Core Insights - Data is recognized as the fifth production factor, characterized by non-competition, replicability, and unlimited growth potential, making its value extraction process more complex than traditional production factors [1] - The development of the data factor market relies heavily on a clear policy framework and implementation pathways, with local data trading institutions and data merchants emerging as key drivers [1] - The establishment of a robust ecosystem for data supply and usage is essential to achieve the goals of effective data flow and security [1] Group 1: Industry Overview - The data factor market is currently in a critical phase driven by policy and practical exploration, with the establishment of the National Data Bureau marking a significant step towards a unified national data market [19][20] - By 2025, the market size is projected to exceed 200 billion, with a compound annual growth rate of over 25% [23] - The construction of a complete national data circulation system is planned over the next five years, aiming to empower the real economy and stimulate growth [27] Group 2: Evaluation of Service Providers - The selection of "Outstanding Service Providers in the Data Factor Industry" is based on comprehensive evaluations by iResearch and industry experts, focusing on the capabilities of data developers, operators, and IT technology providers [2][4] - The evaluation model includes four core dimensions: industry depth, product and technology capabilities, service capabilities, and ecosystem capabilities [4] Group 3: Case Studies and Applications - Neusoft's City Data Value Empowerment Platform integrates data to enhance urban services in health, employment, and smart governance, creating a comprehensive service ecosystem [11][12] - The "Fujian Health Public Service Operation Platform" aims to provide a full lifecycle service system, while the "City Human Resources Development Platform" connects various stakeholders to promote employment and training [15] Group 4: Future Directions - The focus on high-quality data sets and specialized intelligent entities is expected to become mainstream, with ecosystem co-construction and scenario-building capabilities as core competitive advantages [20] - The establishment of a "trusted data space" is crucial for providing diverse data product choices to cross-domain consumers [25] - The industry faces challenges such as an incomplete pricing system and compliance barriers, which need to be addressed to facilitate the free flow of data in the market [31][28]

Core Insights - The release of data value is accelerating the reconstruction of content production, user interaction, and platform service models in the media industry, injecting new vitality into the sector [1] - Data-driven decision-making is replacing traditional experience-based judgments, optimizing resource allocation, and enhancing operational efficiency in media services [2] Group 1 - The application of data is transforming brand communication from a broad approach to precise targeting, enhancing the attractiveness and interactivity of brand messaging [2] - The media industry's data capability construction is accelerating, with a focus on exploring the value of data elements while ensuring data security and compliance [2] - The integration of local media with urban business environments is expected to enhance the core advantages of information dissemination and resource linking, shaping city images and showcasing urban vitality [2]

"下一步，我们将支持试验区在更多领域开展先行先试，在推进数据市场化价值化上探索出更多新做 法。"栾婕表示，同时将支持地方因地制宜加强试验探索，打造更多可感可及的应用场景；进一步加强 工作协同，推动互学互鉴，破解痛点难点问题，探索数据价值释放路径。 （文章来源：科技日报） "目前，我省在推动数据要素深度融合并赋能先进制造业发展方面，已经取得了较好成效，呈现点上有 突破、链上有联动、面上有成效三大特点。"湖南省数据局党组成员、副局长周述东说，目前，湖南已 建成3个全球"灯塔工厂"、9家卓越级智能工厂、24个国家智能制造示范工厂，通过数据深度赋能，推动 关键工序数控化率超60%，经营管理数字化普及率达75%。 热带特色高效农业是海南自由贸易港四大主导产业之一。海南省发展改革委党组成员、副主任黄鹏谈 道，海南省着力打造"种业数据一张网"，建成集科研、生产、销售、科技交流、成果转化为一体的国家 南繁生物育种服务平台，汇聚种质资源信息、育种试验数据、表型信息数据等育种科研数据资源。此 外，探索构建全国种业科研数据交易体系，推动种业科研数据价值释放，为种业数据高效使用和流通交 易奠定了良好基础。 18日，国家数据局举行数据 ...

