[Purpose/Significance] Data-enabled intelligent transformation and knowledge discovery have become new growth points for libraries to maintain development vitality and innovate service concepts. The efficient aggregation, orderly organization, integrated utilization and open sharing of massive multi-modal and heterogeneous data in libraries through data governance have become an important driving force for the intelligent transformation of libraries. [Method/Process] Based on the needs of smart libraries in regard to data management, services, and analysis and mining, this article analyzed the connotation, problems and challenges of library data governance under the background of intelligence transformation. [Result/Conclusion] It proposes a project-driven and application-driven implementation of a library data governance system. Based on the smart library management system, the data-enabled library smart transformation goal, and the principles of “data standardization, assetization, knowledge, and intelligence”, it suggests optimizing and controlling data platform architecture, data governance organizational mechanism, data standard specification system, asset management and operation mode, full-process data security and compliance governance, and data integration application. It aims to ensure data governance can better support the development of smart libraries and facilitate the intelligence transformation of library undertakings.

[Purpose/Significance] The fourth-generation evaluation theory, with its core concept of collaborative construction, has driven the change of scientific research evaluation thinking. Under the background of this theory, the evaluation of the research impact also pays more attention to the process of impact generation and dissemination, and emphasizes the interactions of different stakeholders in the process. [Methodology/Process] Driven by both the categorized evaluation system at the policy level and the change of evaluation theory at the theoretical level, this study proposed the categorized evaluation idea of selecting evaluation subjects based on the content attributes of scientific knowledge. It further verified the rationality of this idea through real case data. This study took REF2021 case data as the main source of analysis, and employed prompt learning to assist manual identification of government, enterprise, university and public stakeholders. Based on it, it explored the differences in the participation of different stakeholder types in the research impact generation process in terms of the distribution of participation and cognitive themes. [Result/Conclusion] The results demonstrate differences in the subjective cognition and realistic participation levels of the four stakeholder types in the research impact generation process. On the basis of the confirmed rationality of evaluation ideas, this study proposes suggestions for the selection of evaluation subjects based on disciplinary category from the specific case data, and provides new practical ideas for academic evaluation practices in China.

[Purpose/Significance] This study explores the cognitive transition characteristics of users in the exploratory search process and analyzes the users’ cognitive changes under different task types and search intentions. It contributes to a further understanding of the learning mechanism in the exploratory search process. [Method/Process] An experiment was used to record the participants’ search process on the video screen. The think-aloud method was used to collect the participants’ descriptions of the search process. The questionnaire gathered data on the participants’ personal information, task perception, and task answers before and after the search. Through coding of the video and textual data, the article analyzed the length and probability of users’ cognitive transiting paths across different task types, and the characteristics of these paths with different search intents. [Result/Conclusion] This study finds that the cognitive transition path is the shortest when searchers take procedural tasks. Searchers mostly initiate their cognitive transitions from a state of “understanding”, and application is the demarcation point between ascending and descending cognitive states. Analysis of user cognitive transition paths reveals significant variations across different search intents. Paths associated with information collection and information assessment exhibits the highest degree of complexity.

[Purpose/Significance] This study aims to extract structured item information from free-text clinical scales using ChatGPT without annotations, which efficiently advances the structuring and intellectualization of medical scale resources. [Method/Process] A framework for item information extraction was defined, including eight attribute types and considering the structural differences in clinical scale measurement concepts. A dataset was constructed by collecting 59 commonly used clinical psychometric assessment scale documents. Zero-shot prompt templates were designed based on measurement concept levels, and experiments were conducted using the official ChatGPT-3.5 and ChatGPT-4 interfaces. The extraction performance and possible influencing factors of different ChatGPT versions in processing different clinical scale texts were analyzed from multiple perspectives. [Result/Conclusion] The extraction performance for scale item sources is the best, with Micro-F₁ and Macro-F₁ scores of at least 98.90% and 97.83%, respectively. This is followed by response options, instructional guidance, and scoring rules, with item numbers and instructions showing moderate performance. Clinical explanations have the lowest performance, with Micro-F₁ and Macro-F₁ scores of 47.73% and 45.51%, respectively. ChatGPT-4 performs better overall, but the recall rate of some attributes is weaker than that of ChatGPT-3.5. The increase in measurement concept levels, dimensionality, number of items, and text length are found to reduce model performance. In summary, ChatGPT can efficiently assist in the structuring of medical scale resources, especially when dealing with simple scales.

