[Purpose/Significance] With the rapid advancement of the information society and the ongoing construction of smart cities, public libraries are facing increasing pressure to transition into a smart service model. Smart services leverage cutting-edge technologies to enhance user experiences and improve the efficiency of library services. Public libraries in China, however, are encountering challenges such as mismatched service offerings, unsatisfactory user experiences, and inadequate technological implementation as they move toward a smart service model. It is crucial to identify how to optimize this transition in a manner that prioritizes user needs, ensuring that smart library services meet the demands of a diverse user base. This research aims to explore the dynamic relationships among users, technology, content, and the service environment in public library smart services, thereby promoting innovation and addressing diverse user requirements. [Method/Process] The study develops a model to analyze the influence of various factors on the user experience of smart services in public libraries. Adopting Actor-Network Theory (ANT) constructs an integrated framework for understanding the interactions between various actors in the smart service ecosystem. By combining both online and offline surveys, the research captures library users' perceptions of their smart service experiences and identifies the critical factors that influence user experience and provides valuable data support and strategic recommendations for optimizing smart library services.Principal component analysis is used to identify the key factors affecting user experiences. [Results/Conclusions] The findings show that the core factors influencing user experience in smart services include: "advanced technology support," "network compatibility and flexibility," and "convenient communication channels" within the "library technology actors" dimension; "usability, operability, clarity, and comfort of portal browsing" within the "interaction between human-technology actors" dimension; "effort expectancy, information literacy, and time-energy consumption" within the "user (human actor)" dimension; "professionalism and competence of library staff" within the "librarian (human actor)" dimension; and "social influence and facilitating conditions" within the "interaction between human actors" dimension. These factors have a positive impact on the user experience, with particular attention required for the factors related to the "technology actors" dimension. Libraries need to focus on improving three factors in this area while maintaining and further optimizing the other factors. "Human-technology interaction" activities are crucial in improving the usability and user-friendliness of smart services, especially in more complex technological settings. Social influence and enabling conditions play an important role in enhancing user trust and their overall experience. Based on the empirical findings, the study proposes optimization strategies for public library smart services from three dimensions: the technical actors of the smart service system, the "human-technology actors" interactions, and the "translation" activities among human actors. These strategies include enhancing multi-dimensional collaboration among technical actors in the smart service system, improving the sensory experience of users with the smart service terminals in libraries by increasing their ease of use, empowering digital literacy, and optimizing innovation spaces to drive bidirectional reader participation. The aim is to provide a specific guide for the design and optimization of smart library services.

[Purpose/Significance] Unclassified sensitive information, a special type of information, that falls between state secrets and public information, may threaten national scientific and technological security if it is not managed properly. This study aims to clarify the conceptual connotation and management value of unclassified sensitive information. Additionally, it seeks to improve China's information security protection system by promoting the country's "national unclassified sensitive information management system". [Method/Process] First, based on literature research and content analysis, the characteristics and attributes of unclassified sensitive information and the necessity of its management are systematically explained. Second, the management experience of controlled unclassified information (CUI) in the United States is analyzed by means of case studies. These studies include the creation of special laws and regulations to unify the CUI management, the formation of specialized management institutions to create a complete organizational structure, the development of a CUI management system, and the establishment of CUI classification and labeling. Finally, it proposes strategies to promote the development of China's sensitive information management system, given the current state of management situation in China, with the aim of promoting the safe and efficient management of public information resources. [Results/Conclusions] China needs to strengthen the top-level design of its management system for unclassified sensitive information. First, China should establish a policy and standard system for managing unclassified sensitive information, and clarify the rules for defining and controlling it. Second, the organizational and institutional structure should be improved for the management of unclassified sensitive information, and strengthening the review of information disclosure. Third, efforts should be made to develop a management system for registering directories and labels of sensitive information, and to realize standardized and dynamic management of directories of sensitive information. Fourth, the dissemination, use, training and management check should be strengthened, and thus long-term and healthy management of unclassified sensitive information can be promoted. Fifth, a registration directory and labeling management system for sensitive information should be developed so as to achieve standardized and dynamic management of the sensitive information directory. Finally, efforts should be made to strengthen the dissemination and use of sensitive information, as well as training and management inspections, so as to promote the long-term and healthy management of unclassified sensitive information.

[Purpose/Significance] The confluence of digital transformation and the Fourth Industrial Revolution has driven the emergence of data science as an interdisciplinary field. Data science leverages structured and unstructured data to discover knowledge and support decision-making, thereby reshaping research paradigms in information science, computer science, and the social sciences. This study focuses on the development of data science degree programs within member institutions of the iSchools Consortium, a global alliance of information schools. Through systematic empirical investigation, the study aims to unveil innovative features in the program's disciplinary positioning, curriculum architecture, and talent cultivation models. This research aims to inform global information science education institutions on how to optimize their disciplinary strategies and curricular designs for data science. Ultimately, this will address the challenges of knowledge system reconstruction and talent development iteration within the traditional library and information science (LIS) discipline amid its digital transformation. [Method/Process] This study employed a web-based survey and content analysis methodology to create a multi-dimensional analytical framework based on the 2023 iSchools Consortium membership directory. Using a stratified sampling approach that integrated disciplinary influence, as measured by the QS World University Rankings, and program maturity indicators, including curriculum comprehensiveness and industry partnership networks, eight representative U.S. higher education institutions were selected as core samples. A systematic empirical investigation was conducted to thoroughly analyze the current landscape of data science degree programs. The study focused on four critical dimensions: 1) degree-awarding structures such as degree types, concentration specializations, and accreditation standards; 2) credentialing ecosystems such as micro-credentials, stackable certificates, and non-degree pathways; 3) curricular architectures such as core course clusters, elective modules, and interdisciplinary integration mechanisms; and 4) career trajectory outcomes, such as sectoral distribution, occupational roles, and industry-specific skill premiums. [Results/Conclusions] The study summarizes the current state of data science discipline education in international iSchools from several perspectives, including the characteristics of degree program offerings, the reconstruction of disciplinary positioning, pathways for curriculum integration, and insights into employment trends. Based on this, it makes recommendations for developing China's domestic data science discipline. These recommendations include optimizing the disciplinary layout, innovating the curriculum system, and deepening industry-education integration. However, it should be noted that this research is constrained by its small sample size of eight institutions and its geographical scope, which is limited to the United States. In the future, the study could expand to encompass members of the European iSchools consortium, such as the iSchool at University College London and the iSchool at Humboldt University in Berlin, as well as emerging data science programs in the Asia-Pacific region. Through cross-national comparative analysis, it aims to reveal how culture, policies, and industrial ecosystems impact disciplinary development differently. Furthermore, the study could incorporate Learning Analytics technology to model learner behavior in data science courses offered on MOOC platforms, such as Coursera and edX. This would facilitate the refinement of course module granularity and adaptability to better meet learners' needs.Keywors: data science; data science degree; library and information science(LIS); iSchools; data literacy

