Abstract

As the data sharing process spans multiple stakeholders, its complexity increases significantly, making it increasingly difficult to track and understand the source, circulation, and usage of data. This not only limits the comprehensive utilization of data but also affects the establishment and maintenance of trust, thereby hindering cooperation efficiency. To address this, this paper integrates two analytical tools—Process Mining and Social Network Analysis (SNA)—to deeply explore the data sharing process among multiple stakeholders. By combining these two methods, we can more finely depict the data flow trajectories between different stakeholders and gain a deeper understanding of the structural characteristics of the data sharing network, such as the frequency, direction, and intensity of data sharing. This in-depth analysis helps identify potential barriers and opportunities within the data sharing process, providing new insights for promoting data compliance, efficient circulation, and utilization

Share

COinS