12月22日，国家数据局发布第四批次30个公共数据"跑起来"示范场景。加上前三批次，目前已有100个 示范场景对外发布。国家数据局副局长陈荣辉表示，为充分释放公共数据价值，国家数据局组织实施公 共数据"跑起来"示范场景建设。下一步，将持续推进示范场景建设与推广，推动场景从"点上突破"走 向"面上开花"，以公共数据开发利用引领撬动各方数据融合应用，更好释放数据要素价值。 场景领域不断拓展 公共数据开发利用是数据要素市场化配置改革的先导工程。当前，公共数据"跑起来"示范场景建设进展 如何？在国家数据局12月22日举行的第四场"数据价值化 我们在行动"新闻发布会上，陈荣辉介绍了3个 方面的情况。 打造场景样板，数据赋能作用显现。第一批公共数据"跑起来"示范场景经过一年建设，各项任务已经基 本完成。社会效益和产业带动作用初步显现，形成了可复制、可推广的建设模式。比如，在产业发展领 域，海关总署依托跨境贸易通关数据，助力中小微企业降低融资成本；物流数据开放互联有效提升多式 联运组织效率，降低物流成本；自然资源部"天地图"应用，已成为面向企业和公众提供基础地理信息服 务的重要平台。 申报热情高涨，场景领域不断拓展。从四批 ...

申报热情高涨，场景领域不断拓展。从四批次场景情况来看，数据供给方式从"共享为主"向"共 享、开放、授权运营协同推进"转变。第四批场景区域覆盖范围更广，其中西部和东北地区场景占比达 35%。场景领域不断拓展，第四批场景逐步向高频民生服务、特色产业、基层治理等纵深领域延伸，其 中医疗检查检验结果共享互认等共性场景，将创造更大示范价值和社会效益。 发挥带动作用，推广经验做法。在公共数据开发利用落地实施方面，探索出一系列有益的经验做 法。后续将组织开展公共数据"跑起来"典型案例分享，集中展示数据开发利用模式，推动互学互鉴、强 化示范引领。 提升"外贸+金融"服务质效 "单一窗口"通过公共数据赋能，在提升"外贸+金融"服务质效方面取得了明显成效。数据显示，截 至目前，"单一窗口"金融服务已累计办理国际结算1272亿美元，融资授信1488亿元人民币，出口信用保 险78万份，惠及外贸企业45万家。 人民日报海外版记者 邱海峰 12月22日，国家数据局发布第四批次30个公共数据"跑起来"示范场景。加上前三批次，目前已有 100个示范场景对外发布。国家数据局副局长陈荣辉表示，为充分释放公共数据价值，国家数据局组织 实施公共数据 ...

重庆高速集团已构建起覆盖全路网的智慧化运营体系，为公众出行提供更安全、高效的交通服务。图为 工作人员在该集团智慧运行中心查看高速公路相关实时数据。孙凯芳摄（人民视觉） 12月22日，国家数据局发布第四批次30个公共数据"跑起来"示范场景。加上前三批次，目前已有100个 示范场景对外发布。国家数据局副局长陈荣辉表示，为充分释放公共数据价值，国家数据局组织实施公 共数据"跑起来"示范场景建设。下一步，将持续推进示范场景建设与推广，推动场景从"点上突破"走 向"面上开花"，以公共数据开发利用引领撬动各方数据融合应用，更好释放数据要素价值。 场景领域不断拓展 公共数据开发利用是数据要素市场化配置改革的先导工程。当前，公共数据"跑起来"示范场景建设进展 如何？在国家数据局12月22日举行的第四场"数据价值化 我们在行动"新闻发布会上，陈荣辉介绍了3个 方面的情况。 打造场景样板，数据赋能作用显现。第一批公共数据"跑起来"示范场景经过一年建设，各项任务已经基 本完成。社会效益和产业带动作用初步显现，形成了可复制、可推广的建设模式。比如，在产业发展领 域，海关总署依托跨境贸易通关数据，助力中小微企业降低融资成本；物流数据开 ...