[Purpose/Significance] Integrating culture and tourism is key to promoting rural revitalization. Constructing a scientific evaluation system and exploring differentiated development paths are core issues for achieving rural cultural and tourism development. [Method/Process] Taking 26 mountainous counties in Zhejiang Province as the research object, a research framework incorporating multi-dimensional analysis methods was constructed based on user-generated content data from tourism platforms. First, travel journal texts were collected to build a cultural and tourism integration database. Second, the BERTopic model was used to identify the potential thematic elements in tourists' narratives. Third, sentiment analysis was applied to quantify the emotional value of different themes in each county. Finally, fuzzy-set qualitative comparative analysis (fsQCA) was employed to reveal the complex development paths of cultural and tourism integration. [Results/Conclusions] 1) Through global topic modeling, eight themes of cultural and tourism integration were identified in 26 mountainous counties in Zhejiang Province, including ecological landscapes, traditional settlements, food culture, transportation, cultural activities, cultural heritage and arts, accommodation facilities, and leisure industries. These eight themes are summarized into four conceptual categories of cultural and tourism integration: natural experience dimension, cultural experience dimension, service support dimension, and leisure consumption dimension. 2) Tourists generally hold a positive attitude towards cultural and tourism experiences in different counties. The natural and cultural experience dimensions are highly regarded, but the service support dimension shows uneven levels, and the leisure consumption dimension displays significant differences, hindering the improvement of the quality of cultural and tourism integration in mountainous counties. Ecological landscapes and traditional settlements constitute the core layer of tourism experiences, while accommodation and leisure business formats, as potential directions, still require further development and activation. The comprehensive performance of cultural and tourism integration in various counties presents a notable spatial pattern of "two poles in the north and south, a developing middle region, and relatively weak coastal areas". 3) Through configurational path analysis, the development paths of cultural and tourism integration in the 26 mountainous counties can be summarized into six configuration paths, including the "ecological landscape + traditional settlements + food culture + transportation" model, the "cultural heritage and arts + leisure industries + food culture" model, the "traditional settlements + food culture" model, the "ecological landscape + cultural activities + transportation" model, the "ecological landscape + cultural heritage and arts + leisure industries + food culture" model, and the "cultural heritage and arts + leisure industries + food culture" model. These paths differ significantly in their combinations of core elements, reflecting the differentiated development strategies of different regions in terms of resource endowment, cultural characteristics, and market positioning. Five of the paths highlight food culture as a core condition, reflecting its foundational role in cultural and tourism integration. Cultural heritage and arts and leisure industries jointly form the core conditions in three successful paths, highlighting the importance of combining in-depth cultural experiences with leisure activities. Accommodation facilities often appear as missing or marginal conditions, indicating that short-term stays are the main form of rural cultural and tourism.

[Purpose/Significance] Amid the global wave of digital transformation in education, artificial intelligence (AI) has emerged as a driving force behind Japanese educational reform, propelling the country's education system toward an "AI+" model. The "Approved Program for Mathematics,Data science and AI Smart Higher Education" (MDASH), led by the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), outlines a comprehensive framework for designing and implementing AI literacy (AIL) education in Japanese universities. MDASH not only reflects the Japanese strategic response to the AI-driven future, but also provides valuable theoretical references and practical guidance for enhancing AIL education in China. This study provides a detailed analysis of the "MDASH literacy-level" (MDASHL) curriculum model design, paying a particular attention to the model's modules and the mechanisms of interaction between them. It also examines the theoretical references from MDASHL review system to the AIL framework studies. The study proposes innovative implementation strategies for AIL education from unique perspectives, especially the "industry-academia integration" aspect. [Method/Process] Using internet research and literature analysis, starting with an exploration of Japanese national AI policy landscape, the study traces the evolution of Japanese AI policies and the contextual origins of the MDASH. It describes the objectives and philosophy of Japanese AIL education and delves into the theoretical underpinnings of the MDASHL curriculum model based on the mapping relationship between indicators of AIL frameworks and the components of the MDASHL review system. We select Hokuriku University, Wakayama University, Chiba University, and Kansai Univerisity as samples because they were approved by MDASHL and demonstrated exemplary effects. We introduce their subject curriculum design and specific teaching initiatives, identify the commonalities and unique characteristics of their AIL education, and further elaborate on their specific educational implementation pathways. [Results/Conclusions] The findings indicate that the Japanese MDASHL curriculum model is deeply rooted in the AIL frameworks. It summarizes five educational directions for Japanese AI literacy education: recognition, realization, comprehension, ethics, and practical operation. By comparing the current status of AIL education in China and Japan, the study found that Japanese AIL education has achieved rapid responsiveness and systematic development under the unified coordination of MEXT. It suggests that Japanese AI literacy education strategies have localized value, from which beneficial insights can be drawn in three areas: strategic planning, curriculum design, and industry-academia integration. These strategies provide innovative solutions for developing AIL education systems in Chinese universities. However, this study acknowledges limitations in the sample size. To comprehensively capture the full landscape of Japanese AIL education development, future research should expand the sample size, summarize its patterns and characteristics more thoroughly, and enhance the persuasiveness and generalizability of the findings.

