Using Big Data for Environmental Sustainability: Big Data + AI Technology = Accessible, Usable, Useful Knowledge
Description:
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.
(Seed Grant) Large: HBCU Data Science Consortium (HBCU-DSC)
Description:
In alignment with the South Big Data Innovation Hub program’s goals of promoting collaboration and supporting the cross-pollination of tools, data, and ideas across disciplines and sectors, an HBCU Data Science Consortium (HBCU-DSC) is being proposed. 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.
Large: HBCU Data Science Consortium (HBCU-DSC)—Six University Leads
Description:
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. Project Goals: 1. To build a network of HBCU researchers focused on development of resources, collaborations and initiatives centered around data science 2. To increase possibility of securing funding and research awards in data science by HBCU Consortium members
Keeping Data Science Broad
Description:
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.