今天分享的是：艾瑞咨询：2025年中国城市可信数据空间行业研究报告 报告共计：27页 艾瑞咨询2025年中国城市可信数据空间行业研究报告核心总结 在城市化与数字化转型背景下，数据成为城市治理核心资源，城市可信数据空间作为政府主导、多方共建的城市数据基础设施，为数据 可信、安全、合规流通利用提供通道，对城市治理与产业赋能意义重大。艾瑞咨询此报告从多维度剖析该行业。 报告先明确城市可信数据空间概念，指出其是可信数据空间的城市级形态，以公共数据为主、社会数据为辅，旨在打破数据流通困境、 激活数据要素潜能、促进城市治理升级。发展驱动因素多元，政策上，国家与地方出台系列政策，鼓励建设并开展试点，推动行业规模 化落地；技术上，隐私计算（如多方安全计算、联邦学习等）解决数据"可用不可见"，区块链实现数据存证溯源与规则自动执行，为数 据流通提供技术保障；需求上，当前数据开发利用不足，城市治理面临数据沉睡、协同低效等问题，亟需可信数据空间盘活资源并以公 共数据牵引多维度数据融合。 接着阐述发展现状，城市可信数据空间以政务云为基石，构建数据流通利用支撑底座，搭配数据运营管理与开发利用两大平台，形成总 体框架，核心能力涵盖可信管控 ...

Core Viewpoint - The Shandong Provincial Government is leveraging the "Data Element ×" initiative to enhance the development and utilization of data resources, aiming to create an innovative service system for data elements and improve the effectiveness of market-oriented reforms in data allocation [2]. Group 1: Regulatory Framework - Shandong is accelerating the legislative process for the "Shandong Provincial Data Regulations" and has introduced several management guidelines, including the "Public Data Resource Registration Management Norms" and "Data Trading Norms," establishing 283 data standards to ensure legal and systematic data utilization [2][3]. Group 2: Data Utilization and Infrastructure - The province is focusing on enhancing data production capabilities through integrated digital government reforms, establishing a unified foundational information platform, and creating a comprehensive big data platform system, which has facilitated over 52 billion data sharing instances and opened 48 billion data records [2][3]. - Shandong has developed over 90 high-quality datasets in sectors like industrial manufacturing and transportation, promoting the use of public data through 141 authorized operational scenarios [2][3]. Group 3: Data Circulation and Market Development - The province is promoting data circulation by organizing events like the "Data Market Construction and Supply-Demand Matching" and has launched the "Data Market," resulting in the listing of over 1,900 data products from local data trading companies [3]. Group 4: Industry Empowerment - Shandong is utilizing its geographical advantages and marine resources to develop marine data, accumulating over 50 petabytes of high-quality marine data, which constitutes 25% of the national total, and has established a marine big data trading service platform [3]. - The application of data in marine fisheries and disaster prevention has led to significant improvements, such as a 50% increase in monitoring efficiency and a 19% rise in output per unit sea area [3]. Group 5: Talent Development - The province has implemented measures to accelerate the cultivation of digital talent, including 51 advanced training sessions for over 1,500 high-level digital professionals, and has introduced chief data officer roles in government and chief data engineer roles in enterprises [4]. Group 6: Future Directions - Shandong will continue to focus on market-oriented reforms in data element allocation to stimulate strong data-driven momentum, contributing to the modernization efforts in China [5].

在数字经济时代，数据已成为关键生产要素。尤其在金融领域，如何实现数据的安全可信流通与高效利 用，成为推动行业数字化转型的核心议题。山东联信数字科技有限公司依托自身技术优势，构建了 以"融沂通"平台为典型应用的金融可信数据空间，为区域金融服务注入全新动能。 作为"融沂通"平台的技术研发与运营单位，山东联信数字科技有限公司以"数据要素化、流通合规化、 应用场景化"为目标，打造了"1+3+N"金融可信数据空间架构： "1"指金融大数据枢纽平台，形成数据汇聚与智能分析的核心载体； "3"代表可信管控、资源交互与价值共创三大核心能力； "N"覆盖信贷风控、监管科技、政策匹配等多类金融场景。 联信数科依托隐私计算、区块链、人工智能等前沿技术，构建起涵盖数据采集、治理、流通、应用全链 条的技术体系，确保数据"可用不可见、可溯可审计"。 1. 隐私计算赋能数据"不出域"流通 联信数科集成联邦学习、多方安全计算与数据安全沙箱等技术，实现多方数据联合建模与分析，原始数 据不离域，从源头保障数据安全与隐私合规。 2. 区块链构建可信流通链条 通过区块链技术对数据授权、访问、使用等环节进行全程存证，建立不可篡改的可信日志，支持数据权 ...