[Purpose/Significance] Academic journals are widely used as a processing unit for identifying discipline structure. By identifying discipline subfields through journal clustering, it is possible to effectively reveal the intrinsic structural features of a discipline. From journal contents on the semantic correlation of articles, it proposes a new method of constructing correlation between journals, called journal article topic coupling, and a discipline structure identification model. [Method/Process] It employed the LDA topic model to identify the topic and its topic distribution. Based on this, it proposed a threshold-based method to construct journal article topic distribution, and adopted the t-SNE algorithm to obtain low-dimensional embedding of the high-dimensional distribution to address the difficulty of clustering journal by high-dimensional journal topic distribution. [Result/Conclusion] It conducts empirical analysis on 68,078 articles in 107 economics and management journals included in CSSCI from 2018 to 2022, and describes the model’s parameter selection and setting methods. The results demonstrate that the new method effectively utilizes article topic correlation on the semantic dimension for journal clustering and discipline subfields identification, divides domestic economic and management disciplines into 16 subfields, including 9 in economics, 5 in management, and 2 in the cross-field, along with an interpretation of the research scope of each subfield.

[Purpose/Significance] The current subscription fees for literature information resources in China are offered at discounted rates. But in the continuous development of global open access, China needs to pay high conversion fees to complete the comprehensive transformation of open access. University libraries are facing new challenges in the construction of literature information resources. [Method/Process] This paper conducted research from the perspectives of open access influence comparison, the transformative policies of publishing groups, and the funding of university literature resources. It proposed countermeasures research, including the construction and management of university publication information, calculation of open access transformation, and construction of open access transformative mode. [Result/Conclusion] University libraries should be cautious in open access transformation. The subscription-based publishing model has generally achieved a balance, and teachers and students can publish for free in hybrid journals, therefore, this paper proposes prioritizing support for publishing in high-quality, fully open access journals. Each university needs to carry out the management of its own publication costs, and conduct a comprehensive evaluation based on specific publisher policy, the number of university publications, and the price system of article processing charges. It provides direction guidance and case reference for university libraries to respond to the open access transformation.

[Purpose/Significance] This study aims to explore the specific mechanisms and implementation methods of value co-creation in university library user services, providing new perspectives for their sustainable development. [Method/Process] Based on the review of the concept and development of value co-creation, this study selected the comprehensive service center in Peking University Library as a case study. It focused on four aspects: the innovation of user-supported service concepts, the planning of institutional frameworks for resource integration, the construction of open and integrated service environment, and the development of a collaborative service ecosystem among participants. [Result/Conclusion] Actively promoting value co-creation in university library user services can better meet the users’ diverse needs and promote the sustainable development of library services.

[Purpose/Significance] This article investigates the cognitive and emotional factors influencing users’ willingness and behavior to disclose false information on social networks, so as to promote the healthy development of social networks. [Method/Process] It explored the complex mechanism of users’ disclosure willingness and behavior from the perspective of dual paths of cognition and emotion. It analyzed the data from 847 valid questionnaires using SEM and fsQCA. [Result/Conclusion] ①Engagement, perceived value, perceived risk, and self-efficacy positively affect the disclosure willingness and the disclosure behavior.②Emotional arousal positively influences users’ willingness to disclose information. Negative emotion leads to a stronger willingness to disclose false information. ③Cognitive factors make users more focus on information quality, while emotional factors make users more focus on the reputation of information sources. ④Self-efficacy and emotional arousal show positive regulation in the influence of disclosure willingness on disclosure behavior. ⑤Two paths triggering users’ willingness to disclose false information are found, with self-efficacy as the core factor.

