数据要素乘数效应

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国家数据局:将继续支持地方深化实数融合 释放数据要素乘数效应
Xin Jing Bao· 2025-09-28 10:47
9月28日,在国家数据局"数据要素×"系列发布会第三场上,国家数据局政策和规划司负责人、局新闻发 言人栾婕表示,将继续支持地方深化实数融合,释放数据要素乘数效应。 栾婕透露,截至目前,今年"数据要素×"大赛已顺利完成地方分赛阶段的激烈角逐,全国报名队伍突破 2.2万支,各地共遴选出900多个项目入围全国总决赛。将于10月中下旬在北京、上海两地举办相关赛道 的全国总决赛评审,并于11月在上海举办颁奖仪式。 (文章来源:新京报) 首先是支持政策有效,行动落实更有保障。各地加强政策对接,结合实际完善政策,不断夯实"数据要 素×"行动实施政策保障。截至目前,山东等10多个省市已经出台了"数据要素×"行动整体或者具体领域 工作方案,配套制定了财政资金奖补等专项支持政策。许多地方结合"数据要素×"行动的实施编制了"四 库全书",也就是"项目库、场景库、案例库、专家库",对入库企业实施"一企一策",既加大投资,也 帮助解难题,还帮助宣传推广,让企业更有获得感。下一步,国家数据局将指导地方持续推进行动走深 走实,全面完成行动任务和目标。 其次是基层探索有力,价值释放图景更加显现。各地统筹推进试点建设、大赛牵引、案例推广、场景 ...
用起来、活起来,多地施策释放数据要素“乘数效应”
Zhong Guo Xin Wen Wang· 2025-09-28 09:01
Group 1 - The core viewpoint of the articles emphasizes the implementation of "data element ×" actions across various provinces, showcasing the multiplier effect of data elements in enhancing economic and social development [1][2] - More than 10 provinces and cities have developed comprehensive or specific work plans for the "data element ×" initiative, supported by financial incentives and policies [1] - Local governments are creating databases, including project, scenario, case, and expert libraries, to tailor strategies for individual enterprises, thereby increasing investment and addressing challenges [1] Group 2 - In the tourism sector, Chongqing has utilized multi-source data to create an intelligent optimization model for tourism routes, resulting in a 25 percentage point increase in visitor satisfaction [2] - Shandong has developed a "data-driven marine tourism joint operation" model, leading to a 150% increase in marine tourism products and a 172% rise in visitors [2] - Jiangsu has launched a unified data exchange, listing 3,933 data products and attracting 1,864 data vendors and third-party service providers within five months [2] - The release of the data element multiplier effect has also fostered the cultivation of digital talent, with Guangdong implementing standards for evaluating big data engineering technical talent and providing training subsidies [2]
重庆数据局:释放数据要素乘数效应,实现数据“动起来、用起来、活起来”
Zhong Guo Jing Ji Wang· 2025-09-28 08:02
"比如,过去孩子入学需要线下排长队、跑动3次、提交10份材料、耗时超15天,现在实现全程网办,仅 需学生家长身份证、5天内就能收到通知书。"胡军国说。 最后,重庆推动"数据要素×"城市安全,强化数字赋能感知预警,通过打造"韧性安全城市治理一张 图",实现60万余个风险点位全落图、2100万余个感知设备全接入、1900万余件事件全汇聚,相关隐患 数据全提示、问题数据全推送,有效推动了各类风险早发现、早处置。强化数字赋能指挥调度,通过数 据流整合带动业务流、决策流和执行流,融合视联网、单兵设备、无人机等资源,开发AI视频孪生、 融合会商等功能,形成"一体部署、三级贯通、五级调用、多跨协同"指挥调度体系,确保城市在日常情 况下高效运行、极端情况下安全运行。 中国经济网北京9月28日讯(记者 李方) 9月28日上午,国家数据局举办"数据要素×"系列第三场新闻发 布会。重庆市大数据应用发展管理局党组成员、副局长胡军国指出,重庆以率先承担数字中国建设综合 试点为契机,扎实推进数字重庆建设,创新打造一体化智能化公共数据平台,率先建成市域一体、两级 管理、三级贯通的公共数据资源管理体系,充分释放数据要素乘数效应,较好实现数据 ...
事关数据产业,六部门集体发声
Jin Rong Shi Bao· 2025-05-29 13:46
Group 1: Data Element Action Plan - The "Data Element ×" three-year action plan (2024-2026) aims to enhance scenario-driven demand, promote high-quality supply of data elements, and facilitate compliant and efficient circulation of data [1] - Since the implementation of the action plan, significant progress has been made in the marketization and valuation of data, with nearly 500 digital technology companies established by central enterprises and about 66% of industry leaders purchasing data [1] - Data applications in various sectors are expanding, with notable improvements in industrial and agricultural productivity, such as a 30% reduction in high-end product development cycles and a 5.5% increase in agricultural yield [1] Group 2: Transportation Sector Data Utilization - The transportation sector is identified as a key area for leveraging the multiplier effect of data elements, with a focus on expanding supply through shared and open data [2] - The Ministry of Transport is constructing a comprehensive transportation big model based on a "1+N+X" technical architecture, which includes a general model base and multiple industry-specific models [2] - A transportation data sharing and exchange system has been established, aggregating 2.7 billion data entries and providing 1.4 billion services, facilitating cross-regional and cross-departmental collaboration [2] Group 3: Agricultural Data Integration - The agricultural sector is rich in data resources, with ongoing efforts to integrate new technologies like big data and AI into agricultural practices [3] - The "Farm Direct" app has registered 1.08 million users, linking various agricultural elements and enabling functionalities such as field management and loan approvals [3] - The "Zhejiang Livestock Industry Brain" project exemplifies successful data sharing across multiple departments, aiding in risk management and financial support for livestock farms [3] Group 4: Scientific Data and Innovation - The Chinese Academy of Sciences is promoting the circulation of scientific data elements, generating multiplier effects in fields like biomanufacturing and astronomy [4] - The Academy has established 32 scientific data centers, accumulating 260 petabytes of data, and is enhancing data security and accessibility [5] - Innovations include the development of a data-driven robotic chemist platform and improvements in carbon cycle models based on ecological data [5] Group 5: Healthcare Data Management - The National Medical Insurance Bureau has established a unified medical insurance information platform covering 1.33 billion insured individuals and facilitating the management of 3 trillion yuan in medical expenses annually [6] - The platform processes over 1 billion new data entries daily, with a total of 4.11 petabytes of data accumulated [6] - The integration of drug traceability information into public data resources enhances drug safety and regulatory efficiency [7] Group 6: Emergency Management Data Competitions - The "Data Element ×" competition has launched an emergency management track with three focus areas: enhancing safety production supervision, improving natural disaster monitoring, and advancing emergency management intelligence [8][9] - Teams are encouraged to explore data integration from various sectors to identify potential safety risks and improve disaster response capabilities [8][9] - The competition aims to foster the development of high-quality datasets for training models and applying intelligent robotics in emergency scenarios [9]