Research on Service-Oriented Sharing and Computing Framework of Geographic Data for Geographic Modeling and Simulation

Geographic data are the foundation of geographic model construction, and any stage of their acquisition, processing, and analysis may have an impact on the efficiency and quality of geographic modeling and simulation. With the advent of the era of big data, a large number of data resources are generated in the field of geographic information. However, due to the heterogeneity of geographic data and the security of data usage, massive geographic data resources are difficult to fully explore and utilize, resulting in the formation of data islands. This paper proposes a service-oriented geographic data-sharing and computing framework, which provides users with a complete set of geographic data access and application processes (such as data acquisition, processing, configuration, etc.), so as to reduce the difficulty of using data and improve the efficiency of data sharing. The framework mainly consists of three core components: (1) the “Data service container” can publish data resources as data services to provide a consistent data access interface; (2) the “Workspace” provides a series of methods and tools for users to develop data-computing solutions; and (3) the “Data-computing engine” is responsible for performing computing tasks such as data processing and configuration. Finally, a case of runoff simulation using the SWAT model is designed, in which the whole process of data sharing, acquisition, calculation, and application is realized, so as to verify the validity of the proposed framework.