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Geospatial cyberinfrastructure is a research area that focuses on geospatial data and the need to provide more effective organization, integration, computation, and visualization for widely distributed geospatial resources scattered across cyberspace. This CAREER award will support a promising early-career investigator's efforts to build key theories and techniques of a cyber-knowledge infrastructure that enhances access, search, and reasoning capabilities for using geospatial data across the ever-expanding Web. Current data search tools are built primarily using standard techniques derived from computer science and ignore the inherent properties of geospatial data, such as location. The investigator will employ an innovative suite of algorithms to answer complex spatiotemporal questions using the best available geospatial data. The research activities to be conducted will transform traditional cyberinfrastructure from a data infrastructure to a knowledge infrastructure with core intelligent data access, search, and reasoning elements. The project will address a critical need for data-access sustainability and will increase research capabilities across a broad range of scientific and computer information domains. Project results and methods will help develop more intelligent cyberinfrastructure to support data and knowledge discovery in a variety of data-intensive applications. The investigator will integrate her research with community-driven geospatial cyberinfrastructure education and outreach activities, and she will make algorithms and other materials developed during the course of this project available via open source media.

The research program to be pursued by this investigator will build a cyber-knowledge infrastructure that will effectively resolve fundamental issues residing in geospatial data access, discovery, and knowledge synthesis. The project will integrate three innovative approaches to support intelligent knowledge discovery: (1) a large-scale web-mining technique; (2) a hybrid semantic search technique that combines a top-down ontological approaches and a bottom-up data-mining approach; and (3) an intelligent spatiotemporal reasoning system that enables high resolution queries. The successful completion of the project will yield a variety of geospatial data, analytic tools, and workflows that can be readily accessible and reused in order to answer spatiotemporal questions in a timely manner as well as to reproduce and validate scientific results in real time. The project will help foster coupled spatial- and computational-thinking skills for future researchers in cyberinfrastructure and data science through scientific community-driven curriculum development.



National Science Foundation, Division of Behavioral and Cognitive Sciences


May 2015 — April 2020