Journal of Library and Information Science in Agriculture

Practice and Reflection on Scientific and Technological Strategic Intelligence | Open Access

LENG Fuhai

2024, 36(5): 4-13. DOI: 10.13998/j.cnki.issn1002-1248.24-0432

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[Purpose/Significance] The new round of technological revolution and industrial transformation is accelerating, and its impact on national development and security is becoming deeper and wider. The complexity and uncertainty of the technological innovation system are highlighted, and the technology policy agenda is also undergoing a transformation in order to cope with the increasingly fierce international technological competition. In order to identify the trend of technological development, countries generally engage in data-driven strategic intelligence practice. [Method/Process] Through research on the standard Innovation Management - Tools and Methods for Strategic Intelligence Management - Guide published by the International Organization for Standardization, the Science, Technology, and Innovation Policy Agenda published by the Economic Development Cooperation Organization, Safeguarding the Future of the United States: Framework for Key Technology Assessment issued after the recent national key technology assessment in the United States, The 2023 EU Industrial R&D Investment Scoreboard by the EU, the Japanese R&D Overlook Report, and the Scientific Structure Atlas of the Chinese Academy of Sciences, this study is focused on how to develop and utilize scientific and technological strategic intelligence to support the "evidence-based decision-making" agenda in the report development process. [Results/Conclusions] The essence of technological strategic intelligence is to provide data, knowledge, and evidence for decision making. The operational cycle model of strategic intelligence is DIKI, which is a strategic intelligence data infrastructure and analysis model including indicators, and tools for technology policy issues. There is a need to establish a dedicated strategic intelligence unit within the organization to understand and utilize technology strategic intelligence data, and to consciously incorporate it into the "evidence-based decision-making" agenda. Combining different types of strategic intelligence has become a necessary skill for technology policy makers. Technology innovation policy makers should take responsibility for the generation, maintenance, integrity, and accessibility of a large amount of administrative data related to the monitoring of technology innovation systems and policies.

Development Trends of International Open Peer Review Platforms and Recommendations for China | Open Access

ZHANG Zhixiong, WANG Yuju, ZHAO Yang

2024, 36(5): 14-22. DOI: 10.13998/j.cnki.issn1002-1248.24-0499

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[Purpose/Significance] This study systematically analyzes the basic models and development trends of international open peer review platforms, with the aim of exploring the insights these platforms provide for academic communication and research governance in China. The goal is to accelerate the establishment and development of an open peer review system in China, fostering a more open, collaborative, and efficient academic exchange environment that promotes the free flow of knowledge and the widespread dissemination of scientific ideas. [Method/Process] The article first reviews and analyzes several international open peer review platforms and communities that are led by the scientific community and operate independently of scientific journal publishing, such as Peer Community In (PCI), Sciety, PREreview, and Review Commons. On this basis, it outlines the basic operational models of international open peer review platforms and identifies a number of common features among the three basic models. Then, through an in-depth analysis of the development dynamics of these platforms and communities, the study summarizes their development trends from different perspectives, including research institutions, scientists, scientific community, and international academic communication models. Based on this analysis, and taking into account international experience and the specific characteristics of China's research environment, the article proposes recommendations for building an open peer review system in China. [Results/Conclusions] The study identifies three basic operational models of international open peer review platforms: platforms established for the purpose of open publishing, platforms developed primarily as preprint servers, and platforms built independently for open peer review. It also summarizes the key trends in the development of these platforms: strong support from major research institutions, active participation of leading scientists, the formation and impact of large-scale platforms, recognition of open peer-reviewed research by the scientific community, alignment with the international open access (OA) movement, and the reshaping of international academic communication models.International open peer review platforms and communities are emerging as important forces in driving research innovation and enhancing research quality. In light of China's current situation, the article offers six recommendations to accelerate the development of open peer review platforms and communities: (1) fully recognizing the significance of open peer review platforms for Chinese science; (2) updating scientific publishing concepts to create a supportive environment for the development of open peer review platforms; (3) implementing policies to support the construction of open peer review platforms and communities in China; (4) promoting exemplary cases and innovative practices in the development of open peer review platforms and communities; (5) building robust national open peer review infrastructure to support the development of open peer review communities; and (6) engaging in brand building to create internationalized open peer review platforms and communities. These efforts aim to secure a new position for China in global scholarly communication.