[Purpose/Significance] It is crucial to explore the factors and pathways that render social media users susceptible to health misinformation. This helps understand the underlying psychological mechanism of these susceptible users when facing health misinformation, thereby aiding in enhancing their ability to identify such misinformation. [Method/Process] This study collected data through an online situational experiment. Based on the MOA model and the ELM theory, it employed fuzzy-set Qualitative Comparative Analysis (fsQCA) to investigate the configuration paths influencing social media users’ susceptibility to health misinformation. [Result/Conclusion] The results indicate that three configural types of users who are susceptible to health misinformation: the health-consciousness core-driven type, the popularity- driven core type, and the dual-driven type characterized by both high health consciousness and information popularity. Among these, high health-consciousness and the reliance on information popularity-based pathways emerge as pivotal factors influencing health misinformation susceptibility.

[Purpose/Significance] While the “renaming” of the “Library, Information, and Archives Management” has come to an end, how to reconstruct its sub-disciplines under the first-level discipline framework of “Information Resource Management (IRM)” is one of the important topics in front of the domestic academic community. The emergence of the “Information Resource Management Science (IRMS)” concept provides a new direction for the research on this topic. [Method/Process] The article adopts theoretical analysis method to explore the system structure of IRMS in depth from four aspects: discipline system, theoretical foundation, method system, and sub-discipline system. [Result/Conclusion] The research sorts out the discipline system of IRMS, improves its theoretical foundation, and method system. Based on the conceptual origin of IRMS as reflected in the two book series, the Modern Information Resource Management Series and Information Resource Management Series in the Age of Digital Intelligence, as well as the inheritance and innovation of “Library, Information, and Archives Management”, which is the main part of IRMS, it constructs two distinct sub-discipline systems.

[Purpose/Significance] This study aims to construct a comprehensive assessment framework to objectively measure, compare and analyze the quality and dynamic evolution trends of government open data in various regions. This framework will then be used to identify potential problems and solutions related to government open data quality management, providing reference for government data service optimization and data governance decision-making. [Method/Process] Relying on multi-indicator comprehensive evaluation theory and Delphi method, this article formulated government open data quality assessment indicators and their dimensions. Using the single-sample Wilcoxon test and combined weighting method, the availability, weights, and dimensional scores of the assessment indicators were analyzed to construct a framework for assessing the quality of government open data. [Result/Conclusion] This article evaluates the quality of open government data on the government websites in the sample areas in five dimensions: content, expression, access, protection and quality of use. Based on it, it analyzes existing problems, and proposes optimization countermeasures.

[Purpose/Significance] In the trend of sensory regression in digital age, libraries need to pay attention to sensory participation and sensory design in services to enhance the value and service effectiveness. [Method/Process] Using explanatory multi case study methods, it constructed an analytical framework based on sensory design and service design theories to explain the STEAM education cases in libraries and to verify and improve the theoretical framework. [Result/Conclusion] Through case studies, the study improves the theoretical framework of sensory design for library services. Starting from the dimensions of resources, users, and works, it analyzes application scenarios of sensory design in library service design and offers suggestions.

[Purpose/Significance] Large language models trustworthiness can ensure their reliable and safe deployment in key fields such as healthcare, education, and law, and gain the public trust. It is important to promote the healthy and sustainable development of generative artificial intelligence technology. [Method/Process] This paper uses the literature research to analyze the relevant literature on the large language models trustworthiness. It comprehensively analyzes the large language models trustworthiness from four aspects: its concept and connotation, its influencing factors, the challenges, and the “TRUE” strategy. [Result/Conclusion] The research on the large language models trustwortiness is still in the exploratory stage. Starting from its connotation, influence, challenges, it establishes a “TRUE” strategy system of information technology, information resources, information users and information environment, in order to promote the reasonable use of LLM and drive the development of generative artificial intelligence towards a better future.

