The central goal of the NSF project: CIF21 DIBBs: Scalable Capabilities for Spatial Data Synthesis (Award #1443080) was to develop a set of capabilities for spatial data synthesis through scalable data aggregation and integration based on cloud computing, cyberGIS, and other cutting-edge cyberinfrastructure tools. 

The intellectual merit of the project is centered on not only the innovation of the spatial data synthesis capabilities, but also the enabling power of such capabilities for significantly advancing data-intensive geospatial problem-solving within various research and education domains. Specifically, the novel CyberGISX platform prototyped by the project addresses many of the challenges associated with using cutting-edge cyberGIS and data science capabilities for non-expert audience, including software installations, dependencies management and scaling to heterogeneous computing and cloud platforms. The CyberGISX platform has not only made it easy to share the knowledge about using the spatial data synthesis capabilities developed by the project, but also aids with the reproducibility and replicability of research activities thereby promoting open science practice. The project also has contributed to making extensive scientific advances, including for example studies of (a) population dynamics and urban sustainability by synthesizing social media and spatial data; (b) emergency evaluation using data-intensive agent-based modeling; and (c) assessment of spatial accessibility of healthcare resources such as ICU units and ventilators responding to the COVID-19 pandemic. The broad and significant research efforts made by the project have positively impacted the following interdisciplinary fields: 1) advanced cyberinfrastructure and geographic information science; 2) urban and social sciences; 3) emergency management; and 4) human-environment and geographic sciences.

The work done under this award has made tremendous broader impacts. The CyberGISX platform and spatial data synthesis capabilities created by the project have been made available to the general public, and broad science and engineering communities. Capabilities and tools on CyberGISX have been incorporated into a number of undergraduate and graduate courses which have helped to enhance and empower interdisciplinary and transdisciplinary education. The project provides scalable and easy to access spatial data synthesis capabilities for tackling computation and data challenges associated with using geospatial big data for research, which has benefited a number of disciplines. Examples of such impacts include (a) social science communities, through data-intensive social media research; (b) Earth and environment science communities, through the development of LiDAR processing capabilities leveraging a collaboration with the U.S. Geological Survey; (c) health geography community through timely research on spatial accessibility of healthcare resources during the COVID-19 pandemic; and (d) emergency management communities through agent-based evacuation modeling responding to disasters and groundbreaking research on flood mapping. The crosscutting nature of the project bridging advanced cyberinfrastructure and many domain science communities has proven to be greatly and mutually beneficial to the associated research and education communities.

This project has placed a major emphasis on education and workforce development, which is important to the future development of both advanced cyberinfrastructure and data-intensive geospatial sciences and technologies. The project was instrumental in holding two summer schools conducted in 2017 and 2019 each of which brought more than 30 participants together from across the country to learn cutting-edge cyberGIS and geospatial data science. The summer schools were conducted with active collaboration with the AAG (American Association of Geographers) and UCGIS (University Consortium of Geographic Information Sciences) which helped engage diverse participants. A number of hands-on workshops and training courses were offered on multiple campuses and at various conferences and meetings with diverse and underrepresented participants engaged. Many course modules and computational notebooks were developed to teach both graduate and undergraduate students cyberGIS-enabled spatial data synthesis capabilities that have been pioneered by the project. An online MOOC course on Foundations of CyberGIS and Geospatial Data Science has been developed and offered on Coursera. Overall, the project has created novel spatial data synthesis capabilities and associated tools that drastically lower the barriers to harnessing geospatial big data and advanced cyberinfrastructure in many geospatial-related communities for conducting open and reproducible research and education.

Last Modified: 12/14/2020
Modified by: Shaowen Wang