数据要素价值释放

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广东推进“数据要素×”:加快数据条例立法,打造可信数据空间
2 1 Shi Ji Jing Ji Bao Dao· 2025-09-29 10:02
日前,国家数据局举办"数据要素×"系列新闻发布会第三场,介绍各地在推进"数据要素×"行动实施的有 关情况。 国家数据局政策和规划司负责人、局新闻发言人栾婕表示,自启动"数据要素×"三年行动计划以来,10 多个省市已出台这一行动整体或者具体领域工作方案,配套制定财政资金奖补等政策。下一步,将继续 支持地方先行先试、大胆探索,印发数据要素场景指引。 发布会上透露,广东作为全国经济大省,正聚焦实数深度融合一条主线,通过供给公共数据、多源数据 和行业数据,提供数据政策、设施建设与数据安全等多重保障,以及培育数据流通交易平台、企业、人 才等数字经济生态,多维度实施"数据要素×"行动。同时,发挥"数据要素×"大赛牵引作用,激活数据要 素潜能,助推实体经济发展。 "数据要素×"的广东行动 粤港澳大湾区市场主体众多、产业发展活跃、数据资源丰富、应用场景广阔,基于这些综合优势,广东 在实施"数据要素×"行动上作了众多探索。 发布会上,广东省政务服务和数据管理局党组书记、局长王天广表示,近年来广东通过多维度供"燃 料"、全方位强"根基"、多载体培育"生态",推动数据要素价值释放驶入快车道。 广东分赛呈现"三个更多" 去年,首届" ...
数据之声 | 刘奡:提升技术产品能力 推动文化数据资产合规开发和有序利用
Xin Hua Cai Jing· 2025-09-12 05:41
Core Viewpoint - The event highlighted the need for enhancing technical product capabilities to ensure the compliant development and orderly utilization of cultural data assets, which are crucial for sustainable development in the digital economy [1][2]. Group 1: Cultural Data Assets - Cultural data assets are recognized as important data elements that face risks such as easy transportability, piracy, and unauthorized derivative creations [1]. - There is an urgent need to improve technical product capabilities to ensure the compliant development and orderly utilization of cultural data assets, aiming for their preservation and appreciation [1]. Group 2: Technological Support and Innovation - The rapid iteration of digital technology and the booming data industry necessitate technological innovation and cross-industry integration to unlock the value of data elements [1]. - In the cultural and tourism sectors, establishing a one-stop cultural data service platform can facilitate the digital organization, management, transaction evaluation, rights confirmation, authorization analysis, and comprehensive monitoring and protection of data assets [1]. Group 3: Cross-Industry Collaboration - Cross-industry integration is vital for driving innovation and enhancing the value of data elements, as it improves data circulation efficiency and fosters collaborative innovation across different sectors [2]. - The openness of data is crucial for cross-industry integration, with competitions like the "Data Elements ×" providing valuable resources for technology-driven companies [2]. Group 4: Recognition and Awards - Beijing Tengrui Cloud Cultural Technology Co., Ltd. won the first prize in the Beijing division of the "Data Elements × Culture Tourism" competition for its project on sustainable development of cultural digital data assets, which integrates management, protection, and operation of data assets [2]. Group 5: Digital Economy Forum - The "Xinhuanet Digital Economy Salon" series aims to create a high-end think tank exchange platform focusing on the theoretical frontiers, innovative practices, and key issues in the digital economy [3]. - The launch of the "Voice of Data" information release column aims to provide insights into digital economy policies, local data practices, and exemplary cases of digital enterprises [3].
