With the explosive popularity of ChatGPT and the development of AI generated content (AIGC), the new generation of artificial intelligence (AI) technology has triggered people's imagination and discussion about the production mode of digital content and the industry transformation. At the same time, it also prompted more scholars' thinking beyond embracing the technological changes in the field information resource management. Based on this, we invited 6 experts to carry out related discussions from the perspective of the disciplinary construction and development of information resource management. (1) AIGC and the field of library and information service: The essence of the rapid development of AI technology lies in the improvement of people's ability in knowledge acquisition brought by the continuous enrichment of data resources and the improvement of quality. The professionals in the field of library and information service should fully understand their value and their role, give full play to the advantages of data resources in libraries, effectively utilize their expertise in knowledge organization and management, actively promote research and development of AI technology, and contribute their wisdom and solutions. (2) The disruptive change brought about by AIGC: The emergence of ChatGPT has brought subversive challenges to the library and information service field. The professionals in this field should actively promote the transformation of the AI era, seize the opportunity, and explore new growth points around knowledge production, resource discovery, knowledge relevance and scientific research ethics. In addition, they should give play to the advantages of our country's political system and intensive development policies, promote the transformation of information services to knowledge content generation service, and raise the knowledge productivity of the whole society. (3) AIGC and cultural heritage resources: ChatGPT has ushered in an era of model-driven content production and carry out innovation in the mode of intelligent service of cultural heritage resources supported by AIGC. In addition, this paper also analyzes the copyright ownership, real-time, interpretability, verifiability, trustworthiness, algorithm bias and cognitive misdirection of large-scale AIGCs. In the future, universal value rationality such as public order and good customs should be endowed with the AIGC, and the paradigm change in the field of cultural heritage should be actively welcomed and promoted. (4) AIGC and researches on intelligent information processing of ancient books: While ChatGPT plays a positive role in promoting intelligent information processing of ancient books and promoting cultural transmission and civilization inheritance, it also brings challenges in cultural value and national security, content security and information governance, information literacy and humanistic education. It is necessary to make efforts in the aspects like providing higher quality and larger scale of precise processing of ancient books in the future, so as to build a scientific, comprehensive and systematic system of information security and digital ethics. (5) AIGC and intelligent tool revolution: This paper analyzes the three elements of big data, giant model and huge computing power in the development of AIGC technology, as well as the four development directions of large and complete data volume, fine granularity of data analysis, multi-source and multi-mode semantic integration of semantic association, human-computer integration of information services and intelligent interaction. It is pointed out that AIGC will bring about the paradigm change of content production in three aspects: production innovation, automatic generation and ecological cultivation. At the same time, it will also bring challenges in technology monopoly and hegemony, network information security technology integration and other aspects. (6) AIGC and library: Based on the analysis of the core technology innovation trend in the ChatGPT model expansion, data enhancement and model fusion, this paper demonstrates the necessity and crisis of using ChatGPT in libraries. In addition, from five aspects of intelligent management system, retrieval system, recommendation system, question answering system and search engine, this paper puts forward some suggestions on the use of GPT in library service integration and innovation promotion.

