A CONTROL-DRIVEN DATA ASSET CLASSIFICATION METHOD FROM A RIGHTS PERSPECTIVE
Keywords:
Data assetization, Data classification, Tripartite rights separation, Differentiated governanceAbstract
Against the backdrop of the digital economy, the process of data assetization is accelerating. However, in operational links such as registration, utilization, and transaction, institutional data rights have failed to be translated into enforceable implementation mechanisms, leading to ambiguous rights, responsibilities, and inefficient circulation. From a rights management perspective, this paper proposes a tripartite classification framework for data assets: identification data resolves issues of attribution, raw material data regulates usage based on clarified ownership, and tool data further enables the distribution of benefits. This framework integrates the national policy of "Tripartite Rights Separation", analyzes the distinct rights characteristics of different data types, and designs differentiated governance pathways. It aims to provide institutional support for data assetization operations and foster the efficient functioning of the data factor market.References
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