上海城市可信数据空间试运行 已有近300家企业加入 形成数据产品超300个
Jie Fang Ri Bao· 2025-08-22 01:47
Group 1 - Shanghai is exploring a unified technical framework and governance protocol to establish a "maximum consensus" among various participants in the data space, addressing issues such as data supply, flow, usage, and security [1] - The Shanghai urban-level trusted data space has accelerated its implementation and became one of the first 63 innovative development pilot projects announced by the National Data Bureau in July [1] - The trusted data space aims to resolve bottlenecks in data value release, including concerns over data misuse, complex supply processes, and inconsistent data quality [1] Group 2 - The trusted data space is currently in trial operation, with nearly 300 participating enterprises and over 300 developed data products, accumulating billions of data calls [2] - Leading companies are exploring deep applications of the trusted data space, utilizing multimodal public data for decision-making during flood risk periods and enhancing services like navigation and delivery [2] - The trusted data space encourages industry leaders or alliances to establish their own operational data spaces across various sectors, including finance, healthcare, and smart manufacturing [2]
年底前将数据流通节点城市扩至50个左右 这场发布会信息量很大
Zheng Quan Shi Bao Wang· 2025-08-14 09:58
Core Viewpoint - The National Bureau of Statistics of China announced significant achievements in the construction and development of a digital China during the "14th Five-Year Plan" period, emphasizing the importance of data as a production factor and social wealth for high-quality economic development [1][7]. Group 1: Data Infrastructure and Policies - The National Bureau of Statistics plans to introduce over 10 new systems, including data property rights, and aims to expand data circulation node cities to around 50 by the end of the year [1][8]. - By June 2025, the number of 5G base stations is expected to reach 4.55 million, a fivefold increase from 2020, while gigabit broadband users are projected to grow 34 times to 226 million [2]. - The data industry is rapidly growing, with the number of data enterprises expected to exceed 400,000 and the industry scale reaching 58.6 trillion yuan, a 117% increase from the end of the "13th Five-Year Plan" [5]. Group 2: Data Utilization and Economic Impact - In the first half of the year, the number of new data products launched by major data trading institutions reached 3,328, a 70% year-on-year increase, with high-quality data set products increasing by 280% [3]. - Data-driven solutions have significantly improved efficiency across various sectors, such as a 5.5% increase in agricultural yield through smart fertilization and a 15-fold improvement in drilling decision efficiency in the industrial sector [5]. - The application of data in the service industry has led to a 30% increase in operational efficiency for freight matching [5]. Group 3: Regional Development and Industry Ecosystem - The Yangtze River Delta is emerging as a key growth area for the data industry, with its scale expected to account for 22.6% of the national data industry by 2024, housing over 100,000 data enterprises [6]. - Major cities like Beijing, Shanghai, Guangzhou, Shenzhen, and Hangzhou are attracting leading enterprises and fostering a trend of industrial ecosystem clustering [6]. Group 4: Innovations in Data Models - New models such as "data corpus pricing as equity" are being piloted in cities like Shanghai and Tianjin, allowing companies to convert high-quality data sets into equity investments [9]. - As of June, over 35,000 high-quality data sets have been established, with a total volume exceeding 400PB, and the trading volume of high-quality data sets reached nearly 4 billion yuan [9].
钢铁业利润回升效益向好
Jing Ji Ri Bao· 2025-08-06 21:59
Core Viewpoint - The Chinese steel industry has experienced a reduction in production and a significant increase in profits in the first half of the year, driven by national policy adjustments and industry self-discipline [1][2]. Group 1: Economic Performance - In the first half of the year, the total revenue of key steel enterprises was 29,985 billion yuan, a decrease of 5.79% year-on-year, while total profits reached 592 billion yuan, an increase of 63.26% [2]. - The average profit margin for the steel industry was 1.97%, up by 0.83 percentage points year-on-year [2]. - National crude steel production was 515 million tons, down 3.0% year-on-year, aligning with national industrial control policies [2]. Group 2: Inventory and Market Dynamics - The average month-end steel inventory for key steel enterprises was 18.91 million tons, the lowest level in nearly four years [3]. - The industry is witnessing structural development opportunities despite overall reductions, with increasing demand for high-end manufacturing materials and green low-carbon materials [3]. Group 3: Environmental and Technological Advancements - Investment in energy conservation and environmental protection by key steel enterprises accounted for 28.9% of total investments, an increase of 4.3 percentage points year-on-year [4]. - The industry is focusing on achieving ultra-low emissions, with 193 steel enterprises completing or partially completing emission reduction assessments [4]. - The application of artificial intelligence in steel production and operations is accelerating, with companies like Shougang and Nanjing Steel leading in digital transformation [5]. Group 4: Industry Challenges and Future Outlook - The steel industry is in a deep adjustment period, facing strong supply capabilities against weakening demand, leading to a recovery in profits but with insufficient sustainability [6]. - The Ministry of Industry and Information Technology has issued new guidelines to enhance industry standards and promote structural adjustments [6]. - The industry is expected to benefit from national policies aimed at expanding domestic demand, which will provide a favorable environment for development [7].