[Purpose/Significance] In the current context of frequent major emergencies, the pivotal role of social media has become evident. Although its intelligent recommendation algorithms have increased the visibility of disaster information, they might also exacerbate the spread of internet rumors and the fermentation of group information herd behavior. Understanding the influencing factors of group information behavior in major emergencies under the intelligent recommendation algorithms can reveal the tendencies and decision-making mechanisms of group information following, enabling the formulation of more effective crisis management and emergency plans. [Method/Process] This paper combined content coding analysis with fuzzy-set Qualitative Comparative Analysis (fsQCA) methods, adopting an exploratory-then-confirmatory followed by a verification research strategy, and designed a sequential mixed research method. It identified the key factors influencing group information herd behavior in the context of major emergencies based on social learning theory. The fsQCA method was used to construct a configurational path analysis framework. [Result/Conclusion] The study identifies eight key factors influencing group information herd behavior during major emergencies, including observational learning, perceived social influence, recommendation algorithmic affordance, recommendation algorithm experience, perceived social value, perceived social identity, self-regulation, and self-efficacy. Based on these factors, it discovers three distinct types of information herd behavior in two categories: information herd behavior driven by herd mechanism factors, information herd behavior involved by triadic interactions and imitation of others, information herd behavior involved by triadic interactions and discount own information, and non-herd information behavior. These findings offer new perspectives for a deeper understanding of the role of social media in responding to major emergencies and provide theoretical support for optimizing intelligent recommendation algorithms on social media platforms in specific scenarios.

[Purpose/Significance] The analysis of public speech acts and sentiment dissemination in natural disaster crisis helps understand the acts intentions, acts patterns and psychological states of government social media users, and provides theoretical support and reference basis for governmental crisis management and public opinion control in crisis events. [Method/Process] Taking the “Typhoon Dusuri” event in 2023 as an example, this research integrated qualitative content coding, lag sequential analysis, cluster analysis, theme mining and other research methods to meticulously analyze 254 blog posts and 5036 comments from five government microblog accounts. [Result/Conclusion] In the natural disaster crisis, public speech acts are mainly concentrated in expressive and declarative categories, and there are three main speech act modes, information, relationship and sentiment at the same time. The public sentiment mainly shows homogeneous infection and negative extended transmission, characterized by temporal stages. Public sentiment levels vary across speech act modes, with information mode in lower sentiment level. The “action and rescue” blog topics significantly increase the public sentiment in all the three modes. Due to the dynamic nature of public participation in governmental social media and the difficulty of portraying the participation process in detail, the speech acts classification, lag sequence analysis and automatic clustering methods used in this study provide new perspectives and methods for public participation in crisis governance research.

[Purpose/Significance] Exploring the influencing factors and mechanisms of knowledge service effectiveness of science and technology think tanks can comprehensively enhance their service effectiveness, promote sustainable development, and maximize their value in decision-making consultation. The research will provide a reference for designing the scale and evaluation system of the knowledge service effectiveness of science and technology think tanks. [Method/Process] In this paper, it investigated the current status of knowledge services in science and technology think tanks through in-depth interviews on programmatic grounded theory. The collected raw data from the interviews were analyzed by three-level coding. Finally, it constructed the theoretical model of influencing factors and mechanisms of knowledge services effectiveness in science and technology think tanks. [Result/Conclusion] It finds that the knowledge service effectiveness of science and technology think tanks includes three aspects: the realization of application value, the deepening of theoretical research, and the formation of supply and demand mechanism. Basic resources (supporting force), wisdom synergy (security force), user demand (driving force), and service characteristics (constructing force) jointly determine the level of their knowledge service effectiveness. There is a significant mutual promotion and dependence relationship among the dimensional factors. Among them, user demand exhibits a radial characteristic in its influence on the effectiveness of knowledge services of think tanks and other factors, tending to the center of knowledge services. The demand-driven synergistic integration of diversified institutional resources has a significant impact on the think tank services effectiveness. It is conducive to easing the tense supply and demand relationship between “think tank-decision-making”. This idea need to be emphasized in future relevant policies and service practices.