[Purpose/Significance] This study is focused on the current popular "chatbot" ChatGPT to deepen users' overall cognition of ChatGPT, and provide reference and inspiration for the development of intelligent knowledge services in libraries by combining the power of new artificial intelligence (AI) technologies.[Method/Process] The article comprehensively analyzes ChatGPT, including its development history, technical features, common application scenarios, and integrated application program paths. In addition, it compares ChatGPT with similar AI technologies developed domestically and internationally (such as Google's Brad and Meta's BlenderBot 3), intuitively reflecting that new AI technologies such as pre-training models and cognitive intelligence have become the research and development focus of major technology institutions. The article also analyzes the technical limitations and existing security risks of ChatGPT, pointing out the optimization direction for secondary development and indicating its potential hazards for other researchers. Furthermore, the potential impact of ChatGPT on the Chinese libraries and information institutions are explored. By studying the application of ChatGPT in libraries and information service institutions, this article attempts to provide an in-depth understanding of how to use this technology to improve information retrieval, knowledge management, and user engagement. Finally, a comprehensive overview of ChatGPT and its potential impact on the Chinese information environment is provided. [Results/Conclusions] The integration of new technologies such as big data and AI has great potential for China's library and information service institutions to provide better and more intelligent knowledge services. With the development of modern technologies, libraries and information service institutions have been faced with new challenges and opportunities at the same time. The challenges come from the overwhelming amount of information, the diversification of information resources, and the increasing demands of users for personalized services. The opportunities arise from the availability of advanced technologies such as big data and AI that can help libraries and information service institutions to address these challenges. By fully integrating big data and AI into libraries and information service institutions, these institutions can leverage the power of these advanced technologies to provide more intelligent knowledge services. High-quality scientific and technological resources and knowledge organization systems can play a vital role in ensuring that these institutions are equipped with the necessary infrastructure and expertise to successfully implement these technologies. In conclusion, the integration of big data and AI represents a significant opportunity for China's libraries and information service institutions to provide better and more intelligent knowledge services. By relying on high-quality scientific and technological resources and knowledge organization systems, these institutions can comprehensively improve their level of intelligent knowledge services, and better meet the needs and demands of their users in the digital age.

[Purpose/Significance] Digital technology has become an important driving force in the utilization of data production elements. To make full use of data resources, the underlying accompanying problem is rights management. In practice, the ownership and the right to use of data resource are separated in the circulation process. It has become an urgent problem to conduct data resource management activities based on reasonable and legal protection of users' rights. [Method/Process] Based on the general framework of "practical basis - abstract analysis - general concrete understanding", this paper firstly identified four practice statuses of distributed big data assets as followings: 1) the application of new technology leading to facilitating platforms; 2) attention needed to paid to intellectual properties of multiple users' groups; 3) users' needs to be satisfied on various contexts. For example, conducting resource procurement, collection, data processing and layout of resource allocation systems based on cloud service platforms; 4) maintainance and management of high quality data sets, including self-built and imported resources, the negotiation of ownership and use rights, and emphasis on the rights strategies. Next, this study conducted abstract analysis on the generalized idea of basic dimensions of data rights management from four aspects, namely, technical resource regulation, reasonable use boundary, complexity of rights, and analysis of use rights. [Results/Conclusions] Based on the abstract analysis, this paper put forward and explained four successive solutions at data resource management institute level, as described below. 1) the principle and terms of data policy, which include but not limited to general statement, policies of content use, policy statement on metadata, social media policies, and terms of service; 2) the typical contexts and content planning of rights potofolio. This paper took the resource procurement business of academic libraries as an example to illustrate and summarize the four content planning items on rights portfolio: strategic plan, operational policies, data policies, end-user policies; and 3) the allocation management of data assets, which lays the key part of data asset management. In this paper, we consider that data asset management refer to description and management of the constituent terms of data assets and the relationship between terms. The cost structure of data asset management contains tangible cost (such as consulting, software and hardware purchase fee, and digital resources purchase fee) and intangible cost (such as indirect human resource costs, risks, social credit, and loss compensation); and 4) finally, the establishment standard, working process, associated contrasts and regulations, and the evaluation measurements of data asset management businesses at the institute level. Such solutions are proposed to provide some inspirations to data resource management institutes（such as libraries） under the distributed big data circumstance.

