Core Viewpoint - The joint opinion issued by five government departments aims to strengthen the construction of data element disciplines and digital talent teams, establishing development goals and an implementation blueprint for talent cultivation in the data field in China [1] Group 1: Overall Strategic Shift - The opinion emphasizes a shift from school-based digital talent cultivation to supporting the national digital economy, integrating education, talent, industry, and innovation chains [2] - It advocates for a transition from a professional orientation to an element-driven approach, focusing on data as a new link connecting various professions [2] - The goal is to upgrade talent supply to serve the industry, creating a collaborative ecosystem that promotes high-quality development in the data industry [2] Group 2: Professional Setting Adjustments - The opinion calls for a mechanism to adjust academic disciplines based on the needs of data technology development and national strategy, breaking traditional academic silos [4] - It emphasizes the need for vocational schools to dynamically adjust data-related programs in response to industry demands, ensuring alignment with market needs [4] - The document encourages regional adaptation in establishing data-related institutions and specialties, fostering a connection between vocational education and local data industry ecosystems [4] Group 3: Innovation in Teaching Methods - The opinion promotes a shift from isolated school efforts to a collaborative educational ecosystem, driven by industry needs [5] - It encourages deep involvement of data enterprises in education, creating integrated training bases that merge teaching and production [5][6] - The establishment of a data industry-professional model is proposed to guide the development of new teaching forms, enhancing the practical problem-solving skills of students [6] Group 4: Governance System Reform - The opinion suggests forming a national data vocational education teaching guidance committee to facilitate multi-party collaboration among government, industry, and educational institutions [7] - It aims to create a standard system for data industry job competency requirements and vocational education program construction [7] - The document highlights the importance of cross-departmental collaboration in digital talent development, establishing a monitoring and evaluation mechanism for talent cultivation [7]

Core Viewpoint - The issuance of the "Opinions" by the National Data Bureau aims to enhance the construction of data element disciplines and digital talent teams, focusing on improving total factor productivity and developing new quality productivity to accelerate the high-quality development of China's digital economy [1][11]. Group 1: Importance of "Two Constructions" for High-Quality Development - Enhancing total factor productivity is a core indicator of developing new quality productivity and is essential for high-quality development [2][13]. - The growth of total factor productivity is driven by technological revolutions, resource allocation efficiency improvements, new industrialization, new infrastructure, carbon neutrality, and deeper reforms [2][13]. - Empowering artificial intelligence with data and deepening the market-oriented reform of data elements are crucial for strengthening and optimizing the digital economy [2][13]. Group 2: Digital Talent Development - There is a structural contradiction in the supply and demand of digital talent in China, with a gap of 25 to 30 million digital talents in 2023, which is expanding annually [3][14]. - The development of the digital economy requires a deep integration of education, talent, industry, and innovation chains [3][14]. - The "Opinions" emphasize the need for a multi-level, composite digital talent training system to activate the value of data elements [4][15]. Group 3: Multi-Pathways for Digital Talent Cultivation - The "Opinions" stress the importance of creating a collaborative ecosystem for industry-education integration, supporting partnerships between universities, research institutions, and enterprises [7][17]. - It encourages the establishment of data-related disciplines in higher education and the development of a talent training mechanism that connects undergraduate, master's, and doctoral programs [5][16]. - The focus is on practical training and interdisciplinary knowledge to meet the diverse needs of different industries [8][18]. Group 4: Organized Research in Data Field - The release of data value faces theoretical and practical challenges, necessitating innovation in theory and practice to enhance total factor productivity [9][19]. - The rapid development of AI as a core technology in the new round of technological revolution requires deep integration with vast amounts of data [9][19]. - The "Opinions" outline the main research directions in the data field, emphasizing interdisciplinary integration and organized research to solidify the foundation of scientific research [10][20].

Core Viewpoint - The document outlines the Chinese government's initiative to enhance data element discipline and digital talent development, aiming to leverage data as a new productivity engine for innovation [1][2] Group 1: Data Element Discipline and Talent Development - The initiative emphasizes the importance of cultivating talent in data element disciplines as a critical mission for market-oriented data allocation reform and high-quality AI development [1] - It serves as a foundational element for advancing the planning and construction of a digital China, digital economy, and digital society [1] Group 2: Implementation Strategies - The initiative includes 12 tasks across four main areas: establishing data element disciplines guided by national strategy, promoting vocational education in the data industry driven by industrial development, supporting organized research to enrich academic studies in the data field, and facilitating collaboration among academia, industry, and application scenarios [1] - It aims to create a robust vocational education system in the data industry, involving government coordination, industry guidance, and enterprise participation [2] - The establishment of a national data vocational education teaching guidance committee is encouraged, along with the formation of regional collaborative bodies for data industry education [2]