多措并举“点数成金”
Jing Ji Ri Bao· 2025-07-14 22:10
Core Viewpoint - The article emphasizes the importance of leveraging data as a new production factor to drive economic growth and improve efficiency across various industries, highlighting the need for a demand-driven approach to unlock the value of data [1][2][3]. Group 1: Data as a Production Factor - Data is increasingly integrated into various industries, enhancing the efficiency of traditional production factors such as materials, talent, technology, and capital, thereby promoting high-quality economic development [1]. - The application of data in diverse scenarios can lead to the emergence of new business models and economic growth opportunities [1]. Group 2: Industry Development Ecosystem - A robust industry development ecosystem is essential for maximizing data value, which includes nurturing data service providers and encouraging innovative operational models [2]. - The number of data service companies in China has exceeded 1 million over the past decade, playing a crucial role in activating data value [2]. Group 3: Data Security and Compliance - Ensuring data security and compliance is critical, as both corporate and personal data are sensitive and require protection of rights and privacy [3]. - Establishing a trustworthy data circulation environment involves collaboration among leading enterprises and industry associations to create a standardized and compatible data space [3]. Group 4: Market Development and Challenges - The ongoing market-oriented reform of data allocation is expected to enhance the value of data in social governance, industrial upgrading, and improving people's livelihoods [3]. - Addressing issues such as data barriers, low supply quality, and inefficient circulation is necessary to develop a fair and efficient data market [3].
“数据要素×”行动取得阶段性成效
Xin Hua She· 2025-06-24 07:51
Core Insights - The "Data Element ×" initiative has achieved significant progress in over a year, uncovering a number of excellent data development and utilization solutions that effectively promote the release of data element value across various industries [1][2] Group 1: Initiative Overview - The initiative is driven by pilot projects in sectors such as financial services, meteorology, and traditional Chinese medicine, aimed at addressing challenges in data aggregation, circulation, and usage within industries [1] - A total of 48 typical cases of "Data Element ×" have been published, facilitating the use of data to solve industry development challenges and enhance quality [1] - The "Data Element ×" competition attracted over 19,000 teams and approximately 100,000 participants last year, resulting in a number of replicable, scalable, and high-value data development projects [1] Group 2: Future Directions - The National Data Bureau plans to continue advancing the "Data Element ×" initiative in collaboration with various departments, focusing on typical application scenarios to explore new models and pathways for releasing data element value [2] - There is an emphasis on encouraging more enterprises to participate in pilot projects, case selection, and competition activities to activate data element value and provide new momentum for high-quality development across industries [2]
科策云:以科技之力,驱动科创数智新发展
Sou Hu Cai Jing· 2025-05-21 09:52
Core Insights - The strategic significance of vertical large models in government affairs is highlighted as a digital transformation accelerator, facilitating the transition from "information-based" to "intelligent" government services [1] - AI empowerment is emphasized for modernizing governance capabilities, enhancing decision-making science, service precision, and emergency response capabilities [2] - The release of data element value is crucial, aiming to break down data silos in government and achieve intelligent integration and application of data across departments and levels [2] Data and Technology - The document outlines a comprehensive data structure, including over 18 million enterprise business data, 4.59 million enterprise trademark data, and 10 million patent data, indicating a vast database supporting vertical industry applications [3] - The core technology architecture consists of a three-layer model system: a foundational layer based on domestic computing power, a domain layer for specific scenarios like policy interpretation and public service, and an application layer for lightweight fine-tuning models [3] Application Scenarios - Typical application scenarios include multi-modal government knowledge processing technology, a privacy-computing-based federated learning framework, and a structured parsing engine for policy texts [4] - Intelligent policy services are highlighted, including precise policy matching and push notifications, intelligent