[Purpose/Significance] At present, governments at different levels in China are faced with some problems and challenges in opening up government data such as lagging policy legislation, data unable to meet public demand, insufficient platform service function and integration, imperfect data openness innovation mechanism, and a lack of unified management institutions. The purpose of this paper aims at construction of a stage maturity model to build an evaluation indicator system to measure government data openness maturity, It is important for the local government to understand which level of development their open data is at and which areas need to be improved, in order to comprehensively understand and grasp the actual level of local government data openness in China, which is important for strengthening the construction of sunshine government and e-government, optimizing the process of government data openness, and promoting the innovative development of government data openness. [Method/Process] Based on the idea of the software capability maturity model Capability Maturity Model (CMM), the Chinese government data openness maturity model was constructed, and then a data openness evaluation indicator system was also established on the basis of the maturity model. The government data openness maturity model includes strategic level, data level, technical level, organizational level and application level, and the levels are divided into five categories: initial level, document level, development level, open level and optimization level. The evaluation indicator system consists of 5 primary indicators, 11 secondary indicators and 35 tertiary indicators. The combination weights of the indicators were calculated by using the AHP-entropy weight method. Then, we designed the scoring rules, set the scoring criteria, and scored the four municipalities directly under the central government of China according to the actual situation. [Results/Conclusions] According to the ratings of the four municipalities, Shanghai has a good overall performance, followed by Beijing, Tianjin, and Chongqing. The municipalities directly under the central government are better in terms of related policies launched, but they are lacking in terms of platform function construction, the degree of perfection of local policies and regulations, and the interaction ability with users, which need to be further strengthened. The open government data evaluation indicator system proposed in this paper needs continuous improvement in terms of indicator selection and scoring criteria. In some aspects, the effect of using one indicator alone may not be satisfactory, and the follow-up study involving more elements will summarize more experiences and collect more experts' opinions in the field of government data openness to further improve the government data openness maturity evaluation indicator system.

[Purpose/Significance] Mobile short video apps like Tiktok have become one of the most frequently used tools to obtain/exchange health information in post-epidemic era. This study analyzed the complex relationships between the antecedents and users' health information adoption in mobile short video apps in terms of necessary and sufficient conditions, in order to optimize users' experience with health information adoption systematically, which in turn generates users' sustainability. [Method/Process] Based on both the information adoption model (IAM) and the heuristic-systematic model (HSM), this study constructed a health information adoption model of mobile short videos, in which five predictor variables (content quality, expression quality, information source credibility, app's reputation, perceived information usefulness) and an outcome variable (health information adoption) were included. The construct validity, reliability and symmetrical relationships between the five predictor variables and an outcome condition were examined using structural equation model (SEM) method. Fuzzy-set qualitative comparative analysis (fsQCA) was used to examine and reveal the configuration models. [Results/Conclusions] The results from PLS-SEM method and fsQCA validated the IAM and HSM in the context of mobile short video apps. Specifically, the results from PLS-SEM show that systematic and heuristic clues jointly affect users' adoption of health information. Content quality, app's reputation and information resource credibility significantly impact perceived information usefulness, and further affect the health information adoption. Expression quality has a significant effect on content quality, but no obvious effects on perceived information usefulness and health information adoption. The results of fsQCA reveal three configurations to affect users' health information adoption (i.e., content quality * expression quality * perceived information usefulness * information resource credibility), and another three configurations to affect users' non-adoption i.e., ~content quality * ~perceived information usefulness * ~information resource credibility), in which the latter configurations are asymmetric with the former. The configurations where systematic clues are predominant (S1a and S1b) are more sufficient for promoting users' health information adoption. N1(~ content quality * ~ perceived information usefulness * ~ information resource credibility). This shows the most sufficient configuration path in non-adoption. This study is aimed at exploring users' adoption and non-adoption decision-making process in a growing context of mobile short video apps like Tiktok, in order to contribute to helpful advice for the better management of these apps, which will eventually optimize users' experience with health information behavior. Users always engaged in many kinds of information activities such as information sharing, retweeting, adoption, and some relationships between these activities may exists. Due to the limited length, we did not consider users' other information behavior i.e., retweeting) and the relationship between them in this context, which could possibly be further research directions.