[Purpose/Significance] Exploring the innovative development of red culture reading promotion in university libraries from the perspective of converged media is of great significance for relevant institutions to fully leverage the advantages of converged media communication matrix and carry out practical activities for promoting red culture reading. [Method/Process] A comprehensive survey was conducted on the current situation of promoting red culture reading in 42 “Double First Class” university libraries through online research, face-to-face interviews, literature reviews, and telephone interviews. The survey results were classified, statistically analyzed, and a framework was constructed by drawing on stakeholder theory and the logic of social marketing theory. [Result/Conclusion] This study identifies six key factors influencing the red culture reading promotion in university libraries including red resources, space, activities, stakeholders, communication media, and performance evaluation. It proposes an innovative path for the integration of converged media and red culture reading promotion from the aspects of red cultural resources integration, spatial integration, multi-activity integration, publicity integration, and interest integration.

[Purpose/Significance] This study aims to solve the problems of inconsistent standards and incomplete evaluation indicators of scientific and technological documents in the current Traditional Chinese medicine field in China. This article has established a clinical application value evaluation system, and has designed an evaluation system for scientific and technological documents in the field of Chinese medicine to help researchers screen high-quality literature and promote the progress of clinical research. [Method/Process] Based on the standardization of literature, the characteristics of measurement, the characteristics of traditional Chinese medicine, and the clinical practice guide, the evaluation indicator system was established. The Delphi method and Analytic Hierarchy Process (AHP) were employed to optimize the indicators and determine their respective weights. Indicators were identified by combining rule-based methods and deep learning. The value score of the clinical literature was obtained through weighted summation. Finally, 10 relevant articles were selected to test the effectiveness and feasibility of the system. [Result/Conclusion] The experimental results show that the scores generated by the system can reflect the clinical application value of the literature, the evaluation system is scientific and effective.

[Purpose/Significance] Trust among relevant stakeholders has become a key factor in determining the successful open utilization of healthcare big data. This study investigates the impact mechanism of trust on the stakeholder behavior, considering the factors of trust gains and losses, providing forward-looking references for improving the effectiveness of healthcare big data open use in China. [Method/Process] Focusing on the decision-making behavior of the data platform, users, and patients, and considering factors of trust gains and losses, this study established a tripartite evolutionary game model based on the analysis of the open utilization process. Simulation analysis was conducted using MATLAB, and countermeasure suggestions were proposed based on the equilibrium point analysis and simulation results. [Result/Conclusion] Gaining the trust of patients is fundamental for users to transparently use data. Enhancing the security of the research environment can fundamentally solve trust issues. Strengthening regulation and increasing the trust gains and losses for users contribute to a positive state of open utilization. While raising the trust level of patients in data platforms, it is more crucial to intensify constraints on user behavior. China may consider building a nationally-led platform for the open utilization of healthcare big data, strengthening the construction of a trusted research environment and actively promoting its application, implementing a data use registration system, and establishing a standard system, for effectively guiding the public to participate the collaborative governance of healthcare big data.

[Purpose/Significance] Exploring the mechanism and realization path of historical event traceability can help the correlation and integration of fine-grained, multi-source historical materials and support historical research. [Method/Process] This paper analyzed the mechanism of historical event traceability and, based on the nanopublication model and reusing the domain ontology, designed the Historical Event Nanopublication Model (HENM). Take the Nanjing Massacre as an example, it verified the effectiveness of the historical event traceability path. [Result/Conclusion] This paper finds that the historical event traceability contains two aspects of historical data retrospection and historical truth recovery. The former is realized through the association of historical events and historical data within the historical nanopublications model. The latter integrates historical event nanopublications with the key information of the historical events as a clue to realize the comparison, reasoning, and complementation of historical events

