CIF21 DIBBs: Scalable Capabilities for Spatial Data Synthesis

该项目将开发一套基于云计算、CyberGIS和其他现有工具的可伸缩数据聚合和集成的空间数据合成工具。许多科学问题需要聚集和集成来自多个来源的大量和不同的空间数据，然而现有的方法和软件不能有效地综合通常可用的海量空间数据。该项目将解决与使用大量空间数据有关的问题，从而促进依赖这类数据解决科学问题的工作，如人口动态和城市可持续性研究。从研究活动中获得的学习材料将通过数码地理信息系统科学门户开放获取。有针对性的大规模开放在线课程开发将提供廉价而有效的方式，向学生传授空间数据合成的能力和基本科学原理。在该项目的后半段，将提供暑期班，以提供更有针对性和深入的培训活动。该研究项目将为云计算和网络地理信息系统实现的空间数据合成创造可扩展的能力。该项目将从开发解决具体科学问题的能力开始，然后继续参与更广泛的社区，以验证和改进核心能力。这项研究将包括两个相互关联的主题：(1)基于一些社会、环境和物理因素和过程来衡量城市的可持续性；(2)通过综合多个人口数据源和社交媒体数据来检查人口动态。该项目将提供的空间数据综合能力包括提取元数据和处理空间参考和单位的问题。该项目还将开发表征数据及其传播中的不确定性的基本能力。

This project will develop a set of tools for spatial data synthesis through scalable data aggregation and integration based on cloud computing, CyberGIS, and other existing tools. Many scientific problems require the aggregation and integration of large and varied spatial data from a multitude of sources, yet existing approaches and software cannot effectively synthesize the enormous amounts of spatial data that often are available. This project will resolve problems associated with the use of massive spatial data, thus facilitating work dependent on this type of data for scientific problem solving, such as research on population dynamics and urban sustainability. Learning materials derived from the research activities will be openly accessible through the CyberGIS Science Gateway. Targeted massive open online course development will provide inexpensive and efficient ways to teaching students about the capabilities and underlying scientific principles of spatial data synthesis. A summer school will be offered during the second half of the project to provide a more focused and in-depth training event.This research project will create scalable capabilities for spatial data synthesis enabled by cloud computing and CyberGIS. The project will begin by developing the capabilities for solving specific scientific problems and then move on to engage a broader community for validating and improving the core capabilities. The research will incorporate two interrelated themes: (1) measuring urban sustainability based on a number of social, environmental, and physical factors and processes; and (2) examining population dynamics by synthesizing multiple population data sources with social media data. Spatial data synthesis capabilities that the project will provide include extracting metadata and dealing with problems of spatial references and units. The project also will develop a fundamental capability to characterize uncertainty in data and its propagation.