[Purpose/Significance] This paper summarizes the main contents of the U.S. OSTP national OA policy, analyzes the implementation mechanism of the new version of the national OA policy in the United States, judges the strategy understanding and policy propositions of the United States regarding OA, and proposes enlightenment and suggestions for China. [Method/Process] Utilizing the National Open Access Policy documents issued by the U.S. OSTP, this study conducted a comprehensive examination and systematic analysis of the U.S. National Open Access Policy, focusing on its policy content and implementation mechanisms. Additionally, it incorporated the research reports submitted to Congress by the OSTP and recent practical developments to evaluate the U.S. government’s strategy understanding and policy propositions regarding open access. [Result/Conclusion] The United States has elevated open access to the level of national strategy and comprehensively promoted the implementation of the new version of the national open access policy. China should also re-examine the significance of formulating its national open access strategy, clarify its policy proposals on open access, design scientific reasonable policy content, accelerate the introduction of open access policies, and establish relevant supporting measures to promote policy implementation.

[Purpose/Significance] This study aims to construct an evaluation index system for the sense of personal information security, providing a reference for scientifically assessing the public’s sense of personal information security. [Method/Process] Based on social cognitive theory, this study clarified the conceptual connotation and dimensions of the personal information security sense. Then, the evaluation index system was constructed using a combination of literature review, grounded theory, Delphi method, and analytic hierarchy process (AHP). An empirical analysis was taken to assess the public’s sense of personal information security. [Result/Conclusion] The evaluation index system for the sense of personal information security comprises five primary indicators: self-stability in personal information security assessment, self-efficacy in personal information risk response, satisfaction of personal information security needs in interpersonal communication, perceived control over personal information processing activities, and behavioral tendency towards personal information security. Additionally, it includes 11 secondary indicators and 42 tertiary indicators. The study finds that the public’s sense of personal information security exhibits distinct distribution characteristics in terms of index scores and demographic differences.

[Purpose/Significance] In the context of digital intelligence transformation, this paper analyzes the trend and challenges of intelligence work, proposes a logical framework for empowering intelligence work with trustworthiness to provide a reference for the development of information science. [Method/Process] The paper analyzed the development of intelligence work under digital transformation from the perspective of the “information turn”. On this basis, it summarized the challenges encountered during intelligence collection, analysis, and service. It then clarified the trustworthiness standards for intelligence work and constructed an empowerment logic framework from three dimensions: thinking domain, management domain, and process domain. This framework was to enhance the trustworthiness of empowerment while ensuring its efficiency. [Result/Conclusion] By leveraging the combined efforts across various dimensions, including trustworthy thinking, trustworthy assessment, trustworthy disclosure, discrimination mechanisms, interpretative mechanisms, and adaptive mechanisms, it is helpful to effectively address the challenges of trustworthiness in intelligence work, such as the discernibility of intelligence collection, the explainability of intelligence analysis, and the self-adaptability of intelligence services, thereby aligning with the development of the “information credibility shift” “ information computation shift” and “information integration shift”. Moreover, future research should further address key issues in the construction of the trustworthiness empowerment logic framework, including the development of intelligence trust theory, the identification of trustworthy methods in intelligence, and the refinement of intelligence support mechanisms.

[Purpose/Significance] This paper attempts to put forward the concept of intelligent data to provide ideas and path references for data intensive and data-driven S&T intelligence work under the new paradigm. [Method/Process] This paper comprehensively summarized relevant intelligence work practices, analyzed and defined the concept and characteristics of intelligent data, clarified its generation and circulation mode, and put forward its construction principles, construction and service mode. And then, it explored the construction and service of intelligent data facing S&T strategic decision-making scenarios in the form of typical cases. [Result/Conclusion] Intelligent data is the “scientific research data” in the process of intelligence research and service, and is the core production element of data-driven intelligence research and services, which mainly includes three types, namely, intelligence raw data, intelligence core data, and intelligence derived data. It condenses the precise understanding and insights of intelligence personnel on strategic needs, contains longterm accumulation and precipitation of intelligence service. Intelligent data is characterized by decision scenario orientation, embedded expert wisdom, rich data types, high intelligence value density and strong extensibility (SERVE). Its construction should be guided by decision-making scenarios and deeply coupled with decision-making problems. The construction process should follow the principle of experience to intelligence, explicit to implicit, and result-oriented to process-oriented, and the aim of data storage, methods reuse, evidence-based conclusion and knowledge transfer. It is carried out from four aspects: decision-making scenario preset and analysis, decision-making problem combination and solution formulation, intelligent data construction, intelligence service effectiveness feedback and data upgrading. Taking the construction of intelligent data in the context of S&T strategic decision-making such as export control and major S&T issues as examples, this paper expounds the idea of intelligent data construction and the service effect of strategic intelligence work driven by it.