[Purpose/Significance] This paper systematically reviews and analyzes the relevant research on ChatGPT in the field of information resources management in China to provide reference for in-depth research and practical applications of ChatGPT to support the development of discipline. [Method/Process] Following the PRISMA(preferred reporting items for systematic reviews and meta-analyses) guidelines, it selected 219 research papers on ChatGPT in the field of information resources management from CNKI and Wanfang Data. Through descriptive statistics, it analyzed and addressed four key research questions: technical connotation, application and examples, impact and empirical evidence, and contribution to discipline development. Then, it proposed future research directions from three aspects: technological application, theoretical research, and disciplinary system. [Result/Conclusion] The results show that ChatGPT has significant technical advantages, but some limitations in function and performance. Its application prospects have gained considerable recognition, but the current research fields are limited and lack sufficient instance support. The impact of ChatGPT on the field of information resource management involves multiple aspects such as technological application, social impact, cultural value, legal regulation, and national security. Further empirical research is needed to verify its actual effectiveness. ChatGPT has mainly played a positive role in promoting the development of the information resources management.

[Purpose/Significance] The purpose of this study is to explore selective information behavior and attitude shift under the background of multiple information seeking. [Method/Process] This paper employed an eye-tracking experiment in which participants were presented with articles containing positive or negative views on the same topic. The selection and reading process, including eye-movement data, clicking and other behavioral data was recorded. After the experiment, participants finished the report and were interviewed. [Result/Conclusion] The results show that participants have the negativity bias in multiple information seeking, but they are unaware of this bias. Most participants show a negative shift in their attitudes. People with more positive attitudes change their attitudes more negatively. Difference in the type of material participants focuses on when reading positive and negative information influences the attitude change. The study will help enhance the understanding of the selective information behaviors and negative attitude shifts in multiple information seeking, and contribute to the improvement and optimization of the news system.

[Purpose/Significance] This paper probes into the factors influencing open science policy formulation in research institutions, points out the key issues, and offers recommendations for Chinese research institutions. [Method/Process] Firstly, the qualitative research method is adopted to construct the theoretical model of the factors influencing open science policy formulation in research institutions. Then a questionnaire survey is carried out based on the model, and the key issues of policy formulation are pointed out, and specific suggestions are provided for policy formulation. [Result/Conclusion] The formulation of open science policy in research institutions needs to conform to the national policy orientation, clarify the guiding principles of the policy, improve the decision-making and judgment ability, balance and coordinate the interests of multiple stakeholders, and guarantee the input of material resources，so as to give full play to the main role of research institutions in the process of open science.

[Objective/Significance] The analysis of China’s internet healthcare policy’s content structure aims to provide a theoretical basis for the improvement and optimization of the follow-up policy system. [Method/Process] This article took China’s central policy text in the field of Internet health care as the research object. By combining collaborative governance theory, patient demand hierarchy model, policy tool theory and KeyBERT model, the four-dimensional policy feature analysis framework of collaborative governance, demand hierarchy, policy tool, - policy theme was constructed. The framework was then employed to analyze the structure and evolution of policy content, and identify the policy focus and orientation. [Result/Conclusion] The internet medical policy presents a centralized coordination structure, a focus on meeting basic demand, an imbalance in its policy tool structure and comprehensive coverage of themes. In the future, it is necessary to promote the functional integration of policy implementation bodies’ collaborative governance structure, meet the higher-level needs of policy objects, optimize the internal composition structure of policy tools, and promote the deepening and elaboration of policy coverage topics.

[Purpose/Significance] Social media is an important channel for the dissemination of social cognition and social value. The hot topic system related to “library” reflects the current public’s concern and value trend for the library. Analyzing these topics can provide valuable reference for libraries, broaden the breadth of cultural services and enhance public attention. [Method/Process] This paper examined the hot topics of “library” and their associated comments on Weibo hot search list. With the text mining software (GooSeeker) and social network analysis software (UCINET), this paper explored the thematic characteristics of “library” hot topics from the perspective of the relationship among topic leader attributes, Weibo topic topics, emotional comments and keyword clustering. [Result/Conclusion] The hot topic of “library” encompasses the predominant scholarly investigations and ongoing research areas within the field of library science, corresponding to the modern advancements in society. The proportion of the emotional topic is close to the proportion of the emotional comment. This indicates that positive topics can bring positive comments, and vice versa.

