The scientific connotation, strategic considerations and practical ways of "new quality productive forces" have received wide attention from the political, academic and industrial circles. Cultivating and developing new quality productive forces means fundamentally changing the mode of production. It is necessary to grasp the practical direction of new quality productive forces from their scientific connotation and internal logic, and explore the scientific way of cultivating and developing the new quality productive forces from China's national conditions. As an important engine of economic development in the new era, its connotation characteristics, development path, opportunities and challenges are worthy of further discussion. For this reason, seven experts were invited to share their perspectives. 1) The deep logic and realization path of the construction of new quality productive forces and high-quality data resources. This paper discusses in depth the background and connotation characteristics of the high-quality data resources, and analyzes the internal logic of the mutual promotion between high-quality data resources and the development of new quality productivity. It is proposed that the construction of high-quality data resources must implement the concepts of innovation, coordination, openness, credibility and sustainability, and follow the construction strategies of concept innovation, model innovation, structural innovation and technological innovation. 2) The theoretical logic and practical path of data elements empowering new quality productive forces. In the new era of green and intelligent development, there is a profound dialectical relationship between data elements and new quality productive forces, and a new situation of economic and social development is accelerated in the spiral ascent of complementarity. We should comprehensively build a data space governance model with clear data ownership, smooth data path, guaranteed data quality and orderly and standardized algorithm computing power, expand new quality production capacity and production factors with the goal of human-machine cooperation and promote sustainable economic and social development. 3) Accelerating the promotion of data rights. Data can act on new quality productive forces from the technical, factor and industrial dimensions, and accelerate the formation of new quality productive forces. The multiplier effect of data elements on new quality productive forces will involve many dimensions, levels and stages, the most important and fundamental of which is how to determine the ownership of data. The measures for speeding up the promotion of new quality productive forces are discussed, such as constructing the theory of property rights in accordance with the characteristics of data and the law of development of new quality productive forces, speeding up the clarification of the types and scope of data confirmation, and improving the supporting system of data confirmation. 4) Promoting China's modernization path with Chinese-style digitization. Accelerating the promotion of Chinese-style digitization is not only the only way to realize Chinese-style modernization, but also the core to fully release new quality productive forces and build China's asymmetric competitive advantage under the new situation. It is suggested that in the process of digitalization and informatization in China, the information resource management industry plays a vital role and bears the important responsibility of digital transformation. 5) Interpreting the mission of public libraries from the perspective of new quality productive forces. Since its establishment, public libraries have been based on the concept of enlightenment. Faced with the profound digital transformation of society, today's public libraries need to further develop the potential of empowering the people in the field of digital economy and make them play an active role in the development of new quality productive forces. Public libraries need to further develop their potential to empower people in the field of digital economy, so that they can play an active role in the development of new quality productive forces. They should actively participate in data commercialization, promote the effective use of data elements and the efficiency of resource allocation, and enable more people to obtain and use data elements equally through open access and digital services. 6) The intelligent transformation of university libraries from the perspective of new quality productive forces. In the process of developing new quality productive forces, we should fully understand the profound meaning of new productive forces, based on the core tasks of providing a strong guarantee for the development of new quality productive forces in higher education, grasp the development opportunities, and realize the high-quality development of the industry. This paper explains the understanding of university libraries on the three key words of new quality productive forces, and proposes that the re-understanding and realization of library intelligence is an important starting point for the development of new productive forces. 7) To support information resource management discipline to accelerate the development of new quality productive forces. From the perspective of information resource management discipline, this paper analyzes several aspects of "doing something" under the rise of new quality productivity concept, including theoretical system, information resource guarantee, information analysis and consultation, scenario building, knowledge popularization and civic literacy cultivation. The content of academic evaluation, information policy, intellectual property rights, digital consumption behavior and other directions related to new quality productivity are also important directions that the discipline needs to pay attention to.

[Purpose/Significance] Talent data have become the most important production factor and strategic resource. Building a scientific and technological (S&T) talent database has become an inevitable way to narrow the digital divide and accelerate the digital and intelligent transformation of talent work. Therefore, this study builds an S&T talent database to promote scientific decision-making for talent development, precision in attracting new quality technical talent, reform in evaluating S&T talents, and building talent system for new quality productive forces. [Method/Process] By analyzing the practical requirements and significance of building an S&T talent database, this study first explores and analyzes the intrinsic logic of promoting the development of new quality productive forces through an S&T talent database. It then summarizes the challenges facing the current construction of a S&T talent database, including the scattering and concealment of S&T talent data, the lack of policies and standardized systems for S&T talent data, the inadequate exploration of value-added S&T talent data, the need to expand the application of digital technology in talent work, and the security risks of S&T talent data. In response to these challenges, this paper finally proposes the idea of building an S&T talents database, and introduces the research exploration and application practice on it, including the construction of big data database for S&T talent aimed at the development of new quality productive forces, the development of AI-powered talent data computing engine, research into the system for profiling new quality technical talent, the analysis of talent growth paths for the training of new quality technical talent, the identification method of new quality talented professionals based on big data, the development of an efficient digital platform for talent management, and the development of a strategic analysis platform for technical talent. [Results/Conclusions] The construction of S&T talent database is an objective requirement for the development of the digital era and an inevitable requirement for the formation of new quality productive forces. Building big data for S&T talent, empowering talent workflow with big data and artificial intelligence technology can help empower talent workflow, release the enormous energy contained in digitalization, effectively activate the internal momentum of talented professionals, institutions, society, and government, and then continuously improve the efficiency of talent resource allocation, the operational efficiency of talent work, the overall effectiveness of talent development governance, and promote the development of new quality productive forces.