[Purpose/Significance] This paper analyzes the current situation of smart reading services on academic platforms, and explores how AIGC technology can empower libraries with smart reading services. It aims to provide a reference for upgrading smart academic reading services in libraries. [Method/Process] This paper adopted content analysis to conduct two rounds of coding analysis on smart reading services provided by nine typical academic platforms. The analysis focused on five indicators: reading material supply, auxiliary reading, reading applications, reading communication, and behavior management. In response to the existing problems and considering the entire reading process for academic user, this paper proposed a path for AIGC technology to empower smart academic reading services in libraries. [Result/Conclusion] Big data and artificial intelligence technology are promoting the smart services of academic platform in the reading materials supply, auxiliary reading, and reading applications. However, the application of these technologies in reading communication and behavior management remains limited. In the “five situations” of reading: seeking, reading comprehension, reading application, reading communication, and reading behavior management, AIGC technology can empower smart academic reading services in libraries in five aspects: high-quality academic resource, reading cognitive strategies, writing assistance, reading communication, and reading behavior management.

[Purpose/Significance] Exploring the construction of a set of scientific and feasible evaluation indicator system aims to realize the quantitative evaluation of the service effectiveness of the preprint platform. [Method/Process] Firstly, based on the E-S-QUAL model and combining with the research context, this study explored the construction of the evaluation indicatorsystem of preprint platform service effectiveness. Secondly, this study adopted the hierarchical analysis method to assign weights to the evaluation indexes at each level. Then, it selected arXiv and ChinaXiv as the sample platforms, and used the fuzzy comprehensive evaluation method to carry out empirical evaluation of the platform service effectiveness. Finally, it summarized the evaluation results, and drew relevant research conclusions. [Result/Conclusion] The evaluation indicator system of service effectiveness of the preprint platform constructed in this paper contains five first-level indicators of efficiency, system availability, fulfillment, privacy and empathy and 17 second-level indicators such as review cycle. The fulfillment and system availability in the first-level indicatorsaccount for a higher weighting than the content accuracy and interface friendliness in the second-level indicators. And the evaluation index system has strong scientific, operability and applicability.

[Purpose/Significance] As a key component in the circulation of data elements, there are some dilemmas in data product trading. Exploring and sorting out the corresponding dilemmas and solutions are conducive to the effective operation of data trading market and the efficient development and utilization of data elements. [Method/Process] This paper analyzed the definition and characteristics of data products, sorted out three dilemmas in current data product trading, that is, information asymmetry, data valuation and pricing, and data ownership determination. Then, it presented the generation mechanism of these dilemmas and summarized the existing solutions to the data product transaction dilemmas. [Result/Conclusion] From the perspective of the closed loop among the data product characteristics, the resulting trading dilemmas, solution approaches, and the processing of the dilemma generation mechanism, this paper constructs an analysis framework for data trading dilemma and their solutions, and reviews the relevant theories and practices, in order to further enrich the basis of data transaction theory and provide effective reference for data transaction practice.

[Purpose/Significance] Public data opening and sharing is a critical factor in the development of national public services and digital construction. In the era of data intelligence, exploring new research methods and implementation pathways is essential for integrating the value creation and intelligent data sharing. This article aims to elevate the level and efficiency of public data opening and sharing, and meet the public data needs of society and individuals. [Method/Process] With the literature review, this study explored the development and research status of public data opening and sharing in China. By incorporating the five principles of information economics, it analyzed the value of data centers in the context of public data opening and sharing. With the empirical research, this study designed a model for public data opening and sharing based on data centers from overall frameworks, strategic pathways, and practical key points. [Result/Conclusion] The construction of a public data opening and sharing model based on data middle platform involves the restructuring and reengineering of the entire business process upon the public data repositories. It needs to be fully guaranteed from organization, standardization, procedure and security. The model facilitates the reuse of overall public data capabilities, to better meet the public data needs of society, organizations, and individuals.

