Group 1 - The core viewpoint of the article highlights the successful completion of geological work in Jiangsu province during the year 2025, marking it as the first full year of the new geological work framework and system [1] - The meeting emphasized that the geological work has significantly contributed to national energy resource security, ecological environment safety, land space development and protection, geological disaster prevention, and food security, achieving 24 key work results that rank among the top in the national industry [1] - The focus for geological work in 2026 will be on demand orientation, innovation leadership, and digital empowerment, with a commitment to advancing nine key areas of work to enhance safety in five aspects [1] Group 2 - The meeting outlined the importance of strengthening geological technology innovation and accelerating the digitalization of data resources, aiming to enrich the connotation of the "geology+" era [1] - There is a commitment to promoting new economic enhancements in the industry, building a strong and practical workforce, and fostering a culture of proactive geological engagement [1] - The initiatives are designed to provide robust political support for the successful commencement of the 14th Five-Year Plan [1]

Core Insights - The article emphasizes the importance of data asset management as a strategic necessity for companies to leverage data as a core asset for growth and innovation in the evolving digital economy [1][18]. Group 1: Data Value Transformation - The 8.0 version of the guide outlines a three-stage transformation of data value: resourceization, assetization, and capitalization, providing a clear path for companies to follow [2][28]. - Resourceization focuses on ensuring data quality, security, and availability, which are prerequisites for value release [2][28]. - Assetization aims to make data's value visible and measurable through activities like registration, valuation, and internal/external circulation [2][28]. - Capitalization allows data to be treated as a stable asset, enabling innovative financing methods such as pledging for loans and securitization [2][28]. Group 2: Practical Implementation Paths - The guide identifies four core paths for companies to realize data value: digitalization of industries, digital management, digital productization, and ecosystem collaboration [4][5]. - It provides tailored strategies for different types of companies, including value operation-focused firms, transaction innovation-driven companies, compliance-driven enterprises, and foundational management-focused organizations [5][6][7]. Group 3: Future Trends - The report anticipates five key trends in data asset management: integration of AI in data management, real-time decision-making through digital twins, establishment of precise value measurement frameworks, expansion of knowledge management, and active participation in data market ecosystems [9][10][11][12][13]. Group 4: Target Audience - The guide is designed for various stakeholders, including CEOs and CDOs for strategic direction, data department heads for optimizing management systems, business managers for understanding data's role in innovation, and finance/legal personnel for compliance challenges [14][15][16][17].

Group 1 - The core viewpoint emphasizes the critical role of data as a key resource driving high-quality economic and social development, reshaping industry development logic and operational efficiency [1] - The intelligent connected vehicle industry is highlighted as a data-intensive sector, using data to accelerate the iteration of autonomous driving algorithms and the construction of high-precision maps, contributing significantly to China's global market share in new energy vehicles [1] - As of May 2024, the national government service platform has achieved over 540 billion calls, showcasing the effectiveness of data-driven public service modernization in China [1] Group 2 - The need to solidify the foundation for data resource utilization is emphasized, including the establishment of national and local data development strategies, data ownership, circulation rules, and regulatory responsibilities [2] - In the industrial sector, there is a push for equipment networking and digitalization of production processes to achieve automatic data collection across the entire process [2] - The construction of smart agriculture big data platforms is proposed to integrate data across various agricultural processes, enhancing data completeness, consistency, and timeliness [2] Group 3 - The importance of integrating data with new information technologies such as AI, cloud computing, IoT, and blockchain is stressed to create a collaborative system that maximizes the value of data [3] - A robust security framework is necessary to ensure sustainable data utilization, including compliance with data security laws and the establishment of a classification and protection system for core and important data [3] - The management of data throughout its lifecycle is crucial, focusing on risk monitoring, early warning, and emergency response capabilities to protect personal information and corporate secrets [3]

