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]

Core Viewpoint - The National Development and Reform Commission, along with four other departments, has released an opinion aimed at strengthening data element discipline construction and digital talent development, proposing specific measures across four key areas: enhancing data element disciplines, promoting vocational education in the data industry, fostering academic research in the data field, and facilitating collaboration among industry, academia, and research [1][4]. Group 1: Enhancing Data Element Disciplines - The opinion supports the establishment of digital colleges in comprehensive universities to integrate relevant academic resources [2][5]. - It encourages specialized universities in fields such as science, finance, law, media, and arts to strengthen the construction of advantageous majors related to data technology, analysis, security, digital economy, finance, management, law, governance, media, and art [2][5]. Group 2: Promoting Vocational Education in the Data Industry - The opinion proposes the establishment of a coordinated system for vocational education in the data industry, involving government oversight, industry guidance, and enterprise participation [3][6]. - It encourages the creation of regional industry-education joint entities based on industrial parks to facilitate talent cultivation, innovation, and high-quality development of the data industry [3][6]. Group 3: Fostering Academic Research in the Data Field - The opinion emphasizes the need for strategic research in the data field, focusing on key issues such as data property rights, pricing, and trading [3][6]. - It calls for in-depth research on foundational theories and policy laws related to data elements, keeping pace with advancements in technologies like artificial intelligence, blockchain, and privacy-preserving computing [3][6]. Group 4: Facilitating Collaboration Among Industry, Academia, and Research - The opinion highlights the importance of strengthening the leading role of enterprises in constructing application scenarios, identifying technical needs, and implementing results [1][4]. - It encourages data companies to participate in vocational education, collaborating on student training, technology research, product innovation, and result transformation [3][6].

Core Viewpoint - The document outlines a comprehensive strategy to strengthen data-related academic disciplines and digital talent development in China, emphasizing the importance of aligning educational programs with industry needs and national strategic goals [1][3][4]. Group 1: Academic Discipline Development - Educational departments and data management agencies will collaborate to enhance data-related academic programs, supporting institutions in establishing degrees in data science, digital economy, and management [4][5]. - A talent cultivation mechanism will be established to ensure seamless transitions between undergraduate, master's, and doctoral programs in data-related fields [4][5]. - Vocational schools will be encouraged to adjust their data-related programs dynamically based on industry needs, including new courses in data collection, cleaning, compliance, and operations [4][5]. Group 2: Industry-Oriented Vocational Education - A system for data industry vocational education will be developed, integrating government oversight, industry guidance, and enterprise participation [6][7]. - The establishment of a national data vocational education teaching advisory committee is proposed to enhance the quality of education [6]. - Collaboration between data companies and vocational schools will be encouraged to create practical training bases and improve the quality of teaching [7]. Group 3: Research and Academic Collaboration - The document emphasizes the need for building academic communities and fostering a digital talent pipeline in the data field [8][9]. - It calls for the establishment of high-level academic journals and platforms for data research to facilitate the dissemination of knowledge and innovations [8]. - Research will focus on critical issues such as data marketization, property rights, and the application of emerging technologies like AI and blockchain [8][9]. Group 4: Application and Innovation - The creation of typical application scenarios is encouraged to promote collaboration between academia and industry, enhancing the practical training of digital talent [10][11]. - Innovative collaborative training models will be supported, with a focus on developing core courses and practical projects in data-related fields [10][11]. - The establishment of technology innovation platforms is proposed to foster interdisciplinary research and the development of cutting-edge technologies in the data sector [11][12]. Group 5: Implementation and Monitoring - A mechanism for ongoing collaboration among government, industry, and academia will be established to ensure effective implementation of the proposed strategies [12]. - The National Data Bureau will monitor the effectiveness of these initiatives and promote successful case studies [12].

