Truthful Auction Mechanism for Data Trading with Share-Averse Data Consumers

In the paper we focus on a promising research problem of data trading, under the scenario that data items can be reproduced easily and inexpensively. Apart from a Bayesian optimal mechanism based data trading approach, we also propose a prior-free data trading approach to organize the data trading process between selfish data owners and share-averse data consumers, with the goal of maximizing revenue of data owners and meanwhile determining the optimal number of data copies. Rigorous theoretical analysis and extensive experiment results are offered to verify the effectiveness of proposed methods in terms of sum of valuations, revenue, individual rationality and incentive compatibility.