Core Insights - The 2025 "Data Element ×" competition has seen significant participation, with over 23,000 teams and more than 117,000 participants, leading to 893 projects advancing to the national finals and 183 awarded projects [1] - The competition has demonstrated breakthroughs in scale, quality, and effectiveness compared to the previous year, highlighting the increasing circulation of data through open, shared, and authorized operations [1] - The integration of public data in projects is notable, with 53% of projects utilizing public data, and over 43% of these projects adopting the new model of authorized operations [2] Data Utilization and Trading - The competition reflects a growing trend in data product and service diversity, with approximately 40% of enterprises offering subscription indices and analytical reports, and 15% providing high-quality industry data sets [3] - Data trading is becoming a crucial method for enterprises to acquire data resources, with over 50% of final projects having engaged in data trading [3][4] - The new model of authorized operations has been widely practiced, ensuring the safe and compliant use of public data while empowering enterprises to develop valuable data products and services [2] Future Directions - The National Data Bureau plans to support the establishment of a comprehensive service system for data circulation and trading, promote new models for industry data integration, and enhance the capabilities of data merchants in developing data products [4]

Core Viewpoint - The establishment of a trusted data space is crucial for addressing the three major pain points in data circulation: supply-side reluctance to provide data, demand-side hesitance to use data, and the sustainability challenges faced by platforms [1][2]. Group 1: Pain Points in Data Circulation - The supply side is hesitant to provide data due to concerns about where the data will be used and the potential loss of control [2]. - The demand side is reluctant to use data because of uncertainties regarding its source, compliance, and quality [2]. - Platforms face sustainability issues as data technologies continue to evolve, and the current business models are not clearly defined [2]. Group 2: Role of Trusted Data Space - The trusted data space is seen as a solution to the trust issues in data sharing, enabling integrated collaborative development and resource sharing to overcome data silos [2]. - Companies are increasingly recognizing the necessity of building trusted data spaces to ensure effective data supply, flow, and utilization [2]. Group 3: Practical Applications and Benefits - Trusted data spaces have demonstrated their effectiveness in reducing costs and enhancing competitiveness, particularly in industries like home textiles, where they protect intellectual property and original designs through integrated platforms utilizing blockchain and AI [3].

Core Viewpoint - Guizhou Data Exchange (贵数所) is at the forefront of data element market reform in China, having established itself as the first comprehensive big data pilot zone and data trading venue in the country, aiming to create a robust data trading ecosystem and enhance data resource utilization [1][3]. Group 1: Service Positioning and Market Coverage - Guizhou Data Exchange aims to serve a unified national market, focusing on building a national-level data trading platform and core hub for data circulation, with an emphasis on compliance and self-regulation [3]. - The exchange provides services to various market entities, including enterprises, social organizations, and government institutions, covering 20 sectors of the national economy such as agriculture, manufacturing, and transportation [3]. Group 2: High-Quality Data Sets and Partnerships - The high-quality data set area of Guizhou Data Exchange has aggregated nearly a thousand high-quality data sets from over 50 data providers, covering various modalities including text, images, and audio [4]. - Major clients include prominent companies like Huawei, Ant Group, and Tencent, indicating the exchange's significant role in the data service market [4]. Group 3: Innovations and Solutions - Guizhou Data Exchange has implemented several innovative measures to address challenges in the data market, including the establishment of 25 data zones to enhance supply and trust in data transactions [7]. - The exchange has developed the first national data product transaction price calculator, providing a credible pricing reference for data products, which is a significant advancement in the data asset pricing mechanism [8]. - It has also created a comprehensive set of data trading rules to enhance mutual trust among market participants, including guidelines for compliance and security assessments [8]. Group 4: Case Study and Economic Impact - A notable example of the exchange's impact is the successful data asset registration and trading by Benxi Steel Group, which utilized its supply chain financial data product to facilitate financing for small and medium enterprises, thereby promoting inclusive finance [6].

Group 1 - The core theme of the recent Global Digital Economy Conference is "Building Digital Friendly Cities," emphasizing the importance of global digital economic cooperation and the challenges faced by major cities in China, such as Beijing, Shanghai, and Shenzhen, in becoming global benchmarks for digital economy [1] - The transformation of digital cities is now a strategic mission aimed at enhancing national competitiveness and modernizing governance, moving beyond mere technological applications to a focus on public value [1][2] - The relationship between value and technology is crucial, where technology should serve as a means to solve urban issues and enhance citizen welfare rather than being an end in itself [2] Group 2 - The development of digital cities must address the new contradictions and core relationships, particularly focusing on data value attribution, distribution, and realization [3] - The process of data value realization involves three stages: data resourceization, data assetization, and data capitalization, each addressing different aspects of data management and economic value creation [3][4] - Cities should adopt data value management as a top-level strategy, establishing clear data ownership and efficient circulation systems, exploring equitable data revenue distribution models, and creating mechanisms for data value release driven by real-world applications [4]