（来源：经济参考报） 12月22日，国家数据局发布新一批30个公共数据"跑起来"示范场景，通过场景培育和开放，促进公共数 据开发利用。本次发布的30个公共数据"跑起来"示范场景，涉及二手车交易卖方身份核验、医疗检查检 验结果共享互认、学业数据可信服务、玉米全产业链大数据应用等经济和民生领域。 在当日举行的"数据价值化 我们在行动"系列新闻发布会（第四场）上，国家数据局副局长陈荣辉表 示，下一步，将继续加大应用场景建设和开放力度，持续推进公共数据"跑起来"示范场景建设与推广， 推动场景从"点上突破"走向"面上开花"，以公共数据开发利用引领撬动各方数据融合应用，更好释放数 据要素价值。 至此，我国已发布四批次共100个公共数据"跑起来"示范场景。其中，第一批公共数据"跑起来"示范场 景经过一年建设，各项任务已经基本完成。社会效益和产业带动作用初步显现，形成了可复制、可推广 的建设模式。 例如，在民生服务领域，推动医疗保障"一人一画像"、旅游景区入园便利、社保数据支撑就业服务等场 景建设，为参保精准管理、游客"免证入园"、职业信用评估等应用提供支撑。在产业发展领域，海关总 署依托跨境贸易通关数据，助力中小微企业降低 ...

公共数据授权运营情况如何？国家数据局解答 中新网北京12月22日电(记者 吴涛)随着数据价值的进一步探索，授权运营成为公共数据开发利用的重要 方式，目前我国公共数据授权运营进展情况如何呢？ 22日，国家数据局党组成员、副局长陈荣辉回应了这一热点问题。他表示，授权运营作为公共数据资源 开发利用的一种创新模式，是对公共数据开放的有益补充，有助于激发供数动力和用数活力、更好促进 数据要素市场化价值化。自公共数据"1+3"政策体系发布以来，各地区各部门积极探索、创新突破，取 得了积极成效。 编辑：熊思怡 广告等商务合作，请点击这里 本文为转载内容，授权事宜请联系原著作权人 中新经纬版权所有，未经书面授权，任何单位及个人不得转载、摘编或以其它方式使用。 关注中新经纬微信公众号(微信搜索"中新经纬"或"jwview")，看更多精彩财经资讯。 据介绍，授权运营能让数据资源供给进一步丰富。授权运营通过引入专业化力量对数据进行加工治理， 有力平衡了数据流通与安全之间的矛盾，让更多数据可以放心供出来。比如，北京建设金融、气象、时 空等公共数据专区，数据流通规模超3000亿条，服务普惠金融、城市运行、交通治理等场景。 陈荣辉还表示 ...

为响应济南市委"持续做好'泉融通'平台运营推广"的要求，济南工行在同业中率先创新推出特色政务场 景线上融资产品—"泉融e贷"，是全市首个依托"泉融通"平台构建线上智能政务模型、开发普惠融资产 品的典型案例，更成功实现了"政务数据"向"金融生产要素"的转化，"泉融e贷"还以其精准、聪明、流 畅的特点备受小微企业青睐，显著提升了普惠金融服务质效。 在数据安全方面，济南工行与"泉融通"平台深度合作：双方签署协议明确法律权责，搭建业务传输专 线，并同大数据局及各数源部门保持密切沟通，及时更新与反馈数据质量，确保政务数据的真实可靠。 运用"可信空间"、区块链加密传输、"数据沙箱"、"隐私计算"等先进技术，保障授权数据调用的安全合 规。模型本地化部署也确保了产品输出的稳定性。同时，在办理"泉融e贷"业务时，产品严格遵循法律 法规及监管要求，客户需线上签署授权书，确保信用数据合法合规使用。 创新驱动破解融资瓶颈，数据融合构建智慧模型 下一步，济南工行积极响应数字山东建设，持续深化政务数据创新应用，加速现有模型向农业产业、科 创企业等场景延伸，打造普惠金融数字化新范式，为加快推进现代化强省建设贡献工行力量。 "泉融e贷"的核 ...

Group 1 - Shandong Kelly Electric Co., Ltd. and Jinan Jiajin New Materials Co., Ltd. successfully secured loans through the "Quanyin E-loan" platform, addressing the financing challenges faced by small and micro enterprises in Jinan [1][2] - The "Quanyin E-loan" model utilizes government data to accurately assess credit limits for small businesses, providing instant online loans with a maximum limit of 3 million yuan, resulting in a total loan issuance of 1.796 billion yuan within a year and an average credit increase of 800,000 yuan per business [2][3] - The Jinan Financial Investment Holding Group's digital technology subsidiary has developed 363 data products to facilitate personalized data services for financial institutions, enhancing the efficiency of loan processes [3][4] Group 2 - Jinan has established a unified data standard and integrated data resources from 77 departments, resulting in over 472 billion data entries to support data sharing applications across various government units [4][5] - The city has implemented a legislative framework to promote the authorized operation of public data, leading to the development of 290 public data products and over 800 transaction orders [4][5] - Jinan's data security measures include the use of blockchain technology and privacy computing to ensure safe data circulation while maintaining compliance, allowing businesses to authorize banks to access necessary information for loans [5]

