ITR: Framework for Integrating Geospatial and Online Data to Respond to Unexpected Events

信息集成的大部分工作都集中在结构化数据源（如数据库或XML数据）的动态集成上。 对于更复杂的地理空间数据类型，如卫星图像，地图和矢量数据，研究人员专注于有限类型的集成，如将矢量数据与图像相结合。 由于现在有大量的地理空间数据和网上有大量的数据，因此有一个极好的机会来利用这两种信息源的整合。 我们计划通过开发一个整合在线和地理空间数据源的总体框架来应对这一挑战。 由此产生的框架将支持处理和连接各种源类型的一般操作，集成各种源类型数据的查询处理，以及管理准确性和效率之间权衡的优化技术。 整个项目将大大提高迅速整合和利用当今各种地理空间和在线资源的能力。 这项研究将作为南加州大学意外事件研究中心的一部分进行，并将大大提高我们国家应对意外事件的能力。

Much of the work on information integration has focused on the dynamic integration of structured data sources, such as databases or XML data. With more complex geospatial data types, such as satellite imagery, maps, and vector data, researchers have focused on limited types of integration, such as combining vector data with imagery. With the enormous amount of geospatial data now available and the huge amount of data available on the Web, there is a terrific opportunity to exploit the integration of these two types of information sources. We plan to address this challenge by developing a general framework for integrating online and geospatial data sources. The resulting framework will support general operations for processing and joining the various source types, query processing that integrates data over a wide range of source types, and optimization techniques that manage the tradeoffs between accuracy and efficiency. The overall project will provide a significant advance in the ability to rapidly integrate and exploit the wide variety of geospatial and online sources that are available today. This research will be conducted as part of University of Southern California's Center for Research on Unexpected Events and will greatly improve our nation's ability to respond to unexpected events.