Core Viewpoint - The legal attributes of data assets present inherent contradictions, leading to ambiguous rights boundaries and market failures, necessitating a systematic governance framework for data asset valuation and management [1][2]. Group 1: Challenges in Data Asset Valuation - The complexity of data rights construction contributes to the difficulties in data asset valuation, as data assets differ fundamentally from traditional tangible and intangible assets [2][3]. - Data assets cannot be easily categorized within traditional property frameworks due to their composite nature, which includes multiple rights and interests [3][4]. - The dynamic value of data assets makes them difficult to assess, as their worth can fluctuate significantly based on time, technology, and policy changes [4][5]. Group 2: Regulatory and Institutional Barriers - Current regulations do not effectively alleviate the challenges in data asset valuation and may even create institutional barriers [7][8]. - The existing data regulatory framework lacks clear, actionable guidance on how to legally and efficiently convert data into assets and conduct reasonable valuations [7][8]. - There is a lack of standardized valuation systems for data assets, leading to significant discrepancies in valuation outcomes among different assessment institutions [8]. Group 3: Proposed Solutions for Data Asset Governance - A systematic, dynamic governance approach is needed to address the challenges of data asset valuation, focusing on rights confirmation and quality standards [9][10]. - Establishing a national unified data asset registration platform can enhance transparency and provide initial evidence of rights and compliance status [10]. - Implementing a dual-track innovation of compliance baseline audits and quality enhancement certifications can help mitigate information asymmetry in the data market [10][11].