DSRep: Implementing decentralized reputation evaluation for data space based on a low-cost and high-throughput blockchain

Data spaces are emerging as a promising solution for secure and decentralized data sharing across organizations. However, in such open environments, it is difficult for participants to establish trust in the quality of data products and the behavior of users. To address this challenge, we propose DSRep , a dynamic and decentralized reputation evaluation model tailored for data spaces. Based on a survey of 31 real-world data exchange platforms, DSRep introduces role-specific evaluation metrics for data products, data providers, and data consumers. DSRep proposes a DAO-based governance mechanism allows dynamic configuration of metrics and weights through on-chain voting. To handle the high-frequency reputation logs efficiently, DSRep propose a blockchain processing mechanism with two-level transaction pools. In the experiments, DSRep can effectively evaluate the reputation of users and data products, while reducing storage consumption by 89.97% and improving throughput by 117.28%. • To the best of our knowledge, this paper is the first to address the problem of reputation management in data space. • Based on a survey of 21 data exchange platforms in China and 10 in other countries, this paper proposes a set of reputation evaluation metrics dedicated to data space, including metrics for data products, data providers, and data consumers. • A fair and dynamic reputation management mechanism based on DAO is proposed, which enhances reputation governance through collective decision-making, tamper-proof record-keeping, and incentive mechanisms. • For high-frequency log processing requirements, this paper proposes a low-cost and high-throughput blockchain transaction processing mechanism, which innovatively adopts two-level transaction pools. This mechanism can reduce storage consumption by 89.97% and improve throughput by 117.28%.