Risk of AI Algorithmic Discrimination Embedded in Government Data Governance and Its Prevention and Control | Open Access

PENG Lihui, ZHANG Qiong, LI Tianyi

2024, 36(5): 23-31. DOI: 10.13998/j.cnki.issn1002-1248.24-0353

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[Purpose/Significance] The purpose of this study is to provide an in-depth analysis of the widespread application of artificial intelligence (AI) technology in the field of government data governance and its far-reaching implications, with a particular focus on the core issue of algorithmic discrimination. With the rapid development of AI technology, it has demonstrated great potential in government decision support, public service optimization, and policy impact prediction, but it has also sparked extensive debate on issues such as algorithmic bias, privacy invasion, and fairness. Through systematic analysis, this study aims to reveal the potential risks of AI algorithms in government data governance, especially the causes and manifestations of algorithmic discrimination, and then it proposes effective solutions to protect citizens' legitimate rights and interests from being violated, and to maintain government credibility and social justice. [Method/Process] This study adopts the literature induction method to extensively collect domestic and international related data on the application of AI in government data governance, including academic papers, policy documents, and case studies. Through systematic review and in-depth analysis, we clarified the specific application scenarios of AI algorithms in government data governance and their role mechanisms. On this basis, this study further identified the key factors that led to algorithmic discrimination, including but not limited to the one-sidedness of data collection and processing, the subjective bias of the algorithm designers, and the influence of inherent social biases on the algorithms. It then explored the potential risks of algorithmic discrimination, including exacerbating social inequality, restricting civil rights, and undermining government credibility, and provided an in-depth analysis through a combination of theoretical modeling and case studies. [Results/Conclusions] The results of the study show that while the embedding of AI technology in government data governance has significantly improved the efficiency and accuracy of governance, it comes with a risk of algorithmic discrimination that cannot be ignored. To address this issue, this study proposed a series of targeted prevention and control measures, including clarifying the principle of algorithmic fairness, formulating industry norms and standards, improving the accountability mechanism and regulatory system, and optimizing the data collection and processing environment, so as to effectively curb the phenomenon of algorithmic discrimination while making full use of the advantages of AI technology, so that AI technology in government data governance can truly benefit the people, and promote social fairness and justice.

Exploration and Practice of Classification Indexing Combined with Large Language Models | Open Access

JIANG Peng, REN Yan, ZHU Beiling

2024, 36(5): 32-42. DOI: 10.13998/j.cnki.issn1002-1248.24-0346

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[Purpose/Significance] Document classification is one of the fundamental tasks of information service institutions such as libraries. The limited human resources make it challenging to categorize the vast number of documents, and the current automatic indexing technologies are not yet fully integrated into the entire indexing process. Large language models (LLMs), with their excellent capabilities in natural language understanding and processing capabilities, have been utilized for various natural language processing tasks such as text generation, automatic summarization, and text classification, which can be integrated into the entire classification process. [Method/Process] Combining the long-term practical experience of the National Newspaper Index, the research on how to introduce LLMs into the classification and indexing process is conducted from three aspects: reducing the reading pressure on indexers, directly using LLMs for classification, and combining them with automatic indexing models. A prompt-assisted topic classification model is designed to leverage the LLM for intelligent analysis and extraction of document content, guiding the model to output concise information summaries. This allows indexers to quickly understand the basic situation of the research, grasp the essence of key concepts and their interrelationships, and thus quickly and accurately determine how to classify the collections. [Results/Conclusions] When the LLM cannot be directly used for text classification tasks based on the "Chinese Library Classification" (CLC), it is combined with existing automatic models to generate the ACBKSY model. The overall classification accuracy of the model has improved by 2.16%, and the non-rejection accuracy has increased by 3.77%. On this basis, the actual indexing workflow is optimized to increase the systematicity and coherence of the indexing work, ensuring that every step from document input to final classification is more efficient and accurate. This optimized workflow has been put into use in the R and F categories of the collection, and it can improve the efficiency of indexing by 1.1 to 1.4 times. However, there are still some shortcomings in this paper, such as not providing the LLM with sufficient learning to fully understand the category settings of the CLC and some simple rule divisions; the classification based on the CLC is essentially a hierarchical classification, and how to guide the LLM to gradually output classification results in the form of multiple rounds of dialogue needs further study.