Core Viewpoint - The document outlines a strategic initiative by multiple government departments to enhance the construction of data-related academic disciplines and the development of digital talent, aiming to leverage data as a new productive force in the economy [1][2]. Group 1: Data Element Discipline and Talent Development - The initiative emphasizes the importance of cultivating various talents necessary for the market-oriented allocation of data elements and the high-quality development of artificial intelligence [1]. - It identifies the integration of the education chain, talent chain, industrial chain, and innovation chain as crucial for advancing digital China, digital economy, and digital society [1]. Group 2: Optimization of Academic Programs - The proposal encourages collaboration between education and data management departments to develop relevant academic programs such as data science and digital economy [2]. - It supports vocational schools in dynamically adjusting data-related programs based on industry needs, including the addition of courses on data collection, cleaning, compliance, and operations [2]. Group 3: Industry-Education Integration - The document calls for the establishment of a coordinated system for data industry vocational education, involving government oversight, industry guidance, and enterprise participation [2]. - It promotes the creation of regional industry-education integration communities, leveraging industrial parks to foster talent development and innovation in the data sector [2].

Core Viewpoint - The document outlines the "Opinions on Strengthening the Construction of Data Element Disciplines and Digital Talent Teams," aiming to enhance the role of data elements in driving innovation and productivity through the integration of education, talent, industry, and innovation chains [1][2]. Group 1: Strengthening Data Element Disciplines - The document emphasizes the need for educational and data management departments to collaborate on building data-related academic disciplines, supporting the establishment of programs in data science, digital economy, and management [1][2]. - It encourages universities to create digital colleges and integrate relevant academic resources, while also accelerating the development of course materials and textbooks in data-related fields [1]. Group 2: Promoting Vocational Education in the Data Industry - The document proposes the establishment of a coordinated system for vocational education in the data industry, involving government, industry guidance, and enterprise participation [2]. - It supports the formation of cross-regional education and industry integration communities led by leading enterprises and high-level educational institutions [2]. Group 3: Academic Research in the Data Field - The document calls for the acceleration of academic communities and the construction of a digital talent pipeline in the data field, including the establishment of technology associations [2]. - It highlights the need for strategic research on major issues related to the market-oriented allocation of data elements and the development of authoritative scientific databases [2]. Group 4: Promoting Collaboration in Data Application - The document stresses the importance of enterprises in constructing application scenarios and identifying technical needs, while supporting educational institutions and research organizations in cultivating innovative digital talent [2]. - It advocates for the formation of interdisciplinary research teams to accelerate the development of key technologies and produce high-quality research outcomes [2][3].

Group 1 - The core viewpoint of the news is the issuance of an opinion by multiple government departments aimed at strengthening the construction of data element disciplines and digital talent teams, promoting the integration of education, talent, industry, and innovation in the data field [1][2][3] Group 2 - The opinion emphasizes optimizing the setting of disciplines and majors related to data elements, encouraging universities and data enterprises to participate in the construction of relevant disciplines such as data science and engineering, and digital economy and management [1] - It proposes the establishment of a talent training mechanism that connects undergraduate, master's, and doctoral programs in data-related fields, and supports vocational schools in adjusting data-related majors based on industry needs [1] Group 3 - The opinion calls for accelerated research on major issues related to the market-oriented allocation of data elements, focusing on key topics such as data ownership, pricing, and trading, while also keeping pace with advancements in technologies like artificial intelligence and blockchain [2] - It highlights the importance of building typical application scenarios to promote deep integration of technological and industrial innovation in the data field, with a focus on cultivating composite, innovative, and practical digital talents [2] Group 4 - The opinion outlines the creation of a data element industry-education integration innovation platform, encouraging the establishment of interdisciplinary research teams to accelerate the development of key common technologies and cutting-edge technologies in the data field [3] - It emphasizes the need for collaboration among government departments to strengthen the organization and promotion of data element discipline construction and digital talent team building, fostering a conducive environment for the collaborative training of digital talents [3]

Group 1 - The core objective of the recent policy is to strengthen the construction of data element disciplines and the digital talent workforce, promoting the integration of education, talent, industry, and innovation in the data field [1][2] - The policy emphasizes optimizing the setting of academic disciplines related to data elements, encouraging universities and data enterprises to participate in the development of relevant programs such as data science and digital economy [1][2] - A talent cultivation mechanism that connects undergraduate, master's, and doctoral programs in data-related fields will be established, with vocational schools adjusting their programs based on industry needs [1][2] Group 2 - The policy aims to accelerate research on major issues related to the market-oriented allocation of data elements, focusing on key topics such as data ownership, pricing, and transactions [2] - It encourages the construction of typical application scenarios to promote deep integration of technological and industrial innovation in the data field, with enterprises playing a leading role [2][3] - The establishment of a data element industry-education integration innovation platform is proposed, relying on leading universities to foster interdisciplinary research teams and enhance the quality of research outcomes [3] Group 3 - The policy outlines the need for a collaborative environment among government, industry, academia, and research institutions to cultivate digital talent effectively [3] - It encourages the development of joint technology patents and the sharing of intellectual property benefits to accelerate the commercialization of technology [2][3] - The establishment of a regular working contact mechanism among relevant departments is emphasized to strengthen the organization and promotion of data element discipline construction and digital talent development [3]

