Core Viewpoint - The rise of the digital economy has positioned data as the "oil of the 21st century," with unique characteristics that complicate its management, circulation, and value distribution. The innovative model of "data trust" is emerging as a solution to data governance challenges and is increasingly recognized as a key to unlocking data value [1][15]. Group 1: Data Trust Service Entities - Data trusts can be categorized into three types: enterprise data trusts, public data trusts, and personal data trusts, reflecting the diverse needs of data subjects [2][16]. - Enterprise data trusts are the most common type, aiming to establish a trustworthy governance service or data circulation framework between data owners and users, ensuring value creation during governance and capitalization processes [2][16]. Group 2: Enterprise Data Trusts - In enterprise scenarios, data asset trusts are utilized for managing and operating data assets, facilitating cross-industry data sharing. The trust framework allows for data cleaning, anonymization, and structuring to meet market demands, generating trust income through service fees [3][17]. - An example includes the data trust business conducted by AVIC Trust in Guangxi, which integrates and analyzes electricity-related data to create marketable data products, helping clients understand electricity usage characteristics [3][18]. Group 3: Public Data Trusts - Public data, characterized by its broad sources and high authenticity, holds significant market value, with McKinsey estimating its potential value in China to be between 10 trillion and 15 trillion yuan [4][19]. - Current public data is primarily controlled by state-owned entities, facing challenges such as slow openness and lack of productization. Data trusts can facilitate smoother productization and circulation of public data, ensuring compliance and privacy protection [5][20]. Group 4: Personal Data Trusts - Personal data trusts involve individuals entrusting their data to a trustee, who supervises third-party access and usage, with profits distributed back to the individuals. This model allows individuals to maintain control over their data and its usage [6][21]. - The first personal data trust case in China has emerged in Guiyang, where individuals can manage their resume data through a data trust, indicating the early stages of personal data trust exploration [8][22]. Group 5: Diverse Implementation Scenarios - The national emphasis on market-oriented data element allocation has led to various practical explorations of data trusts, categorized into asset operation, platform service, and account governance models [9][23]. - The asset operation model focuses on monetizing enterprise data, exemplified by Yunnan Trust's first operational data trust product, which allows for the distribution of income from data rights [9][23][24]. - The platform service model aims to create a trusted data-sharing space, as seen in the "Tianchou No. 1" data trust, which facilitates secure data interactions among multiple stakeholders [10][25]. - The account governance model enhances risk isolation by managing data and funds separately, exemplified by the collaboration between Guiyang Big Data Exchange and other entities to establish independent data and financial accounts [11][26]. Group 6: Local Practice - Shanxi's Data Asset Service Trust - The first network freight data asset service trust in China has been established in Shanxi, leveraging the core data from the Chengfeng freight platform to create high-quality data assets [12][27]. - The project involves systematic data organization and compliance checks, leading to the establishment of a trust plan that enables data value realization through asset valuation and product trading [13][27][28]. Conclusion - Data trusts represent an innovative approach to data governance, providing pathways for secure circulation and equitable value distribution. They require collaborative evolution across legal, technical, market, and social dimensions, with the potential to significantly impact the digital economy [14][29].