[Purpose/Significance] The advent of the digital era has presented China with significant opportunities to modernize rural governance. Digital literacy is crucial for enabling farmers to participate in rural governance and promote the development of digital villages. Rural residents are direct participants in digital village development, and their digital competence fundamentally determines the modernization level of rural governance. Their proficiency in digital skills affects not only the effectiveness of intelligent rural management, but also serves as a key indicator for measuring the progress of digital rural development. [Method/Process] Based on a literature review and sociopolitical reports, this study combines research objectives and thematic focus to create a questionnaire that investigates farmers' digital competence and rural governance performance. A stratified sampling strategy was implemented to select 306 rural households from diversified villages across township and sub-district jurisdictions, in Xia County, Shanxi Province, for the case study. The dataset encompasses respondents' demographic attributes, familial characteristics, digital proficiency metrics, and multidimensional indicators of rural governance efficiency and capacity building. Through integrated application of exploratory factor analysis (EFA) and multivariate linear regression modeling, this investigation systematically examines the determinants through which digital literacy influences governance outcomes. Together, these approaches establish a theoretical framework and evidence-based pathways for enhancing rural digital transformation initiatives. [Results/Conclusions] The empirical analysis results indicate that farmers' digital literacy significantly impacts rural governance efficacy. Specifically, improvements in the four dimensions of digital literacy - digital awareness, digital skills, digital application, and digital security - positively influence the efficacy of rural governance.In other words, the higher the digital literacy level of farmers, the greater the enhancement in rural governance efficacy. Among these, digital security literacy has the most significant effect on improving governance efficacy. Next is digital application literacy, followed by digital awareness literacy. Digital skill literacy exhibits a relatively weaker impact. Given the significant positive influence of digital literacy on rural governance efficacy, this paper proposes recommendations from three perspectives: strengthening farmers' proactive awareness of digital literacy, enhancing their knowledge in digital literacy, and improving the digital infrastructure construction in rural areas. These suggestions provide practical references for the digital development of rural governance in Xia County, Shanxi Province. Due to various constraints, however, the study only examined Xia County in Shanxi Province as the research area, resulting in notable geographical limitations in the sample. This is because rural regions in different areas exhibit significant disparities in economic development levels, cultural traditions, and policy support, all of which may affect farmers' digital literacy and the efficacy of rural governance. Consequently, the conclusions of this study may not accurately reflect the actual conditions in rural areas across diverse regions. To improve the generalizability of the findings, future research should expand the sample selection to include more representative areas.

[Purpose/Significance] Under the background of digital government construction, as a new type of service subject of human-machine collaborative governance, the influence mechanism of the social role positioning of government digital humans on public adoption behavior urgently needs theoretical exploration. Most existing studies have focused on the technical level. This study, based on the perspective of social role theory, explores the influencing mechanism of different role positioning of government digital humans in government service scenarios on public adoption behavior, which is of great significance for optimizing government services and improving the intelligent level of government services. [Method/Process] An experimental research method was adopted to construct a two-factor inter-group experimental design of "social role-business type", and a simulation experiment of government service scenarios was carried out through random grouping. Based on previous studies, we defined the role positioning of "advisors" and "decision-makers" for government digital humans, and constructed experimental scenarios by combining two service scenarios of consultation and approval. The subjects were randomly grouped to complete the role cognition test and human-computer interaction tasks. Data were collected by using the research path combining situation simulation and questionnaire survey. The psychological mechanism and decision-making logic of the public's adoption behavior were analyzed through the data analysis results. [Results/Conclusions] The research findings are as follows: 1) There is a significant interaction effect between the social roles and business types of government digital humans. In approval service scenarios, the decision-maker role is more capable of promoting public adoption behavior than the advisor role; 2) Human-computer trust perception plays a crucial mediating role in the influence path of social roles on the public's adoption behavior, revealing the core value of the trust mechanism in human-computer interaction; 3) The synergy effect between role authority and task fit constitutes an important mechanism influencing public cognition. This study expands the explanatory boundary of the social role theory in the field of intelligent government services and provides theoretical support for the construction of smart government services. However, there are still certain limitations. The service scenario simulation in the experimental design is difficult to fully restore the complexity of real government services. Future research can extend the multi-dimensional role classification system and deepen the mechanism exploration by combining the mixed research method. We have verified the applicability of the theoretical model in real government service scenarios and expand the existing conclusions. In addition, exploration on the dynamic impact of long-term interaction between government digital humans and the public on behavioral evolution is also a potential research direction.