[Purpose/Significance] The burgeoning number of patents poses significant challenges to patent retrieval, highlighting the urgent need for advanced computational techniques to identify similar patents. [Method/Process] This paper proposed a multimodal feature fusion method for similar patent identification. It utilized the BERT-wwm model and the ResNet-50 model to extract textual and image features of patents, respectively. By integrating self-attention and cross-attention mechanisms, the method effectively harnessed intra-modal feature information and inter-modal interaction information. Based on these, the model was trained and optimized for the similar patent identification. [Result/Conclusion] Empirical tests using IPC category “C08F10/00” data demonstrate that the model achieves an accuracy of 80.03% and a recall rate of 82.01%, outperforming baseline models. In simulations of similar patent identification, the model reaches a recall rate of 88.89%, indicating superior practical performance. The fusion of textual and image modal features significantly enhances the accuracy and efficiency of similar patent identification. This approach facilitates improved patent retrieval efficiency, accelerates the patent examination process, aids in patent alert analysis, and strengthens intellectual property protection.

[Purpose/Significance] Computational reproducibility is the cornerstone of reliable and credible research. To investigate and analyze data policies, data availability and reproducibility methods of journals and conferences in computing field can provide references for promoting data sharing and solving computational reproducibility issues. [Method/Process] With web survey research and content analysis method, it analyzed journal data policies and conference data policies. It used web crawler to obtain data availability statement of journal article and analyze the current situation of data availability. Then, it summarized computational reproducibility methods. [Result/Conclusion] Most journals and more than half of the conferences in computing field have data policies, but the intensity of data sharing attitudes still needs to be improved. Journals or conferences with higher level are more likely to have data policies. Compared with journals focusing on data sharing issues, conferences pay more attention to the problem of computational reproducibility. The data availability statement promotes data sharing, but there is still a gap between data sharing practices and data sharing policy requirements. Computational reproducibility methods include data sharing, expert review, setting rewards, paper submission checklist, calling for reproducibility papers and so on.

[Purpose/Significance] Through an analysis of typical cases such as the American Authors Guild v. Hathi Trust case and Cambridge University Press v. Albert case, this paper explores the implications of American jurisprudence in determining the fair use in controlled digital lending in libraries. [Method/Process] Utilizing a case study approach, this research delves into the primary considerations of American courts in adjudicating cases involving CDL in libraries. These considerations include the purpose and nature of use, the nature of the work, the quantity and substantiality of the portion used, as well as market effects. Furthermore, by comparing how the courts interpret and apply the fair use principle in different cases, we aim to uncover patterns and trends. [Result/Conclusion] The study finds that American courts tend to consider multiple factors when determining whether CDL in libraries constitutes fair use. While upholding copyright protection, the courts also strive to satisfy the public’s legitimate need for information access. These precedents not only provide significant guidance for libraries in the United States to conduct CDL, but also offer valuable references for libraries in China when dealing with similar issues.

[Purpose/Significance] General information literacy competitions have gained widespread attention due to their competitiveness and interactivity. This study explores the current situation and development models of information literacy competitions, and provides reference and guidance for the development of such competitions. [Method/Process] It conducted a literature review and online research to collect the data and analyzed information literacy competitions from 2020 to 2022 with a multi-dimensional statistical analysis approach. It focused on organisational structure, competition models and other aspects with the tag analysis method. [Result/Conclusion] This study reveals the characteristics of domestic information literacy competitions in terms of overall quantity, competition scale, organizational structure, target audience, competition themes, disciplinary subjects, competition schedules and formats, and competition outcomes. It proposes a comprehensive competition model of “teaching-training-competition-evaluation” under the broad background of information literacy.