Spoke Projects

South Region Spokes Awards

The Southern U.S. have been awarded funding for projects designed to use data science and data analytics to address challenges related to healthcare, environmental sustainability, and updating and improving power grids. The funding will be awarded through the “Big Data Spokes” program of the National Science Foundation’s (NSF) Big Data Regional Innovation Hub initiative.

Each Big Data Spoke will work on a challenge that requires big data approaches and solutions. Like the Big Data Hubs, the Spokes will take on a convening and coordinating role as opposed to directly conducting research. Each will gather important stakeholders; engage end users and solution providers; and form multidisciplinary teams to tackle questions no single field can solve alone. However, unlike the Hubs, which aim to span the full range of data-driven challenges and solutions in a geographic region, each Spoke will have a specific, goal-driven mission.

“The Big Data Spokes advance the goals and regional priorities of each Big Data Hub, fusing the strengths of a range of institutions and investigators and applying them to problems that affect the communities and populations within their regions,” said Jim Kurose, assistant director of NSF for Computer and Information Science and Engineering. “We (NSF) are pleased to be making this substantial investment today to accelerate the nation’s big data R&D innovation ecosystem.”

Using Big Data for Environmental Sustainability:
Big Data + AI Technology = Accessible, Usable, Useful Knowledge


Principal Investigator: Ashok K. Goel, professor of computer science and cognitive science, Georgia Institute of Technology
Co-PI: Jennifer Hammock, Smithsonian Institute, in partnership with IBM Watson
Amount: $1 million over three years

Website: http://vera.cc.gatech.edu/ and Learn More About VERA

As the effects of environmental degradation and climate change grow, the need for research and education in biological diversity, ecological modeling and environmental sustainability becomes critical. This project brings together scientists from a dozen institutions in academia, government, and industry to translate big data into meaningful knowledge that supports research and education in environmental sustainability. The project will focus on the Encyclopedia of Life (EOL), the world’s largest database of biological species, and other biodiversity data sources. Its goals are to make this data more accessible and usable by integrating artificial intelligence tools, modeling, and simulation.
View a recent paper on the VERA project: Vera: Popularizing Science Through AI
Download a one-pager about VERA
View a 90-second video on VERA

VERA for Modeling the Spread of Covid-19 (White Paper)

  • The website contains a brief User’s Guide as well as a detailed

Smart Grids Big Data



Principal Investigator: Mladen Kezunovic, Eugene E. Webb Distinguished Professor of Electrical and Computer Engineering, Texas A & M University
Co-PIs: Santiago C. Grijalva, Georgia Institute of Technology; Zoran Obradovic, Temple University
Amount: $1 million over three years

The introduction of new technologies for monitoring electrical power grids has led to an abundance of data that can be used to improve power generation and transmission and to enhance customer service. However, this data is still vastly underutilized. This project aims to increase our understanding of the merged data collected from physical systems in order to better understand how energy flows through grids, how to prevent emergencies such as blackouts and brownouts, and how to improve asset management and increase energy efficiency. More Information

Large Scale Medical Informatics for Patient Care Coordination and Engagement


Principal Investigator: Gari Clifford, interim chair, biomedical informatics, Emory University
Co-PIs: Christopher Rozell, Georgia Tech; Herman Taylor, Morehouse School of Medicine; Indranil Bardhan, University of Texas at Dallas; Donald Adjeroh, West Virginia University; Ahmed Abbasi, University of Virginia; Nitin Agarwal, University of Arkansas
Amount: $1 million over three years

This project brings together six universities to design and construct a patient-focused and personalized health system that addresses the fractured nature of healthcare information and the lack of engagement of individuals in their own healthcare. By taking advantage of the enormous amount of information generated by real-time, mobile and wearable devices and the availability of rich social media data on patient behavior, the team will create a comprehensive picture of patient health and a tool to help manage patients’ engagement with their healthcare providers. As its first pilot, the researchers will focus on African Americans and Hispanics/Latinos diagnosed with cardiovascular disease. More Information

2018 SPOKE Project Awards

Smart Privacy for Smart Cities: A Research Collaborative to Protect Privacy and Use Data Responsibly

Principal Investigator: Jules Polonetsky, Future of Privacy Forum

Today’s cities and communities, and their residents, are increasingly connected, and decisions are informed by actionable, real-time data. Data is making modern cities and local communities faster and safer, as well as more sustainable, livable, and equitable. At the same time, smart city technologies raise concerns about individuals’ privacy, autonomy, choice, and possible misuse. Government officials are raising important questions about who should own data, how privacy protections for public-facing technologies work, who and how to communicate with the public about privacy, and more. The long-term vision of the project is to help municipal leaders strengthen their ability to collect, use, and share data in a responsible manner. This will help grow privacy-preserving innovations across applications and geographic boundaries for the public good. In this way, the Smart Privacy for Smart Cities Spoke will serve to increase public knowledge, understanding and engagement with privacy-related concerns, and ultimately promote the public’s trust in smart city technologies and in their local government.

Enhanced 3-D Mapping for Habitat, Biodiversity, and Flood Hazard Assessments of Coastal and Wetland Areas of the Southern US

Principal Investigator: Frank Muller-Karger, University of South Florida

Co-Principal Investigator:  James Gibeaut, Texas A&M – Corpus Cristi

The risk to coastal populations and infrastructure from flooding due to sea level rise, severe storms, and river discharge will increase for U.S. southern states. The vision of this project is that communities occupying low-lying coastal areas of the southern US will be protected and develop in a sustainable manner through planning based on knowledge, conservation, and wise use of sensitive lands. Researchers from the University of South Florida’s College of Marine Science and the School of Geosciences, Texas A&M University – Corpus Christi, and Google Earth Engine are collaborating with the South Big Data Hub through this project to develop more accurate, ultra-high resolution topographic, land cover, and urban environment geospatial products. The project examines in detail areas that were directly impacted by Hurricanes Harvey and Irma in 2017, and identifies flood-prone areas across the region. The 3D maps show habitat diversity, needed to plan for conservation and development in these important ecosystems.

Integrating Biological Big Data Research into Student Training and Education

Principal Investigator: Hong Qin, University of Tennessee Chattanooga

Co-Principal Investigators: Donald Adjeroh, West Virginia University Research Corporation;  Mentewab Ayalew, Spelman College;  Fan Wu, Tuskegee University

The project is a collaborative effort among the University of Tennessee Chattanooga, Tuskegee University, Spelman College, and West Virginia University to integrate and automate biological big data into student training and education. Leveraging the team’s expertise in computer science and ecology, the project will offer training workshops on using network models to integrate heterogeneous genomic big data and heterogeneous ecological big data to address life sciences questions. The team will engage faculty and students in developing a protocol to automate field data collection. The team also will prototype automated methods to enhance plant digitization, leveraging the collection of digitized plant images and meta-information at the Southeast Regional Network of Expertise and Collections, as well as the ecological datasets in collaboration with the Encyclopedia of Life.