Integrated Model of Digital Construction and Operation of Rural Areas Guided by Value-added Data Elements | Open Access

ZHOU Zhian, WANG Jiewei

2024, 36(5): 43-51. DOI: 10.13998/j.cnki.issn1002-1248.24-0381

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[Purpose/Significance] At present, we are in a strategic development period of integrated development of digital rural areas and data elements. The government has introduced a series of policies to promote the deep integration and development of digital technology and rural areas, and promote the release of data value. The continuous improvement of rural digital capabilities and data resource systems, as well as the continuous improvement of data element policy system and the value transformation paths, provide unlimited opportunities for unlocking the value of agricultural data. The purpose of this study is to further study and explore the model of enabling "data elements X" in modern agricultural innovation, summarize and extract the model of empowering high-quality development of the agricultural industry with data elements, and explore the vertical application of data elements in the agricultural field, which is of great significance for breaking through the bottleneck of agricultural industry development with the help of data elements. [Method/Process] The research method of this article is based on the review of data elements, digital rural areas, agricultural data resource policy system, and integrated development trends released by the country in recent years. It has used policy analysis, comparative analysis, model analysis, case study and other research methods. The theoretical basis mainly comes from government official policy documents, and the comparative analysis and model analysis mainly rely on industry experience in practical work. The case study mainly takes the Funan Digital Rural Project and Guangxi Pig Data Authorization Operation Project as examples to deeply analyze the practical application of the DOD mode in the special debt of digital rural data assets and agricultural industry data authorization operation, and conducts in-depth analysis and discussion based on the current situation of the industry. This study combines theory and practice. [Results/Conclusions] First, an innovative digital rural construction and operation integration model (DOD) guided by value-added elements is proposed. The connotation and significance of this model are analyzed, and a model for the operation and benefits of this model is further proposed. Two representative cases are used to deeply analyze the practical application of the DOD model. Finally, based on the case practice and the problems faced, targeted work suggestions are proposed to provide reference for local governments to flexibly use the DOD model, explore the use of value-added data elements to support digital rural construction, and empower agricultural industry development.

Farmers' Digital Literacy under the Background of Digital Rural Construction: Concept and Framework Construction | Open Access

WANG Xiaoyu, ZHANG Suluo

2024, 36(5): 52-64. DOI: 10.13998/j.cnki.issn1002-1248.24-0395

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[Purpose/Significance] In the context of the digital era and the construction of digital villages, digital literacy is crucial for farmers to contribute to rural revitalization and promote the structural transformation of the rural workforce. The defination of the concept and framework construction of farmers' digital literacy is an important basis for the assessment of farmers' digital literacy level, which is of great significance for the education and training of farmers' digital literacy, the promotion of farmers' quality development, and the revitalization of rural talented people. [Method/Process] This study uses the content analysis method to define the concept of farmers' digital literacy based on the perspective of "ability + quality". Farmers' digital literacy refers to digital rural construction, for instance, the ability to use intelligent equipment and digital technology to obtain, produce, use, evaluate, interact, share and innovate digital information, with security guarantee, ethics, and apply to rural life and production practice, so as to improve the quality and ability of digital income increase. Through comparative analysis, this paper reviews the typical and representative digital literacy frameworks at home and abroad, and uses Bloom's cognitive hierarchy theory to construct the farmers' digital literacy framework from the dimensional-level perspective, innovatively introducing farmers' professional skills as the first-level dimension, which is a new skill required to train new professional farmers and high-quality farmers. There is a need to introduce skills related to agricultural occupations. [Results/Conclusions] The framework includes 8 core dimensions of farmers' digital awareness, digital operation, digital information, digital social interaction, digital innovation, digital security, digital application and professional skills, as well as 21 secondary dimensions and several specific elements, including three levels of digital literacy: basic, intermediate and advanced. The basic level consists mainly of "awareness and understanding" and some simple operations with digital technology, tools and equipment. The intermediate level is mainly to be "able to use", which may vary according to individual goals and needs, and professional characteristics. The advanced level mainly refers to "active participation in practice", which can be innovative and practical in a specific area. In the continuum of basic, intermediate and advanced levels, farmers can self-assess against the framework level, providing a pathway for continuous learning and updating of literacy skills. The construction of farmers' digital literacy framework under the background of digital village construction can provide guidance for the formulation of relevant policies and evaluation scales, the updating of the cultivation system of high-quality farmers, and the improvement of farmers' digital literacy. Indeed, as a scientific exploration, the issue of farmers' digital literacy framework still has a huge space for exploration, and it needs to be evaluated by experts, improved from the perspective of farmers' subjects and pre-tested to verify its scientificity and applicability.