[Purpose/Significance] The ongoing digital transformation has led to significant changes in public cultural services, particularly in content generation, communication channels, and modes of public participation. "Accessibility," a key indicator of the extent to which citizens' cultural rights are realized, is typically assessed along four dimensions: availability, acceptability, accessibility, and adaptability. Previous research has focused primarily on the supply side of accessibility, examining how factors such as the distribution of cultural resources, infrastructure development, and policy support affect user engagement. However, with the widespread adoption of digital technologies, individuals' ability and willingness to access information, utilize services, and provide feedback - collectively referred to as "digital literacy" - has become an increasingly important variable influencing cultural participation. Consequently, this study seeks to explore the relationship between users' digital literacy and the accessibility of public cultural services from a demand-side perspective. It aims to provide a more systematic theoretical framework and practical approach to optimizing the effectiveness of public cultural services. [Methods/Process] This study assesses users' digital literacy by examining their level of digital access, Internet usage, and service availability based on data collected from the Beijing-Tianjin-Hebei region. A structured questionnaire yielded 892 valid responses. To analyze the relationship between users' digital literacy and the accessibility of public cultural services, the study applies a generalized ordered logit model. A generalized ordered logit model is employed to analyze the substitution and overlap effects between users' digital literacy and the various dimensions of service accessibility. [Results/Conclusions] There is currently a digital divide exists between different demographic groups. A significant substitution effect is observed between traditional public cultural accessibility and users' digital literacy, with limited overlap between the two. Digitization has driven the modernization of public cultural resources and services, particularly in terms of technology and service delivery. However, there remains a time lag between the users' digital literacy of users and the digital transformation of the public cultural supply side. This lag suggests that the digital needs of users and the availability of digital cultural services are not fully aligned, which negatively impacts the effectiveness of public cultural services. Therefore, enhancing users' digital literacy, especially improving their ability to adapt to digital cultural resources, is a crucial factor in transitioning public cultural services from "accessibility" to "enjoyment". In promoting the digital upgrading of public cultural services, greater emphasis should be placed on developing users' capabilities and anticipating their needs.

[Purpose/Significance] The development of artificial intelligence generated content (AIGC) technology has engendered novel prospects for the establishment of creating inclusive and expansive learning environments. In light of the potential risks associated with the misuse of AIGC tools, the present study analyzes the factors influencing students' use of AIGC tools within the context of artificial intelligence literacy. It constructs a conceptual model framework and explores the relational paths among influencing variables, aiming to provide a theoretical basis for the advancement of AI literacy education in libraries and other educational institutions. [Method/Process] This study adopts a mixed-method approach that primarily integrates Structural Equation Modeling (SEM) and mediation analysis to explore the relationships between the factors that influence AIGC tool usage. A conceptual relationship model was constructed based on the Technology Acceptance Model (TAM), which is widely utilized model for assessing users' acceptance of new technologies. The study builds on this model by adding AI literacy as a key variable to examine its moderating role in shaping the students' use of AIGC tools. The data were collected via a survey disseminated to university students who have used AIGC tools. The survey incorporated a series of inquiries designed to assess constructs such as effort expectancy, performance expectancy, behavioral intention, AI literacy, and actual usage of the tools. The SEM approach was employed to assess the proposed hypotheses and to validate the relationships between the identified factors. Mediation analysis was employed to assess indirect effects between variables. [Results/Conclusions] The findings indicate that effort expectancy exerts a direct impact on the actual use of AIGC tools by students, and indirectly promotes usage behavior through performance expectancy and behavioral intention. Furthermore, AI literacy plays a crucial role in improving the conversion rate from intention to actual usage. Specifically, AI literacy significantly enhances students' acceptance of AIGC tools, especially in terms of increasing their practical ability to use these tools effectively. The research also identifies key factors that influence students' use of AIGC tools, such as performance expectancy, effort expectancy, and behavioral intention, and highlights the significant moderating effect of AI literacy on the relationships among these factors. This study provides empirical evidence for the effective integration of AIGC technology into the education sector and offers theoretical guidance for libraries and educational organizations on how to design AI literacy education programs that help students adapt to a digitally driven society. Future research may encompass a more extensive examination of the utilization of AIGC tools across different academic disciplines, with a particular emphasis on their implementation in specialized domains. Additionally, the proposed model may be refined to better accommodate a wider range of educational contexts and learning scenarios.

[Purpose/Significance] Research on the behavioral stimulation of online social platform interactions triggered by IP-based games on users' active learning and reading, the social demands within gaming communities and their derivative reading-sharing interactions constitute dual intrinsic motivations that promote autonomous reading behaviors. Exploring new developmental directions for reading promotion through digital game dynamics and group-based social guidance provides broader research perspectives for innovative knowledge acquisition and pedagogical learning paradigms. [Method/Process] Based on the game "Black Myth: WUKONG" as the research background, we collected relevant comments and original texts from four social media platforms. Using the LDA model for topic classification of the effectively collected data, users who demonstrated marked behavioral tendencie towards book-related engagement and reading activities attributable to the "WUKONG" game experience were manually identified from the aforementioned dataset. We explored the details of their social discourse and the behavior of user accounts through user-account backtracking, studying the factors that stimulate users' interest in reading and active reading behavior. [Results/Conclusions] Analysis of the five thematic clusters identified by the LDA modeling revealed that in the user behaviors focused on the theme of cultural exploration, 38.3% of the user behavior data showed increased exploratory engagement with original literary works and related content during "WUKONG" mediated group interactions. Whether this interactive exploration closely connects to reading habits needs further study. Further research has shown that a portion of users were influenced in their subsequent behaviors by this game and social interaction. Through text mining of user content on key topics, analysis revealed that 61.15% of user accounts had no prior engagement history, representing first-time participants in the cultural learning interactions of the "WUKONG" game. Notably, 23.7% of this cohort spontaneously expressed self-directed reading intentions during the game-social scenario. As the dominant subgroup in the dataset, their behavioral patterns suggest that gamified social platforms may serve as critical trigger mechanisms. It was found that the factors that stimulate users to read independently include competing for the right to speak in social interactions and obtaining gaming experiences. Accordingly, strategic practices for autonomous reading should accordingly be implemented through digital content guides, transmedia narrative interactions, and visual scene experiences. This research investigates the orienting mechanisms of digital games and community interactions in edutainment convergence, demonstrating both theoretical value and practical implications for user behavior analysis and reading promotion. While the study design ensured breadth of data collection, the heterogeneity of social attributes across platforms warrants further investigation. Subsequent studies should conduct platform-specific comparative experiments to strengthen the empirical foundation for behavioral intervention strategies.