新京报贝壳财经讯（记者陈维城）9月18日，在国家数据局数据要素综合试验区新闻发布会上，国家数 据局新闻发言人、政策和规划司副司长栾婕表示，国家数据局成立以来，坚持问题导向，加快推进数据 产权、市场交易、安全治理等制度建设，破解数据要素市场化配置改革中的痛点问题。 二是打造一批可推广、可复制的经验做法。试验区建设重点是要发挥地方示范带动作用，推动"一地创 新，全国推广"。各试验区因地制宜，立足产业基础、区位优势，积极探索，涌现出一些典型案例。比 如，湖南依托文化产业优势，充分发挥数据在促进文化和科技深度融合中的作用，助力打造世界级音视 频产业集群，探索数据赋能产业发展的"湖南经验"。河南在交通物流、医疗健康等领域探索了数据资源 开发利用的典型做法。下一步，我们将支持地方因地制宜加强试验探索，打造更多可感可及的应用场 景。 三是解决一批数据价值释放的痛点问题。国家数据局成立以来，坚持问题导向，加快推进数据产权、市 场交易、安全治理等制度建设，破解数据要素市场化配置改革中的痛点问题。各试验区积极开展先行先 试，推动解决供数、用数难题。比如辽宁从农业农村等重点行业入手，以公共数据资源开发利用为抓 手，探索数据要素价值 ...

Group 1 - The core viewpoint of the news is the progress in the construction of data factor comprehensive pilot zones, emphasizing innovative reform measures, replicable practices, and addressing pain points in data value release [1] - The pilot zones are implementing bold reforms and exploring new paths for market-oriented data factor allocation, with initiatives like the "reform sandbox" in Hangzhou and a three-stage compliance review model in Wenzhou [1] - The project in Henan province has successfully integrated over 600 types of basic data sets, leading to a significant reduction in traffic accident rates by 53.2% to 58% and congestion rates by 76% to 85.5% [1] Group 2 - Liaoning province is building a rural land data resource library with 870,000 entries, which has improved conflict resolution regarding land disputes and achieved a 94.8% rectification rate for violations in Shenyang [2] - The National Data Bureau plans to support pilot zones in further explorations across various fields, encouraging local adaptations and enhancing collaborative efforts to address challenges in data value release [2]

Core Insights - Data is the core productivity of the digital economy, and its circulation is transitioning from "internal circulation" to "external circulation" [1][4] - The lack of trust presents three major challenges in releasing data value: insufficient processing, integration, and verification [1][4] Group 1: Data Challenges and Solutions - A significant amount of data remains in its "raw" state, lacking primary processing and handling [5] - The existence of "data silos" makes it difficult to integrate multi-source data, hindering the formation of high-value data products [5] - The establishment of a "trusted data space" is crucial for promoting credible data circulation and utilization across different entities, industries, and regions [1][5] Group 2: Trusted Data Space Development - The concept of a "trusted data space" involves connecting multiple parties based on consensus rules to achieve data resource sharing and utilization [2][3] - By 2028, China aims to establish over 100 trusted data spaces, creating a series of solutions and best practices [3][4] - The trusted data space can enhance trust in data processing, integration, and verification, addressing the industry's strong expectations for data security [4][5] Group 3: Agricultural Data Utilization - In Jiamusi, Heilongjiang, public data is being utilized to support modern agricultural inclusive finance, allowing farmers to access loans more easily [2][3] - The integration of over 50,000 agricultural data points into a standardized system is underway, leveraging blockchain and other technologies for data-driven financial services [2][3] Group 4: Future Directions and Challenges - Current applications of trusted data spaces are mostly exploratory and need to develop replicable and scalable models [6] - High-level security guarantees are essential for unlocking data value, especially in high-value and sensitive industries [5][6] - Continuous technological advancements and policy support are necessary to optimize data value release and address security threats in data circulation [5][6]