Core Viewpoint - The document outlines a comprehensive strategy to enhance the construction of data element disciplines and the development of digital talent, emphasizing the importance of aligning educational initiatives with national strategic needs and industry demands [1][2]. Group 1: Strengthening Data Element Disciplines - The education and data management departments are encouraged to optimize the establishment of data-related disciplines, supporting the development of programs in data science, digital economy, and management [2]. - A talent cultivation mechanism that connects undergraduate, master's, and doctoral levels in data-related fields is to be established [2]. - Vocational schools are urged to adjust their data-related programs dynamically based on industry needs, including new courses in data collection, cleaning, compliance, and operations [2]. Group 2: Promoting Vocational Education in Data Industry - A collaborative ecosystem for vocational education in the data industry is to be developed, involving government, industry guidance, and enterprise participation [4]. - The establishment of a national data vocational education teaching guidance committee is proposed to enhance the quality of education [4]. - Encouragement for data companies to participate in vocational education, including the creation of practical training bases within schools [4][5]. Group 3: Supporting Academic Research in Data Field - The document emphasizes the need for building academic communities and fostering a digital talent pipeline in the data field [6]. - It calls for the establishment of high-level academic journals and platforms for data research to facilitate the dissemination of quality research outcomes [6]. - Research should focus on critical issues such as data marketization, property rights, and the application of emerging technologies like AI and blockchain [6][7]. Group 4: Facilitating Industry-Academia Collaboration - The creation of typical application scenarios for data technology innovation and industry collaboration is encouraged [8]. - Support for the establishment of specialized colleges in collaboration with enterprises and research institutions to enhance practical training [8][9]. - The document advocates for the development of innovation platforms that integrate education and industry, fostering interdisciplinary research teams [9]. Group 5: Implementation and Monitoring - The National Data Bureau, in collaboration with relevant ministries, will strengthen the organization and implementation of these initiatives, ensuring effective monitoring and evaluation of outcomes [10].

Core Viewpoint - The article emphasizes the importance of strengthening data infrastructure and institutional construction to activate new momentum in the digital economy, highlighting the need for collaborative governance and value release in the context of ongoing reforms in data factor marketization [1]. Group 1: Data Value and Usage - The concept of "usage" is highlighted as a more accurate reflection of data's value compared to "ownership," as data must be continuously utilized to maintain its value [3]. - The distinction between value creation and value realization is made, with data collection seen as value creation and processing, re-utilization, circulation, and application as part of the value realization process [4]. - The "three rights separation" approach to data emphasizes flexibility, fairness, and incentive mechanisms, allowing various stakeholders to participate in value realization throughout the data lifecycle [5]. Group 2: Institutional Construction and Legal Framework - The article discusses the need for a robust legal framework to support data rights and usage, suggesting that existing property laws require specific interpretations to accommodate data-related issues [7]. - It advocates for exploring new business models and environments that integrate government, large enterprises, and SMEs to foster a collaborative ecosystem for data utilization [7][8]. - The importance of establishing a regulatory framework that encourages innovation while managing risks is emphasized, alongside the need for a service system to support the data industry [8]. Group 3: Government and Enterprise Collaboration - The government plays a crucial role in the foundational construction of data as a new production factor, which is essential for the development of the data industry [8]. - Collaboration between government and enterprises is necessary to promote the development of a data market, with a focus on creating a dual market structure that addresses both tangible and intangible data [8]. - The article suggests that enterprises should leverage their supply chain and value chain advantages to foster new cooperative relationships, balancing competition and collaboration [9].

Core Viewpoint - The Chongqing government has issued a comprehensive reform pilot action plan for the market-oriented allocation of factors, leading to a significant rise in the stock prices of local companies such as Chongqing Construction Engineering and others [1] Group 1: Housing Market Reforms - The plan includes measures to convert existing commercial housing into affordable housing and optimize the mechanism for revitalizing existing land [2] - It supports the use of special bonds to recover and acquire eligible idle land and explores short-term utilization of reserved land [2] Group 2: Capital Market Development - The initiative aims to accelerate the development of the capital market through the "Thoroughbred" action, promoting innovative business models and facilitating mergers, acquisitions, and refinancing for listed companies [3] - It emphasizes the integration of investment and financing functions in the capital market and aims to optimize the REITs project service chain [3] Group 3: Data and Technology Infrastructure - The plan focuses on building a national integrated computing network in Chongqing, enhancing data utilization, and establishing a regional hub for blockchain networks [4] - It aims to develop high-quality industry data sets and promote smart connected vehicles and industrial internet applications [4] Group 4: Energy Sector Initiatives - The government supports the expansion of the Chongqing oil and gas trading center and the exploration of direct sales of overseas oil and gas resources [5] - It aims to facilitate cross-border settlement of oil and gas commodities in RMB and improve the natural gas pricing mechanism [5] Group 5: Digital Platform Development - By 2027, the plan aims to establish a digital platform for factor allocation, enhancing market mechanisms and significantly improving allocation efficiency [6] - The goal is to position Chongqing as a comprehensive hub for factors, serving both domestic and international markets [6]