Core Viewpoint - Jinan is leveraging data resources to address the financing challenges faced by small and micro enterprises, facilitating easier access to credit and promoting new industries and business models through data-driven solutions [2][3][7]. Group 1: Financing Solutions for Small Enterprises - Shandong Kelly Electric Co., a small tech enterprise, successfully secured a loan of 2.79 million yuan through the "泉融E贷" platform, highlighting the effectiveness of data-driven financing solutions [2]. - The "泉融E贷" program has disbursed a total of 1.796 billion yuan in loans, with an average credit increase of 800,000 yuan per enterprise, and has reported zero bad debts since its launch [3]. - The program utilizes a comprehensive data platform, "泉融通," which integrates various public data sources to assess creditworthiness, allowing banks to make informed lending decisions [3][4]. Group 2: Data Integration and Application - Jinan has established a unified data standard and integrated over 20,081 data resources from 77 departments, facilitating data sharing and application across various sectors [5]. - The city has developed 290 public data products and completed over 800 transactions, delivering more than 12 million data entries to support various applications [5]. - The "泉城链" platform has been created to ensure secure and authorized access to sensitive data, allowing businesses to share necessary information with banks for loan applications [6]. Group 3: Technological Innovations and Security - Jinan's data management incorporates advanced technologies such as blockchain and privacy computing to ensure data security and compliance, allowing for safe data circulation [6]. - The city has implemented a "data insurance box" feature through the "爱山东" app, enabling businesses to authorize banks to access relevant data securely [6]. Group 4: Economic Impact and Future Prospects - The initiatives in Jinan are aimed at releasing data dividends to foster new industries, business models, and a digital economy, positioning the city as a leader in data-driven economic transformation [7].

Core Insights - The "泉融e贷" project won first place in the financial services track of the 2025 "Data Element X" Shandong division finals, showcasing Jinan Industrial Bank's leading capabilities in data-driven inclusive finance [1][2] - The project addresses the financing difficulties faced by small and micro enterprises by integrating various government data sources to create a new credit assessment model [1] - The use of advanced technologies such as big data and cloud computing has enabled precise pre-approval for 1.14 million market entities in Jinan, significantly improving financing accessibility [1] Group 1 - The "泉融e贷" project achieved a score of 89.2, outperforming 30 competing financial institutions [1] - The project leverages Jinan's comprehensive financing service platform "泉融通" to overcome traditional credit assessment challenges [1] - The innovative practices of the project provide a replicable model for financial services aimed at small and micro enterprises, aligning with the core goal of the "Data Element X" competition [1] Group 2 - The project combines regional data model advantages with standardized risk control models from the parent bank, laying a solid foundation for future applications [2] - Future expansions of the credit assessment model will target key sectors such as agriculture and technology innovation, exploring deeper integration of data elements with the real economy [2] - The award signifies a significant step for Jinan Industrial Bank in applying data elements and innovating inclusive finance, offering valuable insights for financial technology development at both provincial and national levels [2]

Core Insights - The article discusses the significant impact of digitalization and data as a production factor in various sectors, highlighting the emergence of data as a crucial asset in economic development, particularly in Shandong Province [1][2] - It emphasizes the challenges faced in the implementation of data asset accounting, including insufficient infrastructure, lack of active participation from private enterprises, and the need for a robust data market [3][4] Group 1: Data Asset Accounting - By 2024, data is expected to be recognized as a key asset, with 92 listed companies and 228 non-listed companies in China reporting data asset accounting [1] - Shandong Province has seen state-owned enterprises leading the way in data asset accounting, with the Shandong High-Speed Group reporting a data asset value of 3.51 million yuan and an assessed value exceeding 72 million yuan [2][3] - The reluctance of private enterprises to engage in data asset accounting is attributed to high costs, low returns, and operational complexities [2][3] Group 2: Challenges in Data Market Development - The article identifies several challenges, including a lack of active participation from enterprises, an immature data market, and insufficient infrastructure for data operations [3][4] - Shandong has established regional data trading institutions, but its trading volume of 220 million yuan is significantly lower than that of leading cities like Shenzhen and Shanghai [5][6] - The absence of a provincial-level public data operation platform hinders the development of a robust data market ecosystem in Shandong [6][7] Group 3: Data Security and Trust - Concerns regarding data security and the establishment of a trusted data space are highlighted as critical issues for the industry [7][8] - The need for a trusted data space is emphasized to ensure data can be shared and utilized securely, with various types of trusted spaces being proposed [8][9] Group 4: Revenue Distribution and Coordination - The article discusses the importance of coordinating interests across departments and levels for effective data utilization and revenue distribution [10][11] - A proposed revenue-sharing model in Qingdao suggests that 50% of the revenue generated from public data operations would be reinvested into supporting data resource management [10][11]