Group 1 - The mayor emphasizes the importance of enhancing resource development and utilization, promoting compliant and efficient circulation of data resources, and exploring paths for data elementization, resourceization, and assetization [1] - Integer Intelligent Information Technology (Hangzhou) provides professional intelligent data engineering platforms and data set construction services for the AI industry, with applications in smart driving and smart healthcare [1] - The mayor encourages companies to focus on cutting-edge fields, quickly address market demands, accelerate key technology breakthroughs, and diversify application scenarios to drive development in the industry [1] Group 2 - Hangzhou Jinglian Cultural Technology Company builds a self-developed data processing platform, creating a "data kitchen" model to provide high-quality data products for large model manufacturers [2] - Zhejiang Fulian Technology Company is one of the first enterprises in the "reform sandbox" for data elements, with products applied in financial fraud prevention and power operation [2] - The mayor highlights the need for leading enterprises to leverage their technological advantages, continuously innovate and optimize data service products, and explore new models and scenarios for data asset operation and circulation [2] Group 3 - Hangzhou Data Exchange focuses on a compliance system, infrastructure, application scenarios, and ecological construction to explore a compliant transformation path from data resourceization to data value realization [3] - The mayor stresses the importance of top-level design, focusing on key aspects of data resourceization, and enhancing data mining and utilization capabilities [3] - There is a call to strengthen the data element industry ecosystem, innovate systems and mechanisms for data resourceization, productization, and assetization, and promote compliant and orderly data flow [3]

Group 1 - Data is regarded as the "new oil" and "new currency," becoming a fundamental engine for the deepening development of the digital economy [1] - China is enhancing its focus on data as a key factor for gaining competitive advantages in the next round of industrial competition [1][2] - The establishment of a comprehensive system for the value realization of data elements is a long-term and complex project requiring both institutional innovation and practical exploration [1][2] Group 2 - China's path to data value realization will balance safety and development, addressing the relationships between data development and regulation, security and application, as well as domestic and international considerations [2] - The inclusion of data as a production factor in the Fourth Plenary Session of the 19th CPC Central Committee has solidified its status and value enhancement [3] - Recent policies, including the Ministry of Finance's guidelines on data asset management, indicate that data assets are now recognized as important strategic resources for digital economic development [3] Group 3 - Data assetization is a key goal for maximizing the value of data resources, transforming them into a new source of economic growth [4] - The number of data trading institutions and related enterprises is increasing, with approximately 17,600 data trading companies in operation by the end of 2024, 25% of which were established within the last year [4] Group 4 - The process of data value release involves three stages: resourceization, assetization, and ultimately capitalization [5] - Data resourceization is the starting point for value release, focusing on converting raw information into manageable and reusable data assets [5] Group 5 - A successful data monetization strategy requires a closed-loop solution that aligns with national policy, industry development, low-cost investment, sustainable value growth, and high economic efficiency [6] - An example of a successful data service project involved a city investment company that invested over 3 million yuan, resulting in a data asset valuation exceeding 5 million yuan and a market value of over 30 million yuan [6][7] Group 6 - The "value cube" of data is achieved through addressing three key issues: rights confirmation, circulation, and financing [8][10][12] - The establishment of a data rights confirmation system aims to clarify ownership issues, with innovative products like the "three certificates" service for data rights [8] - A dual-driven model of government guidance and market dynamics is being developed to create an efficient and trustworthy data market ecosystem [10] Group 7 - Data asset pledge financing is a common practice that offers low-cost, efficient, and flexible solutions for financing challenges faced by small and medium-sized enterprises [12] - The construction of a data financing platform facilitates the management of data assets, ensuring compliance, quality, and value assessment [12] Group 8 - The essence of the "value cube" lies in the innovation of models, technological empowerment, and ecological collaboration, which together facilitate the realization of data value [14]