就餐发票、文献资料、车架号……未经发掘的数据看似平平无奇，但经过高质量"开采"就成"数据珍 宝"，从"沉睡的数字"变为"赚钱的源泉"。近日，扬子晚报/紫牛新闻记者探访数据要素新兴产业的三家 代表企业——数族科技（南京）股份有限公司、见鲸科技（南京）有限公司、南京三百云信息科技有限 公司。它们在数字时代"掘金"的应用场景，是否给你带来启发？ 一张购物发票藏100多类高质量数据 如今，扫码或在平台勾选"我要开票"，已成为消费者就餐、住宿开发票的日常。但几年前，"开票难、 开票繁"还困扰着大家——插税盘、输信息，步骤繁琐还易出错；手撕定额票、手写限额票，更是没法 核验。2017年5月，数族科技推出全国首个发票云，发明全国第一张自助开票二维码，拉开发票数字化 服务的序幕。 8年多过去，数族科技的"臻票云"已服务超400万家纳税经营主体，每年采集发票约10亿张。"一张购物 发票，藏着100多类高价值数据。"数族科技创始人徐剑说。目前，该公司已在江苏省数据交易所上架近 300款数据产品，既有34款产业集群企业数据集，也有200多款数据应用类产品。 这些数据产品就像企业的"智能体检单"。比如"企业发票分析报告"和"企业财税 ...

Group 1 - The core viewpoint emphasizes the importance of deepening data resource development and utilization, as well as strengthening efficient data supply to advance the construction of a digital China [1] - A significant data industry supply-demand matching event took place, featuring hundreds of participating companies, particularly in sectors like transportation, industrial manufacturing, and smart energy [1][2] - Data, treated as a new production factor, is accelerating its flow, with over 400,000 data companies and a data industry scale exceeding 5.8 trillion yuan during the 14th Five-Year Plan period, more than doubling since the end of the 13th Five-Year Plan [2][3] Group 2 - The demand from manufacturing enterprises is creating opportunities for transportation and logistics companies, which produce over 3 million high-quality traffic data points annually [2] - The 14th Five-Year Plan has led to the rapid formation of China's data industry chain, with policies promoting data development and utilization [3] - The 15th Five-Year Plan suggests building an open, shared, and secure national integrated data market to promote deep integration of the real economy and digital economy, providing new development opportunities for more enterprises [3]

Core Viewpoint - The development of data assets as a strategic resource is emphasized, with Qingdao City leading the way in establishing a comprehensive management system for data assets, aligning with national strategies for digital economy development [1] Group 1: Institutional Framework - A comprehensive data asset management approach has been established through the issuance of the "Qingdao City Administrative and Public Institutions Data Asset Management Measures (Trial)", consisting of 7 chapters and 34 articles, laying the foundation for the entire lifecycle management of data assets [2] - A progressive revenue distribution mechanism has been created, clarifying data asset rights and establishing a dynamic distribution model to incentivize data sharing and utilization [3] - The first data asset circulation transaction has been initiated, with clear approval processes for the use and income of data assets, ensuring timely and complete revenue collection [4] Group 2: Standardized Processes - A standardized process for data asset development and utilization has been established, including a registration system that has completed data resource registration in 14 fields [5] - The approval process for paid data usage has been reinforced, and a public data operation platform has been developed to facilitate data integration and application [6] - The trading chain has been streamlined, with established pricing negotiations and revenue management practices for data asset transactions [6] Group 3: Market-Oriented Operations - A collaborative data industry ecosystem is being built, with 105 data service providers established and financial policies introduced to support data industry development [7] - Demonstrative data application scenarios have been created, with 5201 data resources identified and 147 data products launched across various sectors [8] - Diverse financing paths for data assets have been explored, enabling companies to convert data resources into development capital, with over 300 million yuan in financing achieved [9]

Group 1 - The core achievement of Top Cloud Agricultural Technology Co., Ltd. is winning the national first prize in the modern agriculture track at the 2025 "Data Element ×" competition, standing out from over 23,000 teams nationwide [1] - The award signifies a breakthrough for Gongshu District in achieving a national first prize, highlighting the district's commitment to strengthening data services and cultivating a data business ecosystem [2] - Top Cloud Agricultural's innovative model, "AI-driven Smart Pest Control," enhances pest warning accuracy by three times, transitioning pest control from passive response to precise proactive measures [1] Group 2 - Gongshu District has focused on high-quality development of the data industry, fostering nearly 19,000 data business enterprises and promoting efficient circulation and value transformation of data elements [2] - Leading enterprises like Top Cloud Agricultural and Zhejiang Transportation Investment Group are driving innovation in various sectors, including smart agriculture and transportation, facilitating collaborative development across the industry chain [2] - The district aims to strengthen policy integration and precise services to cultivate competitive data business enterprises, contributing to the establishment of a robust data industry ecosystem [3]