ANNOUNCEMENT
NSF and NASA partner to address space weather research and forecasting
September 01, 2020
Space weather — solar wind, coronal mass ejections, magnetic storms, upper atmosphere disturbances — can damage infrastructure from electrical power supplies and computer networks to satellite and radio communications — and can even threaten astronauts' health. Accurate forecasting of energetic events on the sun and in the near-Earth space environment is critical for national security and the wellbeing of society. To address this need, the U.S. National Science Foundation and NASA have partnered in funding six projects that will lay the groundwork for faster and more robust space weather forecasting capabilities.
Motivated by the White House National Space Weather Strategy and Action Plan and the National Strategic Computing Initiative, NSF and NASA created the Space Weather with Quantified Uncertainties program. The program brings together teams from across scientific disciplines to advance the latest statistical analysis and high-performance computing methods within the field of space weather modeling.
"These awards will make sure that recent, extraordinary advances in computer modeling and data assimilation techniques are applied to critical questions in space weather research," says Mangala Sharma, NSF program officer for space weather in the Division of Atmospheric and Geospace Sciences." Space weather is a complex phenomenon, the study of which spans physical and geospace sciences, applied mathematics and computing. To address it, these projects bring together researchers with complementary expertise."
Together, NSF and NASA are investing over $17 million into six, three-year awards, each of which contributes to key research that can expand the nation's space weather prediction capabilities.
"Space weather involves intricate interactions between the sun, the solar wind, Earth's magnetic field and Earth's atmosphere," said Jim Spann, the space weather lead for NASA's heliophysics division at NASA headquarters in Washington. "Our ability to understand the sun-Earth system is of growing importance to economies, national security, and our society as it increasingly depends on technology. NASA and NSF through this program enable the operational organizations, NOAA and the Department of Defense, to incorporate that understanding into operational models and space weather predictions to better prepare us for potential impacts."
The projects include collaborations among multiple universities, national labs, and private companies across the country, offering opportunities to build connections with federal agencies and international partners and providing training for early career researchers.
Improving Space Weather Predictions with Data-Driven Models of the Solar Atmosphere and Inner Heliosphere, led by the University of Alabama in Huntsville and jointly supported by NSF and NASA, seeks to improve predictions of solar wind and coronal mass ejections by developing a data-driven model of the sun's upper atmosphere and how it might impact Earth.
NextGen Space Weather Modeling Framework, led by the University of Michigan and supported by NSF, will develop a model for optimal probabilistic sun-to-Earth space weather forecasting with a focus on major space weather events generated by coronal mass ejections.
A Flexible Community-based Upper Atmosphere Ensemble Prediction System, led by the University of Michigan and supported by NASA, will produce a model of the Earth's upper atmosphere that accounts for gaps in available data and improves on current model and software limitations.
Composable Next Generation Software Framework, led by the Massachusetts Institute of Technology and supported by NSF, aims to develop portable, extendable and sustainable space weather modeling software for current and next-generation high performance computing systems with uncertainty quantification and practical data assimilation.
Forecasting Small-Scale Plasma Structures in the Earth's Ionosphere-Thermosphere System, led by the University of Colorado Boulder and supported by NSF, will investigate plasma irregularities and changes in geomagnetic activity that could interrupt GPS satellites and other radio signals.
Ensemble Learning for Accurate and Reliable Uncertainty Quantification, led by the University of Colorado Boulder and supported by NASA, will introduce probabilistic modeling, estimations of uncertainty, and machine learning to space weather forecasting in order to improve their accuracy.
"This work aims to engage researchers from diverse scientific backgrounds to advance our understanding of what is both necessary and sufficient for predicting potentially harmful space weather events," says Slava Lukin, NSF program officer for plasma physics in the Division of Physics. "We hope that, by making models and software publicly available, these projects will seed advances that will transform our future space weather forecasting abilities."
For more announcements, visit NSF's announcement site.
