## 2 Framework Design  
In the process of geographic data sharing, two types of roles are usually involved. For data providers, on the one hand, they hope to ensure the security of data (that is, they do not want users to tamper with, misuse, abuse data, etc. ), and on the other hand, they hope users can quickly produce more results based on their shared data to give full play to the value of data. For users, they want to be able to easily and quickly obtain data resources, and can quickly customize data to meet their personalized data requirements. To address these concerns, a service-oriented geographic data-sharing and computing framework is designed, as shown in Figure 1.  
Data service containers are used to publish data resources as data services. In this paper, data services include data resource services and data-processing services. The former means that data resources are directly provided to users in the form of a data service. For example, if the data provider shares the point data set of shared bicycles in a city, the data can be directly shared in the form of a data service without any processing. In general, the data source shared by the data provider can be in any form, such as data files, databases, APIs (Application Programming Interface), etc. However, if the user needs a hotspot map based on these point data, the data need to be analyzed before the data are shared, and the hotspot analysis method can be published as a data-processing service (hotspot analysis service). In general, data-processing methods can be provided in a variety of forms, such as Python script files, dynamic link libraries, Java packages, etc. In addition, in order to provide the consistent access interface of data services, this paper designs the standardized description method of geographic data and the standardized encapsulation method of data-processing methods. Based on this, standardized data services can be generated and published in a data service container. The workspace is used to provide solutions for the diverse data needs of requirements, as it can share and reuse the data configuration works of users. According to data requirements, users can connect the required data resource services and data-processing services  
Figure 1: Design of the proposed data-sharing and computing framework. from the data service container to the workspace, and then generate data-computing solutions by configuring data-processing logic online. In this way, a data-computing solution that meets the needs of users can be saved, which is convenient for users to modify and improve later. It can be found that in this process, users only need to pay attention to the data-processing logic itself, without paying attention to the source of data and the specific details of data processing, so as to improve the efficiency of users in using data. The data-computing engine generates and executes computing tasks according to the user's data-computing solution, and finally outputs the data required by the user. After the user has configured the data-computing solution in the workspace, the solution can be sent to the computing engine. According to the data resources and data-processing methods configured in the computing solution, the computing engine will first prepare the data-computing environment, which needs to consider the CPU (Central Processing Unit) architecture (such as x86 and ARM), memory size, software, and hardware environment of the computing server, and then synchronize the related data resources and processing methods to the specified computing server. Then, the computing task can be started for data computation. Obviously, in order to ensure the correct execution of the computing task, it is also necessary to develop a series of protection measures such as task computing-process monitoring, abnormal-situation handling, and computing-process optimization. In summary, the framework proposed in this paper not only solves the problem of data sharing and computing, but also brings many benefits to both data providers and data users.