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]