Based on the Information Adoption Model, this paper constructs a model of factors influencing scientific data reuse in the field of machine learning. We select two types of scientific data platforms—open science community platforms and scientific data sharing platforms—to collect data. Then we empirically examine the impact of dataset content quality and data source credibility on scientific data reuse, as well as the moderating effect of platform types on the relationship between data source credibility and scientific data reuse. This paper is of great significance for improving the construction of scientific data platforms and promoting the reuse of scientific data.

The study aims to explore the researchers’ requirements for the reuse scientific data and to identify priority needs to enhance data reuse service capabilities and improve the effectiveness of data reuse. A systematic review of existing literature on scientific data reuse was conducted, supplemented by interviews and expert consultation, to identify 14 key data reuse requirements. Utilizing the Kano analysis method, combined with Kano categorization, mixed categorization and Better-Worse coefficient, the study categorized these requirements and established their priorities. The results show that among the 14 identified requirements, 2 (such as data availability) are must-be requirements, one (data rules) is a performance requirement, 5 (such as data sources) are attractive requirements, 4 (such as data background) are indifferent requirements, and 2 (such as data quality) are multi-attribute requirements. Based on these findings, suggestions and optimization strategies are proposed for stakeholders involved in scientific data reuse to improve reuse services.

In the era of open science, the open sharing of scientific data has become an inevitable requirement, with data reuse as its main goal. Although a variety of scientific data open sharing platforms have been constructed at home and abroad, there is still a lack of in-depth research on the relationship between the effectiveness of data reuse and the characteristics of data openness on these platforms. Focusing on the field of geoscience, this paper quantitatively analyzes three scientific data platforms— National Tibetan Plateau Data Center, NCAR Research Data Archive, and Figshare—with the goal of identifying the key factors affecting scientific data reuse. The findings reveal that data quality significantly impact the reuse of scientific data. Accordingly, this paper proposes strategies to promote scientific data reuse from four perspectives: data platforms, researchers, libraries, and journal publishers.

Joyce G. Saricks is an important figure in the field of readers’ advisory in American public libraries. By analyzing Saricks’ thoughts on readers’ advisory, it is evident that she emphasizes the leisure-orientated nature of readers’ advisory service. She puts forward Appeal Factor Theory, which describes bibliographical information based on the reading experience. Additionally, she proposes a framework for librarians’ competencies in readers’ advisory services, which includes the ability to read and think from the perspective of attracting readers, the ability to communicate about reading, and the ability to write book reviews. Saricks’ contributions to readers’ advisory reflect the combination of theory and practice, and have significantly advanced the field.

In order to improve the efficiency and quality of indexing, an experimental method using generative artificial intelligence is applied to address the shortcomings of traditional rule-based and probabilistic indexing software. A scheme for indexing using the retrieval-augmented generation of generative AI is proposed. Specifically, the journal volume is used as a unit, and the full text is subject-indexed based on indexing words derived from the abstracts of the papers by utilizing a large language model. The paper presents the design of an article abstract indexing database system, which can realize textual concept extraction and subject indexing based on the large model of massive knowledge emergence and reasoning capabilities, as well as key information and emerging knowledge extracted from abstracts. Additionally, this paper explores practical ways to associate index and abstract with academic norms and evaluation, demonstrating the potential value of generative AI in the field of indexing. It provides insights into promoting the application of generative AI technology in library and information science.

As global informatization has permeated all stages of resource distribution, advances in digital technology result in major changes in traditional document production structures. The growing demand among users for enhanced value-added services calls for the reconstruction of document resource guarantee system. This study presents a framework for the system reconstruction based on three aspects: system design, management practices, and operational forms. By leveraging a large language model, the study analyzes the development background and internal demands of the reconstruction, establishes a new operational model and examines the operational mechanism of the large language model. The reconstructed model enables intelligent data mining, quality content production, and value-driven information training. Furthermore, it enhances user knowledge guidance and object precision services, offering references for the intelligent evolution of the document resource guarantee systems.