[Purpose/Significance] To address the problem of semantic ambiguity and soybean breeding knowledge that needs to be revealed in depth, a structured knowledge model was established to thoroughly discuss the definition of key concepts and their interactions involved in the breeding process, standardize the definition and organization of soybean breeding knowledge, and promote the unified expression of knowledge. [Method/Process] By analyzing the characteristics of knowledge structure in the field of soybean molecular breeding, according to the seven-step method of Stanford ontology construction, the semantic model of soybean molecular breeding was established by using the ontology construction tool protege 5.6.3. A total of 48 classes were constructed in the soybean breeding concept ontology, which clarified the concepts and hierarchical associations among concepts under traits, compounds, enrichment pathways and growth classification. Seven types of causal relationships and three types of static relationships were defined. Finally, the ontology-based knowledge graph was presented based on a PubMed literature, and the knowledge unit with Dt1 gene as the central node was queried. [Results/Conclusions] This study integrated the existing knowledge base and ontology related to soybean breeding, established a knowledge model at the biomolecular level in the field of soybean breeding, and provided a certain reference for knowledge sharing and semantic integration in this field. Compared with the existing knowledge models, this study analyzed the characteristics of knowledge structure in soybean breeding, extracted the key entity types and relationship types in the process of hypothesis generation, and constructed an ontology model based on this, which could describe gene expression patterns in soybean growth and development more comprehensively. This is of great significance for discovering the key genes associated with specific traits and analyzing the molecular regulatory networks formed by traits, which will help to accurately design and optimize breeding strategies. The knowledge model constructed in this study could be applied to knowledge discovery, causal reasoning and other scenarios in soybean breeding, supporting experimental design and promoting interdisciplinary communication. The limitation of this study is that the ontology was constructed manually and no automated natural language processing method was used. In addition, in the subsequent use of soybean breeding knowledge model, it is necessary to keep up with the frontier of development in soybean breeding, expand new concept types, add new concept names and relationship names in time according to the knowledge description needs of field scientists, and regularly maintain and expand soybean breeding knowledge model.

[Purpose/Significance] With the rapid development of international academic digital publishing, ebook sales have surpassed those of print books since 2020. Many academic libraries in the USA are adopting e-preferred book collection development policies. In recent years, China's academic ebook market has been growing rapidly, as the well-known academic publishers such as Science Press and Tsinghua University Press have successively launched their own ebook platforms, and high-quality ebook integrator platforms such as Keledge and Cxstar have emerged, leading to a qualitative leap in both the quality and quantity of Chinese academic ebooks. The rapid development of the Chinese and English ebook markets has made collaborative collection development of print and ebooks feasible, which is considered to be a good solution to the tight collection budget and insufficient library space for Chinese academic libraries. The paper aims to propose a strategic direction and implementation path for collaborative collection development of print and ebooks, and provide a reference for the high-quality development of academic library collection development under the background of "Double First Class" construction. [Method/Process] The paper summarizes the main characteristics of SUSTech Library's three phases of book collection development, and introduces SUSTech Library's collaborative collection development practices of print and ebooks from four aspects: collaborative acquisition, collaborative management, collaborative services, and collaborative evaluation. A collaborative acquisition strategy should be based on four factors: collection assurance, patron needs, library space, and cost effectiveness. Collaborative management should redesign the business process from the aspects of funding plan, book selection, acquisition implementation, metadata management, and statistics. Collaborative services should be based on the needs, recommendations, and usage of user groups and individual users. Collaborative evaluation refers to a structured analysis on the print and ebook collections across five dimensions, including language, subject, publisher, book type, and year of publication. [Results/ [Conclusions] The paper puts forward suggestions from three aspects, such as top-level design, deep integration of business processes, and integrated management platforms. The academic libraries' management team should develop collaborative collection development policies and strategies from the top down. Deep integration of business processes should support optimization of organizational structure and job position adjustment, which replaces the traditional approach of defining job positions and responsibilities based on a single material type or business process. Integrated management platforms should support the integration of multiple metadata sources and business processes, and have strong knowledge discovery and service capabilities.

