《意见》中明确，到2027年，建成一批具有引领性和支撑性的数据科技创新平台，形成以企业为主体、 产学研用深度融合的高效创新机制，初步建立数据驱动的产业创新体系，数据供给、流通、利用、安全 等关键技术和设备实现阶段性突破。 （总台央视记者 丁雅妮 刘柏煊） 《意见》提出，结合"人工智能+"行动、"数据要素×"行动、数据流通利用基础设施建设等工作，建设一 批高价值、广覆盖、强牵引的数据科技应用场景。 今天，国家数据局发布《关于加强数据科技创新的实施意见》（以下简称《意见》），其中提出，谋划 布局一批数据领域部级重点实验室等创新平台，推动建设一批数据领域概念验证、中试基地、检验检测 等平台基地。 据介绍，数据科技是以发挥数据叠加倍增作用，释放数据要素价值为目标，系统性构建的数据科学、技 术和工程体系。 ...

Core Viewpoint - The National Bureau of Statistics has released implementation opinions aimed at strengthening data technology innovation, focusing on building a robust infrastructure for data technology innovation [1] Group 1: Infrastructure Development - Accelerating the construction of a national integrated computing power network to support data technology research and verification [1] - Promoting the pooling and intelligent scheduling of diverse computing resources for easier access and utilization [1] Group 2: Data Utilization and Security - Enhancing the infrastructure for data circulation and utilization, including the establishment of a data security protection platform [1] - Facilitating the trustworthy circulation and efficient use of data resources across regions, fields, and entities while ensuring data security [1] Group 3: Support for Innovation - Building prototype verification platforms and experimental fields focused on the frontiers of data technology to provide foundational support for new technologies, models, and applications [1]

每经AI快讯，12月27日，国家数据局官微发布关于加强数据科技创新的实施意见。意见提到，发展壮 大重点创新主体。鼓励国家实验室、企业、高校和科研院所等创新主体组建创新联合体，牵头或参与国 家数据科技攻关任务和重大创新平台建设，解决数据科技领域"卡脖子"难题。强化企业创新主体地位， 建立培育壮大科技领军企业机制，在数据等重点领域培育壮大一批科技领军企业。通过"揭榜挂帅、赛 马竞争"等方式，支持和鼓励科技型企业承担数据科技基础研究、技术攻关、产业应用等重点任务，提 升数据产业协同创新水平。支持民营企业依法参与数字化、智能化共性技术研发和数据要素市场建设， 支持有能力的民营企业牵头承担数据科技攻关任务。 ...

每经AI快讯，12月27日，国家数据局官微发布关于加强数据科技创新的实施意见。意见提到，打造数 据领域创新平台体系。加强数据领域创新能力建设，支持国家级科技创新平台基地发展。充分利用现有 创新资源，谋划布局一批数据领域部级重点实验室等创新平台，建立健全运行管理和评估机制，对考核 评价结果优秀的创新平台给予支持。引导地方根据自身优势和产业发展需要，建设数据科技领域重点实 验室、研发中心等创新平台，持续强化国家数据科技创新力量。 ...

人民财讯12月27日电，国家数据局发布关于加强数据科技创新的实施意见，意见提出，到2027年，建成 一批具有引领性和支撑性的数据科技创新平台，形成以企业为主体、产学研用深度融合的高效创新机 制，初步建立数据驱动的产业创新体系，数据供给、流通、利用、安全等关键技术和设备实现阶段性突 破。到2030年，数据领域关键技术达到国际领先水平，数据科技创新和产业生态体系实现整体性跃升， 对数据要素市场体系建设形成有力支撑，数据要素对经济社会高质量发展的赋能作用全面显现。 ...

Core Viewpoint - The article emphasizes the importance of data as a production factor in driving technological innovation and digital transformation in China, highlighting the need for strategic deployment and innovation in data technology to support the construction of a digital China [1][2]. Group 1: Significance of Accelerating Data Technology Innovation - Technological self-reliance is fundamental for national strength and security, with data as a key production factor crucial for seizing opportunities in the digital economy [2]. - Data technology innovation is essential for enhancing international competitiveness and transforming vast data resources into competitive advantages [2][3]. - Data technology innovation serves as a hard support for developing new productive forces and fostering new growth drivers, aligning with high-quality development requirements [3]. Group 2: Technical Demands for Digital China Construction - The "2522" framework proposed by the Central Committee outlines the need for solid digital infrastructure and data resource systems, promoting deep integration of digital technology across various sectors [5]. - The complexity of data necessitates advanced governance and innovative techniques to meet future demands for large-scale data processing and utilization [6]. Group 3: Comprehensive Policies to Promote Data Technology Innovation - The article calls for a top-level design in data technology innovation, emphasizing the need for strategic planning and resource allocation to enhance data technology capabilities [9]. - Accelerating key technology breakthroughs in data supply, circulation, utilization, and security is vital for addressing current challenges in data utilization efficiency and safety [10]. - Promoting the application of data technology results is essential for integrating digital and real economies, enhancing innovation in data-driven industries [11]. Group 4: Strengthening the Foundation for Data Technology Innovation - The establishment of a robust data infrastructure, standard systems, and talent education is crucial for supporting data technology applications and innovations [12]. - The government aims to improve data foundational systems to facilitate effective data resource development and cross-border data flow [11][12].