Core Viewpoint - The release of the "Opinions" by five major departments aims to strengthen the construction of data element disciplines and digital talent teams, providing comprehensive support for the development of the digital economy and promoting high-quality growth in this sector [2][3]. Group 1: Talent Development Initiatives - The "Opinions" propose 12 measures to enhance the construction of data-related disciplines and digital talent teams, focusing on integrating education, research, and industry needs [2][3]. - There is an emphasis on optimizing discipline settings, encouraging universities to establish data science and digital economy programs, and adjusting vocational education based on industry demands [3][4]. - The initiative supports the establishment of digital colleges within comprehensive universities and encourages specialized institutions to develop programs in areas like digital trade, data security, and health data management [4]. Group 2: Trends in Digital Talent Training - The current trends in digital talent training include accelerated interdisciplinary integration, a stronger emphasis on practical skills, and regional specialization in talent development [4][5]. - The focus is shifting from single-discipline training to a "data + profession" approach, enhancing hands-on capabilities to reduce the adaptation period for talent entering the workforce [4][5]. - Regions with active economies are encouraged to cultivate talents in digital marketing and planning to meet specific market needs [4]. Group 3: Research and Innovation - The "Opinions" call for accelerated research in key areas such as data marketization, data rights, and emerging technologies like AI and blockchain, aiming to establish a robust theoretical and policy framework for data elements [5][6]. - There is a push for collaboration between academia and industry to foster innovation, with enterprises taking a leading role in identifying technical needs and implementing solutions [6]. - The initiative encourages the development of application scenarios to enhance the synergy between education, research, and industry, promoting the cultivation of innovative and practical digital talent [6].

Core Viewpoint - The issuance of the "Opinions" by five government departments marks a significant step towards addressing the shortage of digital talent in China, aiming for systematic, professional, and high-quality development in this area [8]. Group 1: Optimization of Academic and Professional Layout - The "Opinions" propose three approaches to optimize the academic structure: improving subject settings, building a tiered and categorized system, and strengthening teaching elements to systematically construct disciplines related to data [3]. Group 2: Promoting Deep Integration of Industry, Academia, and Research - The "Opinions" emphasize the use of application scenarios as a vehicle to promote deep integration among industry, academia, and research, thereby maximizing the value of talent cultivation [5]. Group 3: Deepening Industry-Education Integration and Vocational Education Reform - The "Opinions" focus on building an ecosystem for industry-education integration, reforming education and teaching, and developing course resources to address the disconnect between learning and application, thus bridging the final gap in talent development [6][15]. Group 4: Supporting Higher Education Institutions - The "Opinions" support comprehensive universities in establishing digital colleges and integrating relevant academic resources, as well as encouraging specialized institutions to enhance their programs in data technology, data analysis, and digital arts [11]. Group 5: Development of Micro Majors - The "Opinions" advocate for universities to offer "micro majors" that meet the urgent knowledge and skill requirements of the data industry, such as digital trade and digital media arts, fostering a collaborative innovation system led by enterprises [13]. Group 6: Addressing the Skills Gap in Vocational Education - The "Opinions" encourage vocational colleges to add data-related programs to address the skills gap, focusing on areas like data collection, cleaning, annotation, and operation, in response to market demands [16]. Group 7: Building a Comprehensive Ecosystem - The "Opinions" propose a complete ecosystem integrating academic disciplines, vocational education, academic research, and industry-academia-research collaboration, aiming to resolve the disconnect between learning and application through a three-integration mechanism [18].

Core Viewpoint - The document outlines the "Opinions on Strengthening the Construction of Data Element Disciplines and Digital Talent Teams," aiming to enhance the development of data-related academic disciplines and the cultivation of digital talent, aligning with national strategic needs and technological advancements [1][2]. Group 1: Key Measures - The document proposes 12 key measures across four main areas to strengthen data disciplines and digital talent development [1]. - First, it emphasizes optimizing academic discipline settings and supporting tiered and categorized construction to enhance core teaching elements [1]. - Second, it focuses on promoting vocational education in the data industry by creating an integrated ecosystem of industry and education, reforming educational practices, and enriching curriculum resources [1]. - Third, it aims to support organized research in the data field by enhancing research organization, accelerating key research directions, and solidifying the scientific data foundation [1]. - Fourth, it encourages collaboration among academia, industry, and application scenarios to build typical application cases, innovate collaborative training models, and create technology innovation platforms [1]. Group 2: Implementation and Coordination - The document mandates the National Data Bureau, in collaboration with relevant ministries, to strengthen the organization and promotion of data discipline and digital talent development, establishing a regular working contact mechanism [2]. - It calls for coordinated efforts from various departments to create a conducive environment for the collaborative training of digital talent, with the National Data Bureau responsible for monitoring implementation effects and summarizing best practices [2]. - Local departments are urged to organize and implement policies effectively based on their specific circumstances to ensure the measures are realized [2].