[Purpose/Significance] New quality productive forces is the latest pattern of productivity development under the background of data-driven intelligence. To explore the mechanism and practical way of bidirectional empowerment of knowledge service and new quality productive forces has important theoretical and practical significance for giving full play to the effectiveness of new quality of data elements, new power of digital intelligence technology and new application of intelligent service, so as to promote the cultivation of new quality productive forces and improve knowledge service. [Method/Process] Based on the summary of the development process of knowledge service and the new interpretation from the perspective of new quality productive forces, this study analyzes the internal relationship and external manifestations of the bidirectional empowerment of knowledge services and new quality productive forces, constructs the bidirectional empowerment mechanism of knowledge services and new quality productive forces, and proposes the bidirectional empowerment path. [Results/Conclusions] "Factor reorganization, scientific and technological innovation, and quality service" has become the internal relationship between knowledge service and new quality productive forces. Data factor as the core production factor, digital intelligence technology as the key production technology, and intelligence-driven new business forms and new models as the common carrier, which is an important basis for intelligent knowledge service and new quality productive forces bidirectional empowerment mechanism. Intelligent knowledge service cultivates the new quality productive forces through three important ways: accelerating scientific and technological innovation, opening up new ways and creating new business forms. New quality productive forces drives the development of intelligent knowledge service and improves the service by solving the resource dilemma, technology dilemma and talent dilemma, and creating new competitive advantages. This is an important manifestation of the bidirectional empowerment mechanism of new quality productive forces and intelligent knowledge service. After clarifying the empowerment basis and the performance of the bidirectional empowerment mechanism, this study proposes that the two kinds of empowerment should be realized from the following four aspects: a) Taking the market demand as the guide by mining new value and responding to new demand, and grasping the new quality growth engine; b) Taking data elements as the center, the compacting intelligent driving base is realized by building the data element empowerment system and improving the standardization of element utilization; c) Taking technological innovation as the key way by releasing the potential of key elements and creating fusion application scenarios to consolidate the foundation of fusion application; d) Starting from the application scenario as the starting point, the bidirectional empowerment mechanism is put into practice in various fields.

[Purpose/Significance] Identifying key core technologies helps to clarify the direction of future efforts, optimize the allocation of innovation resources, accelerate the breakthrough of key core technologies, and promote the development of new quality productive forces by cultivating new types of workers, updating new types of means of labor, and expanding new types of subjects of labor. [Method/Process] Given the importance of key core technology identification in empowering the development of new quality productive forces, the research clarifies the connotation and extension of the key core technologies, and investigates the qualitative and quantitative identification methods of key core technologies at home and abroad. Quantitative methods are divided into three categories: indicator evaluation, social network analysis, and text mining. A comparative analysis of the advantages and disadvantages of each method are reviewed, and the overall shortcomings and problems of existing identification methods are summarized. Based on the analysis of the practical requirements and significance of breakthroughs in key core technologies, this study delves into the inherent logic of identifying key core technologies, which enables the development of new quality productive forces. The method of identifying key core technologies can cultivate new types of workers by improving talent management mechanisms and strengthening skills training for workers, New types of means of labor are updated through promoting technological integration and innovation and engaging in industry-academia-research cooperation and expanding new types of objects of labor by developing new production fields and analyzing market demand. In view of the challenges faced in the process of empowering new quality productive forces through the identification of key core technologies, this study proposes a practical way for empowering the development of new quality productive forces through the identification of key core technologies. [Results/Conclusions] Current research on identifying key core technologies is in its early stages and still faces several challenges, including outdated identification methods, inconsistent standards, the complexity of integrating technologies across disciplines, the need for improving accuracy of identification results, the lack of mining and using of multi-source data, and uncertainties in forecasting market demand. These obstacles hinder the process of using key core technology identification to cultivate new types of workers, update new types of means of labor, and expand new types of objects of labor, thus hindering the accelerated development of new quaity productive forces. Therefore, we need to focus on removing the obstacles that hinder the acceleration of new quality productive forces through the identification of key core technologies. A dynamic identification indicator system can be established to support the training of new types of workers, industry-academia-research cooperation can be strengthened to facilitate the updating of new production materials, and industrial development funds can be established to support the expansion of new types of objects of labor.