Elderly People's Online Health Information Seeking Behavior Based on Evolutionary Dynamics | Open Access

Chunling GAO, Liyuan JIANG

2024, 36(5): 65-78. DOI: 10.13998/j.cnki.issn1002-1248.24-0254

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[Purpose/Significance] It is of great significance to analyze the current situation of elderly people's online health information seeking behavior, grasp its hot topics and development trend, to meet the health information needs and improve the health literacy level of the elderly people, and to promote the high-quality development of health services for the elderly people. [Method/Process] In this study, the DTM model was used to perform dynamic topic mining and analysis of Sina Weibo post content from 2016 to 2023, and the topic evolution, topic semantic evolution and topic information entropy trend were each investigated. In this study, data information related to online health searches of the elderly was obtained from the Sina Weibo platform, and the text content and time in the data information were taken as corpus data. After cleaning the data, different time windows are divided in time order, a DTM model is constructed to identify research topics, and "subject-word matrix" and "document-topic matrix" files are obtained. The topic intensity calculation was carried out successively, and the hot topic identification and analysis of online health searches for the elderly was carried out. The evolutionary trend of topic intensity was visualized and the evolutionary path of topic keywords was analyzed at a fine-grained level, so as to explore the focus and changing trend of online health information searches for the elderly people. [Results/Conclusions] The topics of "senile diseases", "old-age care by science and technology", "diet and health care", "mental health" and "social care" have evolved significantly, and the elderly people pay much attention to health information types such as common old age diseases, physical medical maintenance, social assistance and care for the elderly, and clothing, food, housing and transportation, in order to meet their information needs. The topics of "senile diseases", "old-age care by science and technology", "diet and health care", "mental health" and "social care" have evolved significantly, and the elderly pay much attention to health information types such as common old age diseases, physical medical maintenance, social assistance and care for the elderly, and clothing, food, housing and transportation, in order to meet their information needs. The research popularity of "economic trap", "epidemic control", "medical fraud", "virus transmission", "epidemic travel" and "medical health" as a whole showed a trend of first increasing and then decreasing, and the elderly continued to pay gradual attention to health emergencies and economic property security issues that might arise. The research popularity of "sports health care", "high risk" and "cultural and sports tourism" remain moderately stable from 2016 to 2023 and has not changed significantly. Topics such as "senile disease", "sports health", "high risk" and "medical fraud" are semantically stable. The information entropy of "sports health care", "daily life safety" and "virus transmission" is relatively stable, the information entropy of "medical literacy", "epidemic control", "cultural and sports tourism" and "balanced diet" shows a diffusion trend, and the information entropy of "high risk", "diet and health care", "economic trap" and "medical fraud" shows a convergence trend.