[Purpose/Significance] Traditional bibliometric indicators fail to capture the distinctions between the internal and external dimensions of academic collaboration networks. This paper introduces new metrics, such as external citations and the external h-index, for evaluating the external impact of scholarly collaboration networks, providing a foundation for a more authentic assessment of scholars’ academic influence. [Method/Process] Utilizing data from the American Physical Society, which includes 463,348 research papers and 234,086 disambiguated authors, this study extracts scholars’ ego-centric collaboration networks from the global network. It distinguishes between internal and external influences within these networks and introduces metrics such as the external citation count and the external h-index. These are tested for consistency against traditional bibliometric indicators and validated using data from prestigious physics awards such as the Nobel Prize, the Wolf Prize, and the Dirac Prize, to demonstrate the effectiveness and superiority of the external impact metrics. [Result/Conclusion] The study reveals significant disparities in the distribution of internal versus external influence within scholarly collaboration networks. The proposed external impact metrics introduced are highly consistent with traditional indicators. Convergence validity analysis shows that the external citation count and external h-index are more precise in identifying award-winning scholars compared to traditional metrics. These findings suggest that the external influence of collaboration networks reflects the true impact of scholars and plays a crucial role in academic achievements. The new metrics proposed here offer insightful implications for constructing future talent evaluation systems and breaking away from the “five only” criteria, providing a pathway for reform in academic assessments.

[Purpose/Significance] This study proposes a hierarchical method for predicting the academic impact of papers by integrating their academic contributions and innovative value, based on the knowledge information extracted from the papers themselves. This method provides a more comprehensive assessment for the academic impact of articles. [Method/Process] To evaluate papers based on their content, it first selected conventional bibliometric indicators from the papers themselves. It then employed a prompt-based fine-tuning approach for a large model to extract academic contributions from the paper abstracts and developed metrics to represent the innovative value of the papers, including knowledge heterogeneity, knowledge outlier, knowledge frontier, and knowledge growth. These vectorized academic contributions, with bibliometric indicators and innovative value metrics, were used as inputs for a machine learning algorithm. The algorithm, optimized for performance, predicted the probability of a paper belonging to a high-impact category. Papers were then classified into ten levels (A-J) based on this probability. Finally, it used the SHAP interpretative framework to further analyze the influence and direction of academic contributions, innovative value, and bibliometric indicators on the impact of papers. [Result/Conclusion] The innovative value of a paper is the most important factor in predicting its academic impact, followed by academic contributions, with bibliometric indicators being the least important. The method proposed in this paper significantly enhances the accuracy of predicting the academic impact of papers.

[Purpose/Significance] Based on the existing practical experience, this study explores and summarizes the practical path of evidence-based policy making in science and technology, and looks forward to its future development. [Method/Process] This study adopted the literature review to clarify the connotation and extension of evidence-based policy-making in science and technology, and sorted out the types of policy evidence, evidence grading and recommendation standards. Through the summary, it innovatively put forward the practical path, made an in-depth analysis from the aspects of evidence acquisition, evidence grading and evidence evaluation, and verified the feasibility of this path through case analysis. Finally, it put forward some suggestions for the future development of evidence-based policy making in science and technology. [Result/Conclusion] The proposed practical path reveals the feasibility of integrating evidence-based policy-making model into science and technology policy making, and provides some references for policy making in science and technology field.

[Purpose/Significance] The release of the new edition of the Library Service Declaration has scientifically positioned library service, and declared and committed to the standards and value pursuit of library service to society and readers. It is a milestone in the development of China’s library industry and provides clear direction for library service. [Method/Process] Guided by the Declaration, this article comprehensively examined current service practices, established a scientific outlook on development, resources, readers, and services, conducted indepth investigation and research, identified strengths and weakness, clarified direction, and standardized development. [Result/Conclusion] Taking the “Declaration” as the development goal and basic value pursuit of library construction, the university libraries should enhance service capabilities and establish a new pattern of high-quality services, consolidate the foundation and cultivate the quality of services, innovate and implement new practices for high-quality library services. Through improving the details, optimizing the service, it is necessary to build a more reader friendly and down-to-earth library service system, and promote the high-quality development of university library services.

[Purpose/Significance] With the growth of intelligent decision-making application scenarios, explainability research has gradually become a hot topic. In order to clarify the current research status of explainability in intelligent decision-making and propose feasible paths, reviews the relevant literature on explainability of intelligent decision-making from the perspective of human-computer interaction. [Method/Process] This article used content analysis method for literature coding, and summarized the three main types of literature in this field, four types of explainable information output, and evaluation indicators from both system and user aspects. [Result/Conclusion] Through literature review, a hierarchical framework for explainability of intelligent decision-making is proposed, which divides explanation into three levels: reactive explanation, interactive explanation, and meta explanation. The level of explainability can be improved through explanation evaluation, interaction design, effect testing, and heuristic intervention.