accessible, and therefore beneficial to the public.

ABSTRACT. Eye-tracking studies focused on art galleries and museums within the realm of Instagram, especially in the Indonesian context, are notably scant. This investigation elucidates the user interaction and experience of the art gallery’s Instagram account, @galerinasional. Employing a quantitative approach, we implemented eye-tracking experiments using the well-known online eye-tracking software RealEye. The study participants were followers of the National Gallery of Indonesia’s (Galnas) Instagram profile, seven women and three men, in two age brackets: 18–24 years (n = 5) and 25–34 years (n = 5). The experimental protocol required participants to execute five tasks centered on locating exhibition details and artwork on the Galnas Instagram platform, with a duration of 100 seconds allocated to each task. The Participant Quality Grade (PQG), examination duration, optimal browser dimensionality, K-factor mean, gaze and fixation frequencies, and heat maps were determined for the participants. The key findings are as follows. (1) The participants’ PQG scores were predominantly between 4 and 6. (2) Investigative browsing typically exceeded the 100-second limit. (3) The consensus on the ideal browser dimensions hovered around 1,368.6 × 814.8 px. (4) The K-factor mean across participants tended toward K > 0. (5) The average gaze occurrence was 27 items per second for most participants. (6) A noticeable disparity in fixation counts was observed between the two age groups, with individuals aged 25–34 demonstrating prolonged engagement with Galnas’ content. (7) Heat maps accentuated a pronounced concentration on visual content, encompassing photographs, videos, and their associated captions.

ABSTRACT. Shall people be more moral during the war? By mining large-scale historical newspaper archives, we provide promising evidence through big data analysis to answer this question. Taking the American Civil War as the scenario, we exploited the historical newspaper database Chronicling America as corpus together with widely-used moral lexicons, and retrace the diurnal dynamics of collective moral motivation of American society from 1849 to 1876. Sufficient statistics revealed that compared with Pre-war and Post-war, collective moral motivation of the society increased significantly during wartime. Regression analysis suggested the situational sensitivity of moral motivation, i.e., during the first half of wartime the moral motivation boosted while then decreased in the second half when the war entered a stalemate. Moreover, the two component dimensions, agency and communion, also increased during wartime.

ABSTRACT. Certain knowledge is transfer from one generation to the next through spoken word, a process known as oral tradition or oral knowledge transfer. Oral knowledge refers to the sharing and preservation of information, stories, and experiences through verbal communication. Oral knowledge are major sources of information which includes cultural and traditional beliefs, historical events, ancestral histories, developmental journey, myths, legends, and skills, among other things. It portrays a geographical and political landscape of a community or a social group. At the same time, since it passes from generation to generation orally and there is no documented form of these information. And at this point, the question arises whether these information’s are in a vulnerable phase of missing out? Proper documentation, archiving is the necessity of the hour to preserve these knowledges for sustainable use by budding generations. The study focuses on perspective of library professionals towards oral traditions and their roles and responsibilities in preserving cultural heritages where the initiatives taken by various institutions to preserve the oral knowledge is studied. To collect data of the study, a structured questionnaire was constructed and distributed among the library professionals of North East India through social media platforms. The results states that library professionals’ holds the responsibilities of collecting, documenting, preserving, and disseminating oral traditions, where technologies like Artificial Intelligence (AI) can be involved. Unfortunately, awareness of oral traditions among important stockholders like library professionals is not satisfactory. In this regard, culturally rich site like north east India is still in a position where education, awareness about oral knowledge is in theoretical form; without proper practical implementation of theories of creating awareness among people, preservation of our oral heritages for sustainable use will remain a myth.