Core Viewpoint - The article emphasizes the critical role of data as a key production factor in driving high-quality economic development, highlighting the need for effective data governance and market integration to unlock its value [6][7][10]. Group 1: Importance of Data - Data is becoming a key driving force for high-quality economic development, transitioning from traditional production factors to a focus on data in the digital economy [7]. - The integration of data into various economic sectors is reshaping production methods, social structures, and governance models, making it essential for innovation and value creation [7][9]. Group 2: Institutional Framework - Establishing a robust institutional framework is crucial for releasing the value of data, addressing issues like unclear ownership and lack of circulation rules [10]. - The "data twenty articles" initiative aims to clarify data ownership and usage rights, promoting a structured approach to data rights that encourages participation in data production and application [11]. Group 3: Market Integration - The creation of a unified national data market is essential to overcome barriers such as "data silos" and enhance the efficiency of data resource allocation [12]. - A well-integrated data market can stimulate market vitality and innovation, contributing to the growth of the digital economy and enhancing national competitiveness [12]. Group 4: Application-Driven Value Release - Data is rapidly integrating into various sectors, including production, distribution, consumption, and social services, driving significant changes in operational efficiency and service delivery [13][14]. - In manufacturing, data enhances design efficiency and enables real-time monitoring, while in services, it improves customer experience and operational transparency [13][14][15]. Group 5: Security Governance - Ensuring data security is fundamental for facilitating data circulation and realizing its value, as a lack of security can hinder data openness [16]. - A comprehensive security framework can transform potential risks into manageable ones, fostering trust in data usage and enabling broader application in high-value scenarios [16].

Group 1 - The core argument of the article emphasizes the importance of data as a new production factor in the digital economy, highlighting its explosive growth and the need for a structured market for data elements [1][2][3] - The article outlines the gradual policy developments in China regarding data as a production factor, including the establishment of a data property rights system and the promotion of data marketization [1][2][3] - The concept of "structural separation of data property rights" is introduced, which involves the division of data rights into holding rights, usage rights, and operational rights, aiming to enhance data governance and market efficiency [3][4][5] Group 2 - The article discusses the multi-layered process of transforming data from a resource to a productive factor, emphasizing the need for clear property rights to facilitate efficient economic activities [2][3][4] - It highlights the unique characteristics of data, such as non-competitiveness and low replication costs, which complicate traditional property rights frameworks [2][3][4] - The structural separation of data property rights is proposed as a solution to address issues like data monopolization and privacy protection, while also promoting cross-industry collaboration [3][4][5] Group 3 - The article identifies the challenges in the current data market, including unclear rights definitions and inefficient circulation mechanisms, which hinder the realization of data value [11][12][13] - It presents various models and frameworks for understanding the data value chain, emphasizing the importance of market transactions in transforming data into capital [11][12][13] - The research aims to explore the impact of structural separation of data property rights on the value realization of data elements, filling gaps in existing literature [13][14][15] Group 4 - The article elaborates on the influence of structural separation on different stages of data value formation, particularly focusing on the resource and asset stages [14][15][16] - It discusses how structural separation can break down data silos, improve data quality, and enhance data security, thereby facilitating better data utilization [15][16][17] - The article also highlights the role of structural separation in promoting data asset valuation and market recognition, which is crucial for the development of a data-driven economy [17][18][19] Group 5 - The article emphasizes the significance of data products and their marketization, noting that clear pricing mechanisms and property rights are essential for effective data transactions [20][21][22] - It discusses how structural separation can reduce transaction friction and improve supply-demand matching efficiency in the data market [21][22][23] - The article advocates for innovative application scenarios for data, suggesting that structural separation can facilitate cross-industry collaboration and enhance the overall value of data [22][23][24] Group 6 - The article concludes that exploring the structural separation of data property rights can maximize the value of data elements and support the high-quality development of the digital economy [26][27][28] - It provides policy recommendations for implementing this structural separation, including promoting data sharing, establishing clear asset valuation standards, and encouraging innovative data trading models [28][29]

Core Viewpoint - The initial rights definition and minimization of transaction costs are prerequisites for establishing a unified national data factor market, which will drive the industrialization and fair pricing of data factors, ultimately benefiting the real economy [3][4]. Group 1: Basic Elements for Building a Unified Data Factor Market - The four basic elements for constructing a unified national data factor market are initial rights definition, transaction cost minimization, infrastructure development, and industrialization [4]. - Current obstacles to data factor market construction include unclear data property rights and high transaction costs, primarily due to the lagging property rights system behind technological advancements [4][5]. Group 2: Key Scientific Issues in Data Factor Market Construction - The initial rights definition of data resource development and utilization plays a foundational role in the construction of a unified data factor market, while transaction cost issues need urgent solutions [5]. - The construction of data circulation infrastructure introduces a technology trust mechanism, supporting data resource development, transaction pricing, and regulatory safety [5]. - The industrialization of data factors will act as an accelerator in promoting the construction of a unified national market [5]. Group 3: Data Property Rights Governance - The "Data Twenty Articles" propose a structural division of data property rights, which, while aligning with social equity from a legal perspective, presents significant logical conflicts from an economic standpoint [7]. - The classification and grading of data rights can increase transaction costs and complicate the sharing and trading of data resources, leading to data protectionism and monopolization [7][8]. - The initial rights to data resource development should ideally be assigned to the government, which can represent public interests and facilitate the efficient use of data resources [9]. Group 4: Transaction Cost Issues in Data Factor Market - Five key transaction costs affecting data factor flow include externality transaction costs, communication transaction costs, institutional transaction costs, intermediary service costs, and application delivery costs [11]. - High transaction costs hinder the incentive mechanisms for data resource circulation and utilization, necessitating government intervention to reduce these costs [12].