Core Viewpoint - The company is actively advancing research and implementation of post-quantum cryptography and privacy computing solutions, targeting key industries such as banking, insurance, and telecommunications [1] Group 1: Post-Quantum Cryptography - The company is continuously progressing in post-quantum cryptography algorithm research, migration, and industry application [1] - The company has obtained relevant patents for key technologies in post-quantum cryptography [1] - Multiple core products support post-quantum cryptography algorithms, facilitating their replacement and migration in critical business scenarios for clients in banking, insurance, telecommunications, and securities [1] Group 2: Privacy Computing - The company has launched the NetPEC privacy computing platform and secured related technical patents [1] - The platform enables collaborative computing, data fusion, and joint modeling among multiple institutions, enhancing the ability to extract and utilize the immense value of data elements [1] - The company addresses two major issues: data silos and data privacy protection, promoting data security integration and shared circulation in finance, insurance, and government sectors [1] Group 3: Cloud Native Security - The company does not currently offer cloud-native security products, but its existing security products support cloud-native environments [1]

Group 1: Report Overview - The report is about a research on Zhejiang University Network New Co., Ltd. in the Internet service industry on September 17, 2025 [1][2][17] Group 2: Core Views - The company will continue to deepen the "AI DRIVEN" development strategy, build and improve the full - chain AI large - model service system, and accelerate the digital transformation of various industries [24] - The company will use IT infrastructure resources for high - quality and inclusive computing power matching, support mainstream model access for一站式 services, and participate in data platform construction for data asset value mining [24] - The company will drive with digital technologies, provide a full - stack empowerment platform for government and enterprise digital transformation, and expand the industry ecosystem [25] Group 3: Summary by Directory 01. Research Basic Situation - The research object is Zhejiang University Network New Co., Ltd., belonging to the Internet service industry. The reception time is September 17, 2025. The reception staff includes the chairman, vice - presidents, CFO, board secretary, and independent director [17] 02. Detailed Research Institutions - The reception objects include investors and others [20] 03. Research Institution Proportion - No relevant content provided 04. Main Content Data - The company's future business development focuses on building an AI large - model service system in three aspects: computing power service, model service, and data service [24] - There has been no large - scale block trading of more than 5% shareholders recently, and all equity changes of such shareholders have been disclosed as required [25] - In the first half of 2025, the company's intelligent computing cloud service achieved an operating income of 149.2423 million yuan. The transformation of the intelligent computing business takes time, and the overall business is in a loss state [26]

Group 1 - The controlling shareholder of Digital Certification has changed to Beijing Data Group, while the actual controller remains unchanged as Beijing State-owned Assets Management Co., Ltd [2] - The establishment of Beijing Data Group aims to optimize strategic layout and industrial structure, enhancing the development of information services and the digital industry [2] - The initiative is part of the municipal government's efforts to build a "one area and three centers" framework, focusing on the needs of Beijing's data industry [2] Group 2 - Beijing Data Group will enhance the technological innovation capabilities of state-owned capital investment companies, focusing on cutting-edge technology fields such as big data, artificial intelligence, blockchain, privacy computing, and cybersecurity [2] - The group aims to strengthen service and support functions, contributing to the construction of Beijing as a global digital economy benchmark city [2] - The overall goal is to assist in the high-quality development of the capital city [2]

Group 1 - The core viewpoint of the article is that Digital Certification (300579.SZ) has undergone a change in its controlling shareholder to Beijing Data Group, which aims to enhance the development of the digital industry in Beijing [2] - The actual controller of the company remains unchanged, still being Beijing State-owned Assets Management Co., Ltd [2] - The establishment of Beijing Data Group is part of the municipal government's initiative to build a "one zone and three centers" strategy, focusing on the needs of the data industry in Beijing [2] Group 2 - The objectives of Beijing Data Group include optimizing strategic layout and industrial structure, strengthening the role of state-owned capital investment companies in leading industries, and promoting the development of new productive forces [2] - The company aims to enhance its technological innovation capabilities in cutting-edge fields such as big data, artificial intelligence, blockchain, privacy computing, and cybersecurity [2] - The initiative also focuses on reinforcing service support functions to help establish Beijing as a global benchmark city for the digital economy, contributing to high-quality development in the capital [2]