[Purpose/Significance] As part of the plan to build a better new digital life, information literacy (IL) is a survival skill in the information age. As a major repository of information resources, public libraries are the backbone of public IL education. The research on readers' knowledge construction behavior of IL education in public libraries is not only helpful for readers to improve their individual IL and self-learning ability, but also constructive for the development of the national IL system. At present, relevant research mainly focuses on the framework and practical suggestions of IL education, and rarely analyzes the construction of readers' knowledge in IL education from the perspective of knowledge management and readers' behavior. [Method/Process] From the perspective of readers' knowledge construction, this paper logically extends to the necessary knowledge scene transformation in public library IL education, and finally rises to the level of development strategy on how readers can realize knowledge construction and innovation in public library IL education. Information literacy education in public libraries also includes explicit and implicit knowledge. Information literacy education activities in public libraries focus on sharing explicit knowledge, enhancing the value of collection knowledge, but more attention should be paid to the exploration of implicit knowledge, enhancing knowledge transformation and innovation of participating readers. The path of reader knowledge construction in IL education can be divided into individual knowledge, team knowledge, organizational level knowledge. According to the different levels of knowledge construction, four knowledge transformation modes constitute the spiral process of knowledge innovation. Based on the MOA model, this paper analyzes the motivational factors, opportunity factors, and ability factors of readers' knowledge construction in the IL education in public libraries, as well as the constituent elements of the knowledge construction community and their interactive relationships from a multi-dimensional dynamic perspective. The model of readers' knowledge construction in public library IL education from the perspective of MOA analyzes the influence of motivational factors, opportunity factors, and ability factors on the readers' knowledge construction behavior in the knowledge construction community of IL education. Motivation points to opportunities and skills, suggesting that motivation leads readers to seek opportunities and develop necessary skills; motivation, opportunity and ability, and knowledge construction community all point to readers' knowledge construction behavior, suggesting that together they influence and promote readers' knowledge construction process. [Results/Conclusions] Readers' knowledge construction in the MOA model is a dynamic and multi-stage process. In the IL education activities of public libraries, readers gradually promote their understanding of knowledge and apply it to practical situations by stimulating motivation, exploiting opportunities, improving skills, and ultimately constructing knowledge. At the same time, through the feedback evaluation stage, further enhance knowledge construction strategies, update development goals, and continue reform and innovation. This study is only a theoretical extension of practical work experience, and does not involve rigorous and formal data verification and case study. In the next step, the questionnaire will be used to collect sample data, and through hypothesis testing and model fitting, the application practice of the MOA model in readers' knowledge construction behavior will be further verified.

[Purpose/Significance] Artificial intelligence-generated content (AIGC) is having a profound impact on the field of education. Currently, there are some problems in the digital education environment, such as incomplete digital infrastructure and slow digital transformation. The postgraduate education system has not yet fully responded to the changes in the educational environment in the intelligent era. In the era of AIGC, digital literacy has become an important component of graduate students' core competence, which is related to their future academic research and career development. In order to promote graduate students from the understanding of intelligent technology to the rational application, this paper explores a new way of talent training to adapt to the development of intelligent technology. Improving graduate students' literacy skills is important for adapting to the new demands of learning and research in the AIGC era. [Method/Process] Through a literature review and case analysis, this study explores the importance of digital literacy education for postgraduate students, and identifies challenges in educational content and teaching methods. Based on the successful experience of international universities, by analyzing the advantages and application scenarios of AIGC technology, combined with the current situation and existing problems of graduate students' digital literacy education, this paper proposes strategies and ways to improve graduate students' digital literacy. Based on the relevant theories of educational technology development, combined with educational practice and case analysis, this paper proposes an improvement plan for postgraduate students' digital literacy education in the AIGC era. [Results/Conclusions] In order to adapt to the changes brought about by AIGC technology, colleges and universities need to innovate in curriculum design, teaching paradigm and evaluation methods, and put forward strategies such as introducing AIGC-related knowledge modules, building interactive digital resources' intelligent recommendation platform, establishing interdisciplinary integration mechanism, strengthening ethical and legal education and establishing supervision mechanism, so as to promote the comprehensive ability of graduate students. Future research can further explore the deep integration path of AIGC technology and postgraduate students' digital literacy education, the high-order thinking practice direction of AIGC to promote digital literacy, and how to give full play to the positive role of AIGC technology in education while ensuring academic integrity. The shortcoming of this study is that because the development of AIGC technology is still in rapid evolution, some of the suggestions of the study may need to be adjusted in time according to the further development of the technology.

[Purpose/Significance] Limited by the constraints of traditional literature classification systems, scientific and technical literature information resources face problems such as inadequate disclosure and resource utilization. At the same time, high-quality user-generated data cannot yet be integrated as data elements into services related to scientific and technical literature services, which prevents these services from adapting to the context of the open science and meeting the diverse knowledge needs of readers. This study aims to harness the technological breakthrough potential of AI to build a consumer-end data system for scientific and technical literature information resources driven by AI and experts. This will help to overcome the shortcomings of traditional services, such as the lack of supporting reading information and low interactivity between users, with the hope of promoting the optimization process of scientific and technical literature information resource services. [Method/Process] First, the study analyzes the four-dimensional value representation of the consumer-end data systems for scientific and technical literature information resources, including the intrinsic value, the tool value, the academic value, and the future value of annotation data. Then, following the processing flow of consumer-end data, namely the collection phase, utilization phase, and management phase, the paper proposes principles for the construction of consumer-end data systems. Furthermore, the paper deconstructs and analyzes the risks associated with the involvement of AI in the construction of consumer-end data systems, including four types of risks: machine algorithm risks, annotation content risks, annotation data risks and application risks. Finally, based on the degree of AI involvement in data annotation work, three innovative models of AI plus expert collaborates with user to accomplish data annotation for scientific and technical literature information resources are designed: the AI plus expert-assisted data annotation model, the AI plus expert collaborative data annotation model, and the AI plus expert-led data annotation model. [Results/Conclusions] Under the AI plus expert-assisted data annotation model, AI acts as a tool to complete surface-level information processing based on rules set by experts to assist users in data annotation. In the AI plus expert collaborative data annotation model, AI completes the review of pre-annotation tags for scientific and technical literature information resources, transforming users from a self-generated tag mode to an AI-generated data tag evaluation and selection mode, with experts assisting in the final review of data tag quality. In the AI plus expert-led data annotation model, users provide data annotation requirements, experts guide the process, and data annotation is automatically completed by the AI4S platform.

