these works is similar to ours, they do not comment on how one can derive an optimal reward payoff to participating data providers after finding the *shapley value*, which our work does. Moreover, these works also fail to point out that a data sharing process contains subtleties which deviate from conventional cooperative games, which our paper examines in Section 4.\
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Furthermore, works such as [@5; @6] attempt to formulate the data sharing process as a non-cooperative game, where each participating player contributes data to create a unified predictive model. However, such non-cooperative game rewards each participating players with the same model at the end of the game, which violates our aim to endow players with a reward commensurate to his contribution. Moreover, non-cooperative games fails to account for the possibility of group cooperation between players, which not only is more realistic in real life, but also examines the idea of fair division of reward at the end of the game.\
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Some existing literature [@2; @7] also remarked that participating players could receive the same model and be renumerated with varying amount of money after data sharing. However, it is uncertain how to determine the “exchange rate” between data 