Projects | South Big Data Innovation Hub

PROJECTS OVERVIEW

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. .

PROJECTS IMPACT

$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

The HBCU Data Science Consortium

This project was an awardee of the 2020 South Big Data Hub SEEDS Program - Southern Engagement and Enrichment in Data Science. It was the single large award funded at $100K. The PIs seek to build a consortium that provides an accessible and beneficial platform within the HBCU community.

Evaluation and Demonstration of Open Data Portal Technology for Smart Cities and Data Science for Social Good

This project was an awardee of the 2020 South Big Data Hub SEEDS Program - Southern Engagement and Enrichment in Data Science. It is one of two awards funded in the Seed Grant's mid-range category of >$50,000. The proposed work will build on the Baltimore Data Science Corps NSF HDR project and will develop a number of use cases for serving open data for smart city and urban data applications..

Data4Kids: Virtually Teaching Kids about Data Science

This project was an awardee of the 2020 South Big Data Hub SEEDS Program - Southern Engagement and Enrichment in Data Science. It is one of two awards funded in the Seed Grant's mid-range category of >$50,000. The PIs seek to launch a website that contains guides, videos, and other content to assist educators and instructors on teaching data science to their students.

The Visualization and Data Reuse Challenge - Digital Rocks Portal

This project was an awardee of the 2020 South Big Data Hub SEEDS Program- Southern Engagement and Enrichment in Data Science. It is one of three awards funded in the Seed Grant's small-range category of <$10,000. The PIs seek to promote visualization and reuse of 3D images of porous materials that are stored in the open data repository Digital Rocks Portal (DRP).

The North Carolina Data Science Panel Series

This project was an awardee of the 2020 South Big Data Hub SEEDS Program- Southern Engagement and Enrichment in Data Science. It is one of three awards funded in the Seed Grant's small-range category of <$10,000. The PIs seek to showcase the different educational pathways that high school students can take to become a data scientist.

Reducing Uncertainty in Risk Projections for Statewide Hospital Capacity in COVID-19

This project was an awardee of the 2020 South Big Data Hub SEEDS Program - Southern Engagement and Enrichment in Data Science. It is one of three awards funded in the Seed Grant's small-range category of <$10,000. The PIs seek to study homeless data for the State of Delaware and model demand for beds in the statewide hospital capacity in response to COVID-19 data from Delaware.

Large: HBCU Data Science Consortium (HBCU-DSC)—Six University Leads

(Seed Grant) Large: HBCU Data Science Consortium (HBCU-DSC)

This Consortium seeks to provide an accessible and beneficial platform within the HBCU community that will promote collaboration and support the “cross-pollination” of data analysis tools, data, and ideas across the HBCU community, which is overwhelmingly located in the southern region.

The Open Storage Network

OSN provides value to multiple disciplines, ranging from moving large astronomy datasets to compute resources to datasets geared towards strengthening machine learning research. Our users constitute a varied community of researchers and practitioners. The project is nationally coordinated effort led by the South Big Data Hub and supported by the Northeast, West, and Midwest Big Data Hubs

Seed Grant Program

The South Big Data Innovation Hub Seed Grant program is designed to promote collaboration and support the cross-pollination of tools, data, and ideas across disciplines and sectors including academia, industry, government, and communities. Seed grant awards must support the southern region and the Major Goals and Priority Areas of the South Hub.

Large Scale Medical Informatics for Patient Care Coordination and Engagement

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. As its first pilot, the researchers will focus on African Americans and Hispanics/Latinos diagnosed with cardiovascular disease.

Integrating Biological Big Data Research into Student Training and Education

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. The project will offer training workshops, engage faculty and students in developing a protocol to automate field data collection, and will prototype automated methods to enhance plant digitization.

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

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 at Texas A&M University – Corpus Christi, along with 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.

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

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, to promote the public’s trust in smart city technologies and in their local government.

Keeping Data Science Broad

The goal of this series is to garner community input into pathways for keeping data science as a discipline broadly inclusive. We seek input from data science programs in any region across the nation, either traditional or alternative, and from a range of institution types including minority-serving institutions, community colleges, liberal arts colleges, tribal colleges, universities, and industry partners.

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

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.