pre-examination of application conditions, and simulation of policy effects [4] Implementation Pathways - Suggested implementation pathways include a step-by-step strategy from single department pilots to cross-department collaboration, establishing data standards, security standards, and ethical guidelines for government large models [10] - The cultivation of "government + AI" composite talents is recommended to build a sustainable evolution capability [10] Future Outlook - The vertical large model in government affairs is expected to drive a new governance model characterized by "data-driven decision-making and intelligent service empowerment," ultimately achieving a new paradigm of government services that benefits the public [6] - The company, 科策云, is positioned as a leader in the science and technology innovation sector, with a focus on AI products and government-enterprise product lines, continuously enhancing its offerings to provide high-quality information services [6][8]
专访北京交通大学特聘教授张向宏:未来国家数据基础设施技术路线一定会收敛成一条,核心是将供数、用数和服务主体放进同一个空间
Mei Ri Jing Ji Xin Wen· 2025-05-12 06:37
Core Viewpoint - The core objective of China's data infrastructure is to address issues related to data supply, circulation, and utilization while ensuring data security, aiming for a system where data can be effectively supplied, circulated, utilized, and secured [3][6]. Group 1: Data Infrastructure Goals - The primary goal is to resolve the existing problems of data being "unable to circulate, slow to flow, and poorly utilized" [3]. - China's data infrastructure is defined as a new type of infrastructure that provides services for data collection, aggregation, transmission, processing, circulation, utilization, operation, and security [3]. Group 2: Effectiveness Indicators - The effectiveness of data infrastructure can be measured by the volume of data in circulation; significant platforms like Didi, Meituan, and Ctrip demonstrate effective data infrastructure with billions of users [4]. - The second indicator is the security of the data circulation process, which is crucial for ensuring efficient and trustworthy data flow [5]. Group 3: Key Technologies - Six key technology routes have been identified to ensure both data circulation and security: blockchain technology, privacy computing technology, data networking technology, data components, trusted data space technology, and data sandbox technology [5]. - Current technologies like blockchain and privacy computing are not yet mature enough for widespread application due to efficiency issues, particularly in sectors like finance where they are currently utilized [5]. Group 4: Future Directions - The future of national data infrastructure is expected to converge into a singular "space," "platform," or "network" where data can flow efficiently and securely [10]. - The construction of this space will involve various technologies, but the essential requirement is the presence of numerous data supply entities, application scenarios, and service providers [10]. Group 5: Addressing Data Inequality - The need to bridge the "data gap" across different industries is emphasized, with a focus on ensuring that all sectors, including manufacturing and agriculture, can leverage data for digital transformation [12]. - The national data infrastructure aims to solve the "data equality" issue, enabling artificial intelligence and other technologies to thrive by providing high-quality data [14].
8个应用先行区 46个重点应用场景——天津正式启建数联网
Zhong Guo Chan Ye Jing Ji Xin Xi Wang· 2025-05-04 22:59
Group 1 - The core viewpoint is that Tianjin has been approved to establish a national digital economy innovation development pilot zone, focusing on optimizing data infrastructure and accelerating the construction of a data network [1] - The data infrastructure aims to provide services for data collection, aggregation, transmission, processing, circulation, utilization, operation, and security, which are essential for releasing the value of data elements [1] - The data network will consist of data circulation access terminals, networks, and service platforms, aiming to create a secure and trustworthy environment for data circulation across various levels and sectors [1] Group 2 - The data network allows for "raw data not leaving the domain, data being usable but invisible," facilitating the open sharing of government data and efficient circulation of public and enterprise data [2] - An action plan for accelerating the construction of the data network over the next three years is being formulated, with specific districts identified for pilot applications [3] - Initial applications will cover 17 key areas, including healthcare, industrial manufacturing, transportation, and financial services, utilizing privacy computing technology to break down data barriers [3]