Understanding Earth's surface from tree canopy to bedrock: NSF announces awards for network of "critical zone" research projects
09/01/2020
ANNOUNCEMENT
NSF Public Affairs
media@nsf.gov
703-292-8070
September 01, 2020
Space weather — solar wind, coronal mass ejections, magnetic storms, upper atmosphere disturbances — can damage infrastructure from electrical power supplies and computer networks to satellite and radio communications — and can even threaten astronauts' health. Accurate forecasting of energetic events on the sun and in the near-Earth space environment is critical for national security and the wellbeing of society. To address this need, the U.S. National Science Foundation and NASA have partnered in funding six projects that will lay the groundwork for faster and more robust space weather forecasting capabilities.
Motivated by the White House National Space Weather Strategy and Action Plan and the National Strategic Computing Initiative, NSF and NASA created the Space Weather with Quantified Uncertainties program. The program brings together teams from across scientific disciplines to advance the latest statistical analysis and high-performance computing methods within the field of space weather modeling.
"These awards will make sure that recent, extraordinary advances in computer modeling and data assimilation techniques are applied to critical questions in space weather research," says Mangala Sharma, NSF program officer for space weather in the Division of Atmospheric and Geospace Sciences." Space weather is a complex phenomenon, the study of which spans physical and geospace sciences, applied mathematics and computing. To address it, these projects bring together researchers with complementary expertise."
Together, NSF and NASA are investing over $17 million into six, three-year awards, each of which contributes to key research that can expand the nation's space weather prediction capabilities.
"Space weather involves intricate interactions between the sun, the solar wind, Earth's magnetic field and Earth's atmosphere," said Jim Spann, the space weather lead for NASA's heliophysics division at NASA headquarters in Washington. "Our ability to understand the sun-Earth system is of growing importance to economies, national security, and our society as it increasingly depends on technology. NASA and NSF through this program enable the operational organizations, NOAA and the Department of Defense, to incorporate that understanding into operational models and space weather predictions to better prepare us for potential impacts."
The projects include collaborations among multiple universities, national labs, and private companies across the country, offering opportunities to build connections with federal agencies and international partners and providing training for early career researchers.
Improving Space Weather Predictions with Data-Driven Models of the Solar Atmosphere and Inner Heliosphere, led by the University of Alabama in Huntsville and jointly supported by NSF and NASA, seeks to improve predictions of solar wind and coronal mass ejections by developing a data-driven model of the sun's upper atmosphere and how it might impact Earth.
NextGen Space Weather Modeling Framework, led by the University of Michigan and supported by NSF, will develop a model for optimal probabilistic sun-to-Earth space weather forecasting with a focus on major space weather events generated by coronal mass ejections.
A Flexible Community-based Upper Atmosphere Ensemble Prediction System, led by the University of Michigan and supported by NASA, will produce a model of the Earth's upper atmosphere that accounts for gaps in available data and improves on current model and software limitations.
Composable Next Generation Software Framework, led by the Massachusetts Institute of Technology and supported by NSF, aims to develop portable, extendable and sustainable space weather modeling software for current and next-generation high performance computing systems with uncertainty quantification and practical data assimilation.
Forecasting Small-Scale Plasma Structures in the Earth's Ionosphere-Thermosphere System, led by the University of Colorado Boulder and supported by NSF, will investigate plasma irregularities and changes in geomagnetic activity that could interrupt GPS satellites and other radio signals.
Ensemble Learning for Accurate and Reliable Uncertainty Quantification, led by the University of Colorado Boulder and supported by NASA, will introduce probabilistic modeling, estimations of uncertainty, and machine learning to space weather forecasting in order to improve their accuracy.
"This work aims to engage researchers from diverse scientific backgrounds to advance our understanding of what is both necessary and sufficient for predicting potentially harmful space weather events," says Slava Lukin, NSF program officer for plasma physics in the Division of Physics. "We hope that, by making models and software publicly available, these projects will seed advances that will transform our future space weather forecasting abilities."
For more announcements, visit NSF's announcement site.
