熊伟, 资文杰, 曹竞之. 科学工作流支持的复杂地理计算流程处理[J]. 武汉大学学报 ( 信息科学版), 2020, 45(12): 1903-1909. DOI: 10.13203/j.whugis20200209
引用本文: 熊伟, 资文杰, 曹竞之. 科学工作流支持的复杂地理计算流程处理[J]. 武汉大学学报 ( 信息科学版), 2020, 45(12): 1903-1909. DOI: 10.13203/j.whugis20200209
XIONG Wei, ZI Wenjie, CAO Jingzhi. Complicated Geospatial Flow Processing with Scientific Workflow[J]. Geomatics and Information Science of Wuhan University, 2020, 45(12): 1903-1909. DOI: 10.13203/j.whugis20200209
Citation: XIONG Wei, ZI Wenjie, CAO Jingzhi. Complicated Geospatial Flow Processing with Scientific Workflow[J]. Geomatics and Information Science of Wuhan University, 2020, 45(12): 1903-1909. DOI: 10.13203/j.whugis20200209

科学工作流支持的复杂地理计算流程处理

Complicated Geospatial Flow Processing with Scientific Workflow

  • 摘要: 将地理计算任务以及地理时空数据资源按照特定的业务逻辑组合起来,可以满足用户针对特定领域复杂地理问题的处理需求。传统地理计算流程构建后如果有复杂的迭代情况,仍然需要人工参与。科学工作流支持自动化流程管理方法来辅助地理学家进行地理计算和发现。提出了科学工作流支持的复杂地理计算流程处理方法,能够对复杂应用程序及各程序间的数据依赖关系进行组合,并控制各部分在时间、空间以及资源等约束条件下按序完成,实现地理时空数据进行查找、移动、分析、处理及可视化等操作。

     

    Abstract: By combining geo-computing tasks and spatial-temporal data resources with specific business logic, users can deal with complex geographic problems in specific domains. Traditional geo-computing processes require manual participation if complex iterations are built. Scientific workflows support automated process to assist researchers in geo-computing and knowledge discovery. A method for complicated geospatial flow processing based on scientific workflow is proposed. Firstly, exist open source scientific workflow management systems are compared. Subsequently, the core problems of geo-computing processes are analyzed: Heterogeneous multi-source data access, the description of complex computing, the scalability of computing, and the interaction and sharing of data analysis processes. The complex geo-computing flow processing method supported by scientific workflow is put forward, which can combine the data dependencies between complicated applications. Based on Swift's excellent capabilities in process structure, dispatchable resource types, and fault tolerance levels, geospatial flow can control the sequence of different parts to be completed under the constraints of time, storage and resources. Therefore, spatial-temporal data can be searched, moved, analyzed, processed and visualized. Finally, a housing site selection case based on this method is presented to show the feasibility.

     

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