| dc.description.abstract | Our research chooses a decentralized blockchain as the system architecture of the data sharing platform, using blockchain and smart contracts as management, assistance and supervision roles, to take advantage of their inherent advantages to trace all the data on the platform with its immutable characteristics to reduce the level of trust required between participating organizations. Our study uses causal rule mining which is more purposeful than association rule mining, to reveal the multi-faceted and multi-dimensional complex relationships among organizations. Through the data of National Central University, we simulated the data exchange among organizations in NCU, our study decided to distinguish large-scale, medium-scale and small-scale data sets by the number of column attributes. In addition, we also utilize the data from NBA and NCAA to simulate apply in different fields. As for privacy protection, our research will design a platform as a hub for managing data sharing, aggregation, and analysis, and the organizations involved in sharing will not directly participate in the data of other organizations to reduce the possibility of privacy leakage for individuals or organizations. It is hoped that such a study will promote and integrate the value of data utilization in various fields of society. Finally, the experiment showed that combining data from different organizations enriches the purposeful exploration data set; this will make the analysis results more meaningful and provide a more solid basis for decision support. | en_US |