[Purpose/Significance] Since the outbreak of COVID-19, there has been a rapid increase in the number of studies related to COVID-19 at home and abroad. Review of relevant literature on COVID-19 provides data resources for related research on the emergence and transmission mechanism of SARS-CoV-2. However, the current COVID-19 related dataset is a collection of the literature, without classifying the data for each subfield, and the coarse-grained information such as the title and author fails to provide an in-depth understanding of the progress of COVID-19 research. Therefore, this paper created a dataset for the COVID-19 sub-domain and a fine-grained entity dataset. [Method/Process] Firstly, this paper proposed a literature screening method based on active learning model, which can obtain more valuable marker samples with less labor cost, so that the classifier has better generalization performance. We considered three base classifiers: Support Vector Machine (SVM), Logistic Regression (LR), and Random Forest (RF), while considering four query strategies: uncertainty sampling, expected error reduction, committee-based query, and random sampling. Taking the origin of SARS-CoV-2, one of the sub-fields related to SARS-CoV-2, as an example, articles related to the origin of SARS-CoV-2 were efficiently and accurately located from the literature. At the same time, this paper designed a labeling scheme covering 18 types of entities, including not only genes, proteins, compounds and other entities that are universal in the biological field, but also corona viruses and wild animals that are unique to the field of SARS-CoV-2. In this paper, visual annotation tool BRAT was used for entity annotation. The tagging team consisted of an administrator and six annotators, and the entity tagging consisted of two rounds. What's more, multi-k consistency index was used to calculate the consistency score of annotation results. [Results/Conclusions] The results of the active learning model show that the uncertain sampling query strategy has the best performance. SVM, LR and RF based on uncertain sampling can correctly screen 425, 465 and 489 articles, respectively. After the removal of overlapping articles, a dataset related to the origin of SARS-CoV-2 was constructed, containing a total of 885 articles. Secondly, based on the proposed entity labeling scheme, 6 annotators completed 99 papers. Based on the results of fine marking, this paper constructed an entity dataset containing 39,118 entities, which is the largest and most comprehensive entity corpus in the field of COVID-19.

[Purpose/Significance] In recent years, there has been a lot of research on the demand for health information, but the research on health information services for the elderly is slightly insufficient. In early 2022, China officially entered the aging society. In addition, people's attention to major public health emergencies brought about by the COVID-19 epidemic triggered the author's thinking about the demand for health information for the elderly under such circumstances. This paper aims to explore the health information needs of the elderly under major public health emergencies, enrich the theoretical content of health information needs and services for the elderly, and provide reference for health information services for the elderly. [Method/Process] In-depth interview was used to collect data from 30 elderly people. Thematic analysis was used to analyze the interview text, code the interview text, and summarize sub-themes. [Results/Conclusions] The results show that the health information needs of the elderly under major public health emergencies can be divided into four categories: disease prevention, disease diagnosis and treatment, health care, mental health and social life. In order to meet their health information needs, this paper proposes information service strategies from the perspective of the government, community and media: 1) the government ensures that information channels are unblocked, and makes full use of scientific and technological means to transmit information. In the Internet era, considering that most elderly people are also active on the We Media and social media platforms, government departments are suggested to make full use of scientific and technological means to update the latest news to the public in a timely manner, such as using emerging social media, We Media (such as Weibo, WeChat official account, Tiktok, etc.) to cooperate with official news agencies, and build smooth information transmission channels with the help of scientific and technological platforms, and expand the scope of information dissemination; 2) to enrich grassroots information dissemination channels by taking community as a unit, in addition to regularly issuing relevant notices and information in the community, we can also carry out targeted publicity lectures, free health clinics and other activities under the professional guidance of relevant institutions to help the elderly obtain health information; 3) to standardize the release of media information and improve the social responsibility of the media industry. This study mainly focuses on the elderly who can take care of themselves. The research object comes from the same community. In the future, more attention may be paid to the semi-disabled and completely disabled elderly, and diversified groups in different environments and regions will be considered.