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]

Core Insights - The book "Data Capital" proposes a new framework for a fair data economy, exploring the capitalization of data across various sectors such as healthcare and finance, and aims to create a "smart economy" through trusted technology and artificial intelligence [1][4] Group 1: Data Cooperatives - The concept of a "data cooperative" is introduced to facilitate data sharing among citizens and enhance data innovation capabilities [4] - Establishing data property rights and sharing mechanisms can lead to the tokenization of data and its infrastructure, reshaping traditional banking and financial systems [4] Group 2: Economic Implications - The development of data algorithms and AI is expected to create new forms of economic participation, necessitating a more resilient social system [4] - The book emphasizes the risks and uncertainties in the new economic ecosystem, which directly challenges existing financial systems [4] Group 3: Digital Currency and Tokenization - The latter part of the book focuses on digital currency systems, tokenized financial ecosystems, stablecoins, and virtual asset trading networks, which are closely related to digital currencies [4] - The authors provide insights into the fundamental principles, roles, and future expectations of these digital currency-related topics, marking them as the most essential parts of the book [4]

Group 1 - The trend of data asset value realization is becoming more prominent, with more data being transformed into high-value assets, supported by financial market innovations that open diverse financing channels for related companies [1] - Experts predict that the market-oriented allocation mechanism for data factors will continue to improve, accelerating the process of data value release, which is expected to become a core engine driving high-quality development of the digital economy [1] Group 2 - Aopu Mai Biotechnology Co., Ltd. announced plans to acquire 100% of Pengli Biopharmaceutical Technology (Shanghai) Co., Ltd. through a combination of share issuance and cash payment, highlighting the importance of data as a valuable resource for companies [2] - Companies are increasingly focusing on building comprehensive data management systems to enhance data quality and extract data value, with many establishing specialized data management teams [2][3] Group 3 - A growing number of listed companies have appointed Chief Data Officers to strengthen data strategy and promote deep integration of data resources with business operations [3] - Companies are leveraging professional systems to achieve intelligent and refined data asset management, utilizing data asset management platforms and AI technologies to maximize data value [3] Group 4 - The process of data asset capitalization is crucial, with the inclusion of data assets in financial statements providing solid support for the confirmation, measurement, and disclosure of data value [4] - In the first quarter of 2025, 91 A-share listed companies included data assets in their financial reports, with a total scale of 4.402 billion, marking a significant increase in both the number of participating companies and the scale of inclusion compared to the previous year [4] Group 5 - Data asset inclusion in financial statements enhances resource allocation efficiency and facilitates precise capital market resource allocation, allowing for better monetization of data assets [5] - The successful listing of data assets, such as the smart parking data asset from Zhenjiang Transportation Industry Group, demonstrates the potential for data assets to be valued and traded in the market [5] Group 6 - The process of data capitalization has accelerated significantly under the drive of financial innovation, with examples such as the issuance of asset-backed securities based on operational and public service data [6] - The approval of the first data center REITs in the country further enriches the practice paths for data capitalization, injecting new momentum into industry development [6] Group 7 - The Chairman of the China Securities Regulatory Commission indicated ongoing support for technology companies to utilize intellectual property and data assets for asset securitization and REITs, signaling future policy support and financial innovation to promote the development of the data factor market [7] - Standardization of entity economic data is essential for transforming it into data required by capital markets, which is a primary task of financial technology [7]

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]