A simulated spatial distribution of disease risks, overlaid onto a Google base map of North America.

CyberGIS: infrastructure for massive geospatial data, processes

CyberGIS is geospatial-specific infrastructure that manages, processes and visualizes massive, complex geospatial data while performing associated analysis and simulation.

A consortium of government, academic and private-sector partners has come together to build the National CyberGIS Facility at the University of Illinois, Urbana-Champaign. With funding from the National Science Foundation, the group aims to build a high-performance computing system optimized to handle geospatial data. The platform will be equipped with more than 7 petabytes of raw disk storage, solid-state drives, advanced graphics processing units, a high-speed network and dynamically provisioned cloud computing resources.

"There are critical problems that cyberGIS can assist in, from mapping water resources across local, regional and global scales to managing the preparation and response to disasters and emergencies," said Shaowen Wang, the founding director of the CyberGIS Center. "But to date, no one has created the cyber infrastructure that is really needed to solve such problems."

And that’s what Wang is building at the University of Illinios. NSF has awarded a Data Infrastructure Building Blocks (DIBBS) grant of $1.5 million over three years to a team led by Wang to create scalable capabilities for synthesizing spatial big data.

DIBBS is part of NSF's effort to improve the nation's capacity in data science by investing in the development of infrastructure, building multi-institutional partnerships to increase the number of U.S. data scientists and improving the usefulness and ease of use of data infrastructure.

Many scientific problems cannot be solved without the aggregation of large and varied spatial data from a multitude of sources. At the same time, existing approaches and software cannot effectively synthesize the enormous amount of complex spatial data that often are available. The NSF project will address challenges in working with spatial big data and will create a suite of tools for spatial data synthesis based on cloud computing and cyberGIS .

The team will address two interrelated scientific case-studies: They will measure urban sustainability based on a number of social, environmental and physical factors and processes. The team will also study population dynamics by combining multiple population data sources with social media data.

In tackling these issues, the project will use a number of tools, including:

CyberGIS Gateway, an online cyberGIS environment where large numbers of users can perform data-intensive collaborative geospatial problem solving.

CyberGIS Toolkit, a suite of loosely coupled open-source geospatial software components that provide scalable spatial analysis and modeling capabilities.

GISolve middleware that provides user-friendly and spatially intelligent capabilities for performing computing- and data-intensive geospatial data analysis and problem solving.

The Nimbus Phantom cloud platform that provides infrastructure-as-a-service to the scientific community and has tools to help researchers take advantage of cloud computing.

"This project represents an exciting and important effort focused on establishing the foundation and principles of spatial data science through innovating scalable capabilities of cloud computing and cyberGIS to systematically transform spatial big data into cutting edge scientific knowledge," Wang said.

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