NSF establishes new institutes for harnessing the data revolution
Credit: Nicolle Rager Fuller, National Science Foundation
The U.S. National Science Foundation announced a $75 million investment to establish five new Harnessing the Data Revolution Institutes. The institutes support convergence between science and engineering research communities, bringing together expertise in data science foundations, systems, applications and cyberinfrastructure. Together, they will enable breakthroughs through collaborative, co-designed programs to formulate innovative data-intensive approaches for addressing critical national challenges.
“These new institutes will lead innovation in data science. They will harness diverse data sources and develop new methodologies, technologies and infrastructure for data management and analysis,” said Manish Parashar, office director for NSF's Office of Advanced Cyberinfrastructure. “They position our nation at the cutting edge of global science and engineering by bringing together diverse perspectives to support convergent research."
A summary of each award is provided below.
- NSF Institute for a New Frontier of Biological Information Powered by Knowledge-Guided Machine Learning — Led by The Ohio State University, the institute will establish a new field of Imageomics, in which biologists utilize machine learning algorithms to analyze vast stores of existing image data, such as publicly funded digital collections from national centers, field stations, museums and individual laboratories. The institute will characterize patterns and gain insights into how function follows form in all areas of biology and will expand public understanding of the rules of life on Earth and how life evolves.
- NSF Institute for Accelerated AI Algorithms for Data-Driven Discovery — Led by the University of Washington, the institute aims to construct the knowledge essential for real-time applications of artificial intelligence in three fields of science: high energy physics, multi-messenger astrophysics and systems neuroscience. The institute aims to develop customized AI solutions to process large datasets in real time, significantly enhancing the potential for discovery.
- NSF Institute for Harnessing Data and Model Revolution in the Polar Regions — Led by the University of Maryland, Baltimore County, the institute will serve as a research hub where experts in data science, Arctic and Antarctic science and cyberinfrastructure — from academia, government and private sectors — come together to address national priorities and challenges related to climate change, sea level rise and the rapidly changing Arctic.
- NSF Institute for Data Driven Dynamical Design — Led by the Colorado School of Mines, the institute aims to address the challenge of predicting dynamical processes in materials, including ion and molecular transport, catalytic pathways, and phase transformations in metamaterials, with a focus on discovering fundamentally new mechanisms and pathways. The institute's data science innovations may advance fields both within and beyond STEM involving complex time-evolving systems including molecular biology, atmospheric science, geophysics and physical cosmology.
- NSF Institute for Geospatial Understanding through an Integrative Discovery Environment, I-GUIDE — Led by University of Illinois Urbana-Champaign, the institute will create an integrative geospatial discovery environment that harnesses geospatial data to understand interconnected interactions across diverse socioeconomic-environmental systems — with a goal of enhancing community resilience and environmental sustainability. The institute will generate a new set of analytic tools that carefully address data interdependencies to help better estimate and predict risk and anticipate impacts from disasters or climate change.
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