[Purpose/Significance] Improving the policy and governance systems to promote the development of strategic industries such as artificial intelligence was explicitly proposed in the resolution of the Third Plenary Session of the 20th Central Committee of the Communist Party of China. In recent years, the conflict between AI companies' desire for copyrighted data and the copyright holders' protection of copyrighted data has become increasingly apparent. There have been a number of lawsuits and disputes around the world regarding copyright infringement caused by artificial intelligence. The dilemma of copyright protection of AI training data has become a difficulty and bottleneck that urgently needs to be resolved in the development of high-quality data system for AI. [Method/Process] Based on the academic research and industrial practice on the copyright protection of AI data, this study systematically summarizes six representative approaches to address the copyright dilemma of AI training data, and provides a comparative analysis of the advantages, disadvantages, and applicability of these approaches. The six representative approaches are: signing a license agreement by both parties, initiating special plans or forming alliances, introducing a copyright notice mechanism, introducing a copyright risk guarantee mechanism, replacing with synthetic data, and applying copyright detection tools to large language models. For the copyright dilemma of AI training data, there is no optimal solution that can both encourage the supply of AI copyright training data and protect the copyright of data. [Results/Conclusions] In order to provide helpful references for increasing the supply of AI copyright data, formulating relevant policies, and promoting related work, this study has proposed a concept of general implementation path to build a high-quality data system for AI to solve the copyright dilemma of AI training data, based on the comparative analysis of the above six representative approaches and combined with China's four unique advantages. These include: 1) Integrating existing platforms to build a national-level integrated service platform for copyright data for AI, with state-owned enterprises (SOEs) under the direct administration of the central government taking the lead in establishing a national copyright data alliance and connecting copyright data to the platform. 2) To collaborate with local pilots of data intellectual property rights, explore and promote comprehensive reform pilot programs of copyright data adapted to the development of AI, and continuously strengthen the cooperation efforts and willingness between AI enterprises and copyright holders. 3) The focus should be on principled or critical issues, establishing and improving legislation related to copyright data for AI and promoting industry self-regulation.

" AI for Science " (AI4S) is a new scientific research paradigm that deeply integrates AI technology with scientific research to promote the discovery of new knowledge and the solution of scientific problems. As the application of AI4S in the natural sciences and humanities and social sciences advances, its development line, opportunities and challenges, needs and tasks, and ways of realization deserve further discussion. In order to advance AI4S research, promote scientific and technological (S&T) innovation and progress, and facilitate the effective strengthening of the discipline of information resources management, our journal has invited seven experts to organize this academic conversation on AI4S. 1) Supporting knowledge services for AI4S: In the current landscape of intelligent knowledge services, the requirements for supporting AI4S have increased, including the need for multi-level knowledge discovery and acquisition, cross-disciplinary research and innovation, and user-friendly participatory services. In addition, knowledge service scenarios are moving towards diversification, complexity, depth, specialization, and personalization in ubiquitous knowledge discovery, generative content services, and multi-round interactive service exploration. In response, professional science and technology information organizations need to reassess the role of knowledge services in the AI4Science environment and their significance in comprehensively supporting the S&T innovation process. This involves establishing a broad literature perspective, deepening full-text knowledge elements, balancing universal and specialized depth, autonomously developing core products, and deeply engaging with professional fields to support interdisciplinary innovation. 2) As a knowledge base for AI4S: In the development of AI4S, S&T literature serves as a high-quality corpus of great importance and utility. The Documentation and Intelligence Center of the Chinese Academy of Sciences has developed the concept and general framework for an AI4S knowledge base utilizing S&T literature. It is dedicated to building four types of knowledge bases to support intelligent services such as evidence-based retrieval, situational awareness, inference prediction, and insight generation required for AI4S applications. In addition, to advance the AI for Science knowledge base, it is essential to actively promote the construction of an intelligent data system, develop an AI engine for technical literature knowledge, conduct key technology research on in-depth mining and intelligent analysis of S&T literature, and promote collaboration with scientific research units across various fields, leading AI companies, and teams of field scientists. This approach aims to fully exploit the innovative and developmental value of the discipline of information resource management. 3) Powering AI4S with scientific data: Effective aggregation of scientific data is the foundation for unleashing the powerful capabilities of AI4S. This is essential for libraries to adapt their roles and functions in the AI era and is a crucial prerequisite for catalyzing the transformation of scientific research services, deepening scientific research support, and accelerating S&T innovation. Currently, libraries face various macro and meso challenges in effectively aggregating valuable scientific data to provide support for AI4S. To address these challenges, the following ways can be pursued: defining the roles and functions of libraries in scientific data management; promoting a conducive environment for scientific data management; establishing a collaborative network for scientific data management; and enhancing the service capacity of scientific data management. 4) AI4S and intelligent language modeling for classical literature: AI4S technology can be used to analyze documents and texts, enabling a faster and more comprehensive understanding of a vast amount of historical documents and cultural materials. The development of intelligent language modeling for classical literature represents a significant breakthrough in the field of ancient literature research, bringing new opportunities and challenges. With the increasing popularity of multimodal and generative GPT models in the context of AI4S, the intelligent language modeling of classical literature will focus on integrating diverse information, enhancing adaptability, improving knowledge representation, and addressing a wider range of application scenarios. 5) Library Digital Scholarly Services for AI4S: The concept of using LLM-based AI4S and AIGC to drive the development of smart libraries is consistent with the vision for digital scholarly services in libraries, and presents both opportunities and challenges. Given the trends towards AI4S platformization and the characteristics of "middle-end" digital scholarly service, as well as the longstanding tradition of libraries in serving scholarly research, the reengineering path for the library's digital scholarly services platform includes three approaches: building an AI4S service platform independently, purchasing and utilizing third-party AI4S platforms, and promoting embedded knowledge services as a component of scientific intelligence. This innovative approach addresses the dilemmas of financial resources, human resources, cognitive and practical gaps, and emphasizes the importance of user needs in the AI4S environment. It also focuses on knowledge organization and service delivery to meet user needs in the AI4S landscape. 6) Historical evolution and logical structure of the scientific intelligence paradigm (AI4S): AI4S is a scientific paradigm change dominated by the full application of AI technology to various disciplines, and its logical structure includes "data+model"-driven, knowledge ecology created by machine conjecture, and application scenarios expanded by algorithmic thinking. In the era of digital civilization, AI4S-driven scientific progress and social development must carry forward the value of science and technology for the good, effectively select the theoretical arguments and proposals for extending AI4S to the field of social sciences and humanities, and improve the series of mechanisms for integrating human decision-making and machine intelligence. 7) Development opportunities and prospects of AI4S in the era of generative AI: With the advances in generative AI, pre-training algorithms and large-scale pre-trained models have provided significant opportunities for AI4S in various disciplinary domains. These technologies have shown immense potential and value for applications in diverse fields such as industrial inspection, robotics, and medicine. Additionally, it is crucial to emphasize the importance of key factors such as the constraints of technical implementation conditions for large pre-trained models, the sustainability of data/computing resources, and the transparency, fairness, and accessibility of the technology.