With the increasing standardization and normalization requirements in the industry, the standard literature in the library collection is constantly increasing. The International Standard Classification Number and the Chinese Standard Classification Number are important ways to search for standard literature. The CALIS Joint Cataloging Center and National Library of China do not have clear rules for the classification and indexing of standard literature. In the joint catalog database of CALIS and National Library of China, standard literature only refers to the classification number of the Chinese Library Classification, lacking the professional classification number of standard literature. Cataloging personnel should combine the characteristics of standard literature and use the 686 field attributes of CNMARC format to index the classification of standard literature in a more standardized and complete manner.

Taking Jiashan Library’s “Amazing Parents” reading service project as an example, this paper explores the service practices of public libraries that focus on parents and supporting family education. The project centers on parents, with four key focus areas: parental awareness, parental abilities, parental cooperation, and parental actions. Through a case study method, the paper introduces the background, three major sections, and three major measures of the “Amazing Parents” reading service project, along with its implementation effects. It analyzes the project’s characteristics and extracts key dimensions, ultimately developing service strategies for public libraries to effectively focus on parents and assist in family education based on these four focus points.

With the integration of digital technologies into middle school students’ reading experiences, understanding the current state of digital reading literacy among secondary school students and their individual influential factors is crucial for enhancing immersive digital reading. The article empirically analyzes the digital reading literacy and its influencing factors among 701 middle school students through a questionnaire survey. The findings reveal that overall digital reading literacy among these students is strong, with a trend towards visual and audio-visual co-mingling in reading practices. In addition, there are significant differences in digital reading literacy, self-efficacy, metacognitive strategies, and cognitive strategies among students of different grades. The study suggests that the government should promote the integration of digital reading into the quality education system, provide digital reading curricula in schools, foster reading habits within families, promote the synthesis of digital reading literacy with broader digital literacy, and strengthen the digital ethics and morality among secondary school students. These measures could improve both digital reading literacy and overall digital literacy among secondary school students.

Disinformation—deliberately spreading false information to mislead the public—is presents a significant challenge today, impacting public sentiment and national information security. Libraries face particular challenges in addressing the issue. The paper defines disinformation from the perspective of library and information science, clarifies its fundamental concepts, and explores library practices in disinformation governance through literature review and website survey. It proposes a practicing framework for library involvement in disinformation governance, focusing on four dimensions: resources, users, technology, and management. The framework includes strategies for developing specialized resource navigation, establishing targeted training courses, improving feasible operation methods, and creating standardized action guidelines. In order to improve disinformation governance, libraries should adopt a holistic approach that considers five areas: structure deployment, professional authority reconstruction, cognitive and perceptual shifts, advancements in information technology, and collaborative governance.

Scientific detection is a fundamental aspect of preserving ancient books. Establishing standardized work norms for the scientific detection of ancient Chinese book paper is an urgent task in this field. This study reviews the scientific detection methods for ancient paper from four aspects: basic indicator detection, fiber analysis, morphology analysis, and chemical composition analysis. It also explores the feasibility, reference standards, and experimental parameters of commonly used methods in the scientific detection of ancient paper. Additionally, the article addresses the safety principles necessary for the detection of ancient books. Based on these insights, the study proposes work norms tailored for the scientific detection of ancient Chinese book paper.

Jianxiao Huiji Fangshu has been always confused with Xiuzhen Fang in the process of spread, and the descriptions in ancient and modern edition are different. This book has been collected in the library of Shanghai University of Traditional Chinese Medicine. Through the analysis of biography experience of the compiler and proofreader, as well as some physical characteristics such as the preface and the end of the volume, it can be seen that the confusion between the two books is due to the forgery activities of the bookseller to falsify the preface and title of the book. To investigate the content and source of Huijifang also confirmed that this book was completed during the Jiajing period of The Ming dynasty.

This article analyzed 104 ancient books in the Bookstore of Li Guangming collected by Jinling Library, supplemented by local chronicles, letters, genealogies, archives, and other materials, to explore the historical evolution of the Bookstore of Li Guangming. The focus is on exploring the background of Li Guangming Bookstore’s establishment, changes in store location, development strategies, and reasons for its decline. In addition, based on the ancient books collected by the Capital Library of China and Qingdao Library, a more accurate survival time of the Bookstore of Li Guangming has been obtained which fills some gaps in academic research.