AI-Enhanced Government Data Governance in the Era of Big Data: Exploring Sharing Mechanisms and Management Systems

摘要

This study delves into the literature on management and decision making driven by big data, identifying the sharing mechanisms of big data resources and the interconnection technology of information silos as one of the cutting-edge topics in contemporary big data research. By examining and analyzing the application of government data sharing and exchange domestically and internationally, this paper summarizes issues related to management philosophy and data barriers caused by legacy systems in government data resource sharing and exchange. Based on cloud platforms and in conjunction with the theory of Data as a Service (DaaS), a framework for managing the entire volume of government data resources is proposed. This framework ensures that no alterations are made to existing systems, achieving data non-movement, non-replication, and preservation of the original management model, while defining the rights and obligations of various operating entities regarding data. It addresses the management philosophy issues and systemic barriers encountered in data sharing and exchange.