Abstract: In the big data era, digital economy takes data as a basic production factor and becomes an innovative driving force for promoting the high-quality development of society and economy. Data trading plays a critical role in supporting the circulation of data resources, and creating data value. However, how to design a reliable and maintainable data trading system faces many technical challenges. Aiming at these challenges, this paper proposes an adaptive approach to modeling and verifying data trading systems. Through analyzing the requirements of data trading business, we propose a formal data trading adaptive software modeling method based on Petri nets, and establish a formal model of data trading business process and control strategy implementation technology based on Petri nets. The formal semantics of Petri nets can effectively support the property analysis of data trading systems. Finally, the simulation results verify the effectiveness and feasibility of the proposed method.