Understanding Earth's surface from tree canopy to bedrock: NSF announces awards for network of "critical zone" research projects
09/01/2020
ANNOUNCEMENT
NSF Public Affairs
media@nsf.gov
703-292-8070
Understanding Earth's surface from tree canopy to bedrock: NSF announces awards for network of "critical zone" research projects
September 01, 2020
Land-use change. Environmental change. Extreme natural events such as hurricanes and wildfires. All are placing increasing pressure on the planet and its natural resources. In the critical zone, the layer from the top of the forest canopy to the base of weathered bedrock, where freshwater flows and soil forms from the breakdown of rocks, life flourishes.
To better understand Earth's critical zone — the realm where water, air, soil, rock and life interact — the U.S. National Science Foundation has funded 10 new Critical Zone Collaborative Network awards at $10.5 million per year total, for five years.
The water cycle; the breakdown of rocks and formation of soil; the geochemical and physical erosion of that soil; the evolution of rivers and valleys; patterns of vegetation; and the form and function of the Earth are all products of interactive processes in the critical zone.
Critical Zone Collaborative Network grantees will work to answer scientific questions such as the effects of urbanization on critical zone processes; critical zone function in semi-arid landscapes and the role of dust in sustaining these ecosystems; processes in deep bedrock and their relationship to critical zone evolution; the recovery of the critical zone from disturbances such as fire and flooding; and changes in the coastal critical zone related to rising sea level, among others.
"There's so much still to be learned about the planet we call home," says Richard Yuretich, NSF program director for the CZCN. "These new awards will allow scientists to develop systems-level models to predict how the critical zone is responding to natural and human-altered processes. The research, analysis and outreach activities supported by these grants are crucial for informing future decisions about how humans and the environment should interact."
Nine of the awards are for thematic clusters focused on science topics and one is for a network coordinating hub. The coordinating hub will manage data across projects, plan for future facility and equipment needs, and support outreach and education activities. This approach will lead to increased exchanges of data, information and learning opportunities for researchers and students at all levels.
More information about the CZCN is available on NSF's Critical Zone Collaborative Network website and in this list of awards.
For more announcements, visit NSF's announcement site.
NSF institutes advance U.S. ability to harness the data revolution
09/02/2020
ANNOUNCEMENT
September 01, 2020
Land-use change. Environmental change. Extreme natural events such as hurricanes and wildfires. All are placing increasing pressure on the planet and its natural resources. In the critical zone, the layer from the top of the forest canopy to the base of weathered bedrock, where freshwater flows and soil forms from the breakdown of rocks, life flourishes.
To better understand Earth's critical zone — the realm where water, air, soil, rock and life interact — the U.S. National Science Foundation has funded 10 new Critical Zone Collaborative Network awards at $10.5 million per year total, for five years.
The water cycle; the breakdown of rocks and formation of soil; the geochemical and physical erosion of that soil; the evolution of rivers and valleys; patterns of vegetation; and the form and function of the Earth are all products of interactive processes in the critical zone.
Critical Zone Collaborative Network grantees will work to answer scientific questions such as the effects of urbanization on critical zone processes; critical zone function in semi-arid landscapes and the role of dust in sustaining these ecosystems; processes in deep bedrock and their relationship to critical zone evolution; the recovery of the critical zone from disturbances such as fire and flooding; and changes in the coastal critical zone related to rising sea level, among others.
"There's so much still to be learned about the planet we call home," says Richard Yuretich, NSF program director for the CZCN. "These new awards will allow scientists to develop systems-level models to predict how the critical zone is responding to natural and human-altered processes. The research, analysis and outreach activities supported by these grants are crucial for informing future decisions about how humans and the environment should interact."
Nine of the awards are for thematic clusters focused on science topics and one is for a network coordinating hub. The coordinating hub will manage data across projects, plan for future facility and equipment needs, and support outreach and education activities. This approach will lead to increased exchanges of data, information and learning opportunities for researchers and students at all levels.
More information about the CZCN is available on NSF's Critical Zone Collaborative Network website and in this list of awards.
For more announcements, visit NSF's announcement site.
NSF institutes advance U.S. ability to harness the data revolution
09/02/2020
ANNOUNCEMENT
NSF institutes advance U.S. ability to harness the data revolution
September 01, 2020
Data science is a rapidly growing field that requires the expertise of computer scientists, mathematicians and statisticians to handle the analysis of ever-larger data sets. Big data affects how industry, academia and government operate, and the U.S. National Science Foundation is committed to leading the nation in foundational data science research.
