The CyberGIS Center is well poised to revolutionize many areas of scholarship, ranging from engineering and science to the humanities, and focuses on the following four interrelated themes while engaging a number of related fields across campus and beyond:

  • Advanced cyberinfrastructure
  • Computer science
  • Computational and data science
  • Geography and geographic information science
  • Library and information science
  • Mathematics
  • Statistics
  • Agriculture
  • Applied health sciences
  • Atmospheric sciences
  • Business
  • Civil and environmental engineering
  • Geography and geographic information science
  • Geology
  • History
  • Political science
  • Sociology
  • Urban and regional planning
  • Veterinary medicine
  • Business
  • Communication
  • Geography and geographic information science
  • Industrial and enterprise systems engineering
  • Psychology
  • Advanced cyberinfrastructure
  • Agriculture
  • Applied health sciences
  • Atmospheric sciences
  • Business
  • Civil and environmental engineering
  • Communication
  • Computational and data science
  • Computer science
  • Discovery and innovation
  • Geography and geographic information science
  • Geology
  • History
  • Industrial and enterprise systems engineering
  • Library and information science
  • Mathematics
  • Political science
  • Psychology
  • Sociology
  • Statistics
  • Urban and regional planning and veterinary medicine

CyberGIS Center Projects

Ongoing research projects at the center cut across multiple research fields and focal themes and range from investigating computationally intensive spatial optimization, analysis and modeling for solving large-scale and/or multi-scale spatial problems in multiple application domains such as agriculture, energy, political sciences, public health and sustainability science; developing national and global cyberinfrastructure capabilities (e.g., the Open Science Grid and NSF XSEDE) and middleware (e.g. GISolve) capable of using these capabilities; parallel computing of geospatial visual analytics; to CyberGIS and computational science approaches to understanding complex geospatial dynamics.

The aim of this research is to develop new applications of statistical- and machine-learning algorithms to improve our characterization and prediction capabilities of shallow hydrogeologic properties and processes.

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The Cline Center for Democracy at the University of Illinois at Urbana-Champaign is committed to furthering scientific research concerning the operation of democratic processes and the relationship between democracy and societal welfare.

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This project exploits the massive computational power provided by the Blue Waters supercomputer for computationally intensive zoning optimization research.

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This project aims to study the problem of postharvest losses and identify prevention strategies and address the same by developing a platform and modeling framework for using Concurrent Science, Engineering, and Technology (ConSEnT) tools.

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Snow control operations involve intensive spatial information and geographic information systems (GIS) have been used to provide a suitable platform for creating, maintaining, and analyzing relevant data.

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The goal of this project is to establish fundamental and scalable capabilities for spatial data synthesis through integration with cyberGIS and novel cloud computing strategies to enable cutting-edge data-intensive research and education across multiple scientific communities.

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The CyberGIS Center has received a Major Research Instrumentation (MRI) grant from the National Science Foundation to build a high-performance computing system optimized to deal with geospatial data.

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Biomass Implementation Optimization Modeling Analysis Simulation Software (BIOMASS) has been developed to conduct systems informatics and analysis for biomass provision scenario management.

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The CyberGIS Center and the CyberInfrastructure and Geospatial Information (CIGI) Laboratory are part of the Open Science Grid (OSG), a national cyberinfrastructure that brings together distributed computing and storage resources from many campuses and diverse research communities. The CyberGIS Center and CIGI contribute technical and management expertise to OSG.

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A novel theoretical approach to computational intensity will enhance spatial analysis methods integrated with cyberinfrastructure and GIS. The CyberGIS framework will be established by developing innovative algorithms and software components based on this approach.

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Using XSEDE resources, we have enhanced a set of GIS and SAM algorithms from research software to software libraries and applications for cutting-edge scientific problem solving; released a new version of CyberGIS Gateway; and produced 18 peer-reviewed papers.

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Specific project objectives include:

  • Engage multidisciplinary communities through a participatory approach to evolving CyberGIS software requirements;
  • Integrate and sustain a core set of composable, interoperable, manageable, and reusable CyberGIS software elements based on community-driven and open source strategies;
  • Empower high-performance and scalable CyberGIS by exploiting spatial characteristics of data and analytical operations for achieving unprecedented capabilities for geospatial scientific discoveries;
  • Enhance an online geospatial problem solving environment to allow for the contribution, sharing and learning of CyberGIS software by numerous users, which will foster the development of crosscutting education, outreach and training programs with significant broad impacts;
  • Deploy and test CyberGIS software by linking with national and international CI to achieve scalability to significant sizes of geospatial problems, amounts of CI resources, and number of users;
  • Evaluate and improve the CyberGIS framework through domain science applications and vibrant partnerships to gain better understanding of the complexity of coupled human-natural systems (e.g. for assessing impacts of climate change and rapid emergency response).

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This project creates a unified cyberinfrastructure framework by adapting and integrating heterogeneous modalities of computing and information infrastructure (e.g., cloud, high-performance computing, and high-throughput computing) for scalable spatiotemporal data analytics.

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