Core Insights - The data trading market is a complex system focused on the circulation of data products and services, aiming to solve the challenges of data flow and unlock data value [1][5] - China's data trading market has rapidly evolved since its inception in 2015, with a projected market size of 2,115.4 billion yuan by 2024 and expected to exceed 7,159 billion yuan by 2030 [1][7] - The global data trading market reached approximately $126.1 billion in 2023, with Asia-Pacific being the fastest-growing region [7] Industry Overview - The data trading market consists of data providers, data consumers, trading venues, technical support, third-party service providers, and regulatory bodies, forming a complete ecosystem [2] - Data trading can be categorized by trading venues (on-exchange and off-exchange) and product types (data sets, data services, data applications, and off-exchange services) [3] Policy Framework - The Chinese government has implemented a series of policies, including the "Data Twenty Articles," to support the development of the data trading market, focusing on data ownership, circulation, revenue distribution, and security governance [6] - The policies aim to create a standardized, compliant, and scalable market structure, enhancing the overall ecosystem [6] Global Market Trends - The global data trading market is expected to grow to $177.9 billion by 2025 and surpass $370.8 billion by 2030, with North America, Europe, and Asia-Pacific as the three core markets [7] - Key industries driving data trading include finance, healthcare, retail, and manufacturing [7] China's Market Development - By 2025, China's data trading market is expected to reach 2,840.9 billion yuan, with a compound annual growth rate of 20.3% from 2025 to 2030 [7][8] - The market has developed a multi-layered structure with one national-level exchange and over 50 regional institutions [7] Regional Market Dynamics - The data trading market in China exhibits a "gradient differentiation and collaborative development" pattern, with leading regions including Guangdong, Zhejiang, Jiangsu, Shanghai, Beijing, and Guizhou [15] - The Yangtze River Delta and Guangdong-Hong Kong-Macau Greater Bay Area are identified as the primary trading regions [15] Future Trends - The data trading market is transitioning towards "fine value mining" driven by technologies such as privacy computing and AI, with significant growth expected in vertical industries like manufacturing and healthcare [16] - The integration of data trading with logistics and finance is anticipated to create new growth opportunities, particularly in cross-border data flow [17] - A nationwide integrated market is forming, with key nodes like Beijing, Shanghai, and Guizhou collaborating to enhance resource allocation and break down data silos [18]

Core Viewpoint - The 12th China International Fair for Trade in Services (CIFTIS) showcased China UnionPay's (CUP) independent exhibition, highlighting its advancements in financial technology and international business development, aligning with the theme of "Digital Intelligence Driving Open Cooperation" [1] Group 1: Digital Financial Innovations - China UnionPay exhibited several technological achievements, including AI-integrated payment services and a marketplace for financial tools, demonstrating its commitment to integrating cutting-edge technologies like artificial intelligence and big data into its services [3] - The UnionPay MCP intelligent payment service allows users to complete payments through dialogue, covering both domestic and international scenarios [3] - The "UnionPay Cloud Intelligence" product architecture and privacy computing practices were also showcased, emphasizing the company's focus on financial technology advancements [3] Group 2: International Expansion - China UnionPay has accelerated its internationalization strategy, establishing a global acceptance network in 183 countries and regions with over 2,600 partner institutions [5] - The exhibition highlighted innovations in cross-border payment tools, including mobile POS products, cross-border remittances, and tax refund services, showcasing UnionPay's diverse offerings in the cross-border payment sector [5] - The new "four-party model" for QR code cross-border interoperability was a focal point, with UnionPay facilitating digital upgrades in local payment industries across 19 countries, including Indonesia, Vietnam, Japan, and Brazil [5] Group 3: Services for Beijing - The "Chuangyou Tong" innovative terminal was presented, designed to enhance the experience of inbound tourists by supporting multiple services such as Wi-Fi, UnionPay QR code payments, translation, and maps [6] - This terminal aims to provide a seamless experience for visitors, contributing to Beijing's development as an international exchange and consumption center [6] - UnionPay's participation in CIFTIS reflects its commitment to leveraging technology in payment solutions and fostering global connections [6]

Core Viewpoint - The ownership of patient medical records is a contentious issue, with hospitals, doctors, and patients each claiming rights over the data generated during medical treatment [1][2]. Group 1: Data Ownership and Privacy - Data is recognized as a new production factor, but its ownership remains disputed, particularly regarding patient medical records [1]. - Patients consider their medical records as personal privacy, while doctors argue that their expertise is necessary for data generation, and hospitals claim that without their equipment, data cannot exist [1]. - Ordinary outpatient medical records are typically owned or managed by patients, while inpatient records are managed or owned by hospitals [1]. Group 2: Challenges in Data Utilization - The complexity of data ownership leads to difficulties in data circulation and utilization, with concerns about data leakage and privacy infringement [2]. - The concept of "privacy computing" is proposed as a potential solution, allowing data value extraction without accessing original data, thus addressing ownership ambiguities [2]. - Privacy computing enables collaborative data use without transferring data outside its original domain, mitigating security and privacy risks [2]. Group 3: Technical Aspects of Privacy Computing - Privacy computing faces performance limitations, particularly in distributed models that rely on complex algorithms and frequent data transmission [3]. - New centralized privacy computing models have emerged to alleviate performance issues by encrypting data within a trusted execution environment [3]. - A hybrid approach combining centralized and distributed privacy computing is recommended based on specific needs, balancing data security and performance [3].