NSF is pleased to announce Transdisciplinary Research in Principles of Data Science, or TRIPODS, a collection of research projects tied to Harnessing the Data Revolution Big Idea. This big idea aims to accelerate discovery and innovation in data science algorithms, data cyberinfrastructure, and education and workforce development.
"With NSF's $25 million investment, these interdisciplinary teams will be able to tackle some of the most important theoretical and technical questions in data science," said Division Director for Mathematical Sciences Juan Meza.
Additionally, these TRIPODS institutes contribute to fostering a robust workforce in STEM, by engaging students and trainees from diverse disciplines, hosting summer school programs and other outreach events, and maintaining connections with industry to focus on real-world applications for data science.
Given the importance and scope of these fundamental challenges, NSF is supporting two teams over five years focused on these topics in related but distinct ways.
Foundations of Data Science Institute is a collaboration between the University of California-Berkeley and Massachusetts Institute of Technology, partnering with Boston University, Northeastern University, Harvard University, Howard University and Bryn Mawr College. The goal is to better understand issues within data science including modeling, inference, computational efficiency and societal impacts. Research themes include the complex interactions between decision makers, the data they use and competing actors as well as methods for making use of vast amounts of data.
Institute for Foundations of Data Science is a collaboration between the University of Washington partnering with, University of Wisconsin-Madison, University of California-Santa Cruz and University of Chicago. Their research will lead to methods that are more computationally efficient, robust to errors and incomplete or ambiguous data, and better able to respond and act in changing environments. The team will also study the ethical and societal implications of data-driven algorithms, including privacy, unfairness and bias.
Both teams are dedicated to diversity and inclusion and will feature extensive activities for different educational levels and career pathways. For instance, the Foundations of Data Science Institute plans to recruit participants for its workshops from groups traditionally underrepresented in fields related to data science and arrange meetings that enable them to work with senior researchers. Likewise, the Institute for Foundations of Data Science will organize events targeting diverse groups of middle school, high school and undergraduate students through local partnerships.
"The TRIPODS program continues to lead the way in Harnessing the Data Revolution by addressing the most challenging and fundamental problems in data science," said Division Director for Computing and Communication Foundations Rance Cleaveland.
For more announcements, visit NSF's announcement site.
Check out the latest from NSF’s Science Matters blog - September 2, 2020
09/03/2020
SCIENCE MATTERS
sciencematters@nsf.gov
Check out the latest from NSF’s Science Matters blog.
Wed, 02 Sep 2020
A strong S&E ecosystem depends on partnerships: Maintaining US leadership in AI
Though you may not realize it, as you scroll through the morning's headlines on your smartphone, you hold in your hands the culmination of years of federally funded academic research.
Many of a smartphone's component parts—from the touchscreen interface to its wireless connectivity—resulted from key breakthroughs made in university research labs. Years later, companies picked up these technologies, hardening the capabilities and integrating them into the device upon which we now rely.
For nearly half a century, American ingenuity has pioneered the transformations that have enabled modern digital life and its devices—like your smartphone. This ingenuity has relied on collaboration between academic faculty and students, industry researchers, and government funders. It’s what makes America’s information technology ecosystem uniquely innovative.
Research conducted at U.S. universities with federal funding, combined with industrial innovation, has led to new products that have contributed billions of dollars to economic growth and major improvements to our way of life.
As recently highlighted in the National Science Board's Vision 2030 report, to continue pushing forward the foundations of emerging disciplines like artificial intelligence, which are especially ripe for industry collaboration, new and dynamic partnerships must be created to link foundational and use-inspired research in creative, sustained ways....
Continue Reading
For more National Science Foundation Science Matters blog, visit our blog site.
Accelerating research to impact society at scale
09/03/2020
ANNOUNCEMENT
September 01, 2020
Data science is a rapidly growing field that requires the expertise of computer scientists, mathematicians and statisticians to handle the analysis of ever-larger data sets. Big data affects how industry, academia and government operate, and the U.S. National Science Foundation is committed