[Purpose/Significance] The continuous development of metaverse technology marks the transition of mankinds from information society to information civilization. How to understand the relationship between human beings, physical space and information space in the future society has become a key problem of the era. The mixed reality (MR) Technology is a new intelligent technology that integrates the advantages of augmented reality (AR) and virtual reality (VR), makes virtual objects coexist in the physical world, and integrates the functions of human perception, computer processing and environmental input. The new generation of MR technology has improved the traditional global understanding of digital reality interaction, and also has been bringing technological innovation opportunities for the development of smart libraries. Exploring the new application scenarios of MR technology is helpful in expanding the depth and breadth of the research on smart libraries. [Method/Process] By using the methods of literature review, content analysis and website analysis, this paper reviews the current research status of MR Technology in the field of library science at home and abroad. In addition, through practical cases, this paper summarizes the relevant experience and existing gaps in the application of MR Technology in domestic and foreign libraries. Therefore, it is clear that the research of this paper aims to further stimulate and release libraries' demand and potential for MR Technology. Specifically speaking, by examining the characteristics of high realism, more intelligent and omni-directional MR technology, this paper further explores the ability of smart libraryies in four dimensions of service, knowledge, experience and collaboration, which will contribute to building a new application scenario of smart libraries with the vision of MR technology. It is hoped that this paper can promote the formation of a new type of smart libraries that combines dynamic and static, actively data, blending virtual-real and multi-dimensional expansion. [Results/Conclusions] In the wave of rapid innovation of VR, the construction of smart libraries should be considered in four dimensions: problem orientation, theoretical supports, talent management and subject co-creation. It can provide a better understanding of the future smart libraries with the possible risks, urgent internal and external needs. It is expected to build a future ecological picture of the integration of smart libraries and MR technology. However, due to the limitation of the author's knowledge level and the lack of practical ability, this paper provides a relatively macro guidance. Libraries vary in their application of MR technology. On specific issues, we need specific analysis and different solutions. Therefore, in the future research, we will continuously improve and refine the research in this aspect, and provide reference basis and application value for the effective practice of MR technology in the smart libraries.

[Purpose/Significance] Investigating the influencing factors in the general requirements of public digital cultural service in Fujian Province can provide reference for its sustainable development in this field. Referring to the previous research, this paper took the lead in using the binary logistic regression model to study public demand for digital cultural services in Fujian Province, and selecting universities in Fujian Province as the research object. It provides a significant practical reference basis for the construction of public digital cultural service in Fujian Province, and also has a certain theoretical reference value for research related to public digital cultural service. [Method/Process] Culture is related to people's well-being and the all-round development of people. In order to meet the people's growing need for a better life and protect the people's basic cultural rights and interests, there are more urgent requirements. Public digital cultural service, in the form of digitalization, breaks the restrictions of time and space, and serves as an important magic weapon to get through the "last mile" of public cultural service and improve the accessibility of the service. Digital construction helps to enhance the accessibility of public cultural service, improve the coverage and dissemination efficiency of the service, and promote public cultural participation. On the basis of the relevant literature, the article intends to discuss the impact and mechanism of public digital cultural service, that is, which factors have an impact on public cultural needs? How do these factors affect the public digital cultural service? What is the impact? Under what conditions is the impact more significant? This study was carried out by combining the methods of literature survey, quantitative and qualitative analysis, and obtaining sample data of users through the questionnaire to analyze the statistics with the SPSS 21 software and verify relevant research hypotheses and regression models. [Results/Conclusions] It is found that resource, subject, platform, infrastructure, and service efficiency can effectively strengthen the requirements for the public digital cultural service in Fujian Province. In view of this, we suggest establishing diversified platforms for digital service, integrating cultural resources, enhancing the establishment of service personnel, strengthening promotion and popularization, optimizing the facility and equipment of public culture, and improving the environment of the places. In the analysis of the influencing factors of public digital cultural service, this study is not comprehensive enough. In the future, it is possible to sort out the factors affecting public digital cultural service more comprehensively, and a more comprehensive sample can be used in our study.