The circulation of data elements serves as a key driver of data value and the digital economy, yet current mechanisms face challenges in ensuring data quality and trust due to information asymmetry, fraud, and illicit industrial chains, hindering their wide circulation and application. An evolutionary game model for a blockchain-based trusted data space was established to construct a high-quality, transparent, and trusted circulation paradigm. Taking data providers, trusted space operators, and data users as participants, complex network game theory was applied to analyze the evolutionary stability of multi-agent behaviors and their key influencing mechanisms. Analysis and experiments using multi-source real data show that the blockchain-driven model suppresses low-quality data supply, ensures fairness and trust, and reduces transaction risks and matching costs for users, thereby enhancing their trading willingness. For operators, blockchain adoption depends on the balance between implementation costs and benefits in suppressing low-quality data and maintaining system stability. The proposed model provides a novel game-theoretic framework for trusted data space construction and offers theoretical and practical insights into fostering the healthy development of the data element market
