The South Big Data Innovation Hub supports large and small scale projects, from $1,000 - $1 million, aimed to increase the efficiency and effectiveness of knowledge and technology transfer between individuals, universities, public and private research centers and laboratories, large enterprises, and small and medium-sized businesses.

Each Data Innovation Project will work on a challenge that requires data science ideas, approaches, and solutions. By taking on a convening and synergizing role, as opposed to directly conducting new research, the six Data Innovation Projects, called “Spokes,” will each gather important stakeholders, engage end users and solution providers, and form multidisciplinary teams to tackle large 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.

Seed grant projects are designed to give money to PI’s to establish communities of practise, working groups, or provide a connection point between two or more communities, sectors, or solution providers to grow and scale opportunities for the Southern region. .



  • $6M+ in funding for large-scale Spoke Projects that impact the Southern region
  • $250k per year available for Seed Grant funding


The South Hub supported Data Innovation Projects - Spokes and Seed Grants - are listed below

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.
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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. This project has repurposed VERA to model the effect of social distancing on the spread of COVID-19, including the SIR model of epidemiology. VERA enables a user to build conceptual models and agent-based simulations, and conduct "what if" virtual experiments. We believe that this interactivity should be a significant boon for learning and education.
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