Model Construction and Empirical Research on the Influencing Factors of AIGC User Dropout Behavior | Open Access

Liqin YAO, Hai ZHANG

2024, 36(5): 79-92. DOI: 10.13998/j.cnki.issn1002-1248.24-0314

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[Purpose/Significance] In the context of the rapid development of the artificial intelligence generated content (AIGC), it is crucial to understand the driving factors of users' psychological resilience and the characteristics of AIGC users' dropout behavior. This research focuses on this area to address the lack of in-depth studies in the existing literature. It aims to contribute to the knowledge system by providing a more comprehensive understanding of user behavior in the context of the AIGC. This is significant for promoting the transformation of the AIGC industry, as it helps to reduce the negative impacts of user loss and transfer, and promotes the sustainable use of the AIGC. It also has practical value in addressing the challenges facing the industry. [Method/Process] This study is based on resilience theory and S-O-R theory, which provide a solid theoretical foundation for the research. A questionnaire survey method is used, which is an appropriate approach for collecting data directly from users. A total of 328 questionnaires were collected from a wide range of AIGC users, ensuring the representativeness and reliability of the data. The empirical analysis and testing of the constructed model helps to validate the research hypotheses and draw meaningful conclusions. [Results/Conclusions] The research shows that psychological resilience is indeed a key factor in reducing dropout among AIGC users. Technological resilience and information quality play an important role in enhancing the psychological resilience of users. Based on these results, specific strategies and suggestions are proposed, such as improving the technological stability and performance of the AIGC, enhancing the quality of the information provided, and providing personalized support and training for users. However, there are some limitations to this study. For example, the sample size may not be large enough to cover all types of AIGC users. Future research could increase the sample size and explore other potential factors that may influence user behavior. In addition, longitudinal studies could be conducted to better understand the dynamic changes in user behavior over time. In conclusion, this study provides valuable insights into the factors influencing AIGC user dropout behavior and offers practical suggestions for promoting user retention and sustainable use. It paves the way for further research in this field and contributes to the development of the AIGC industry.

Practice and Enlightenment of Developing Librarians' Digital Scholarship Service Skills at the University of Florida Library | Open Access

YANG Xing

2024, 36(5): 93-101. DOI: 10.13998/j.cnki.issn1002-1248.24-0187

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[Purpose/Significance] The digital scholarship service ability of librarians is an essential guarantee for providing high-quality digital scholarship services. However, the current domestic research on improving librarians' digital scholarship service capability is mainly concentrated at the theoretical level, and there is a lack of librarians' skill training projects at the practical level. An in-depth analysis of practical projects implemented by foreign university libraries to develop librarians' digital scholarship service skills can provide some references and insights for domestic university libraries to re-skill their librarians at the operational level. [Method/Process] The Developing Librarian Pilot Training Project (DLPTP), implemented by the Digital Humanities Library Group at the University of Florida, has effectively increased librarians' skills and confidence in providing digital scholarship services with limited staff, funding, and space, and has stimulated the willingness and interest of more librarians to participate in digital scholarship services. Taking this project as the research object, this paper introduces its implementation experience from three aspects: implementation background, implementation characteristics and effectiveness evaluation based on the methods of literature research and network survey. This paper summarizes its main implementation characteristics from four aspects: 1) Conduct the top-level design of the training project in advance based on the feedback from team members. 2) Organize librarians to collaboratively develop the project charter, which includes detailed descriptions of the project scope, deliverables, outcomes, target audience, team member roles and responsibilities, timelines and constraints, communication methods, and deadlines. 3) Apply for special funds to cover the training costs of external experts. 4) Establish an independent space for teaching activities and project collaboration to encourage creativity and a playful atmosphere. [Results/Conclusions] Finally, it is suggested that domestic university libraries should focus on improving librarians' digital scholarship service ability from four aspects: 1) The library leadership should recognize the importance of digital scholarship services and incorporate them into the library's long-term development strategy, and advocate the concept of digital scholarship services from top to bottom. 2) The librarian competency training program should be designed from surface to depth. 3) The evaluation of librarian's training projects should be carried out from the surface to the essence, putting more emphasis on their learning process rather than the result.4) The library can first establish a digital scholarship interest group within the library, and then actively seek communication opportunities with external stakeholders such as campus departments, publishers, database vendors, and off-campus research institutions, thus building a digital scholarship practice community from the inside out. Due to the limited conditions, information about DLPTP can only be collected from literature and the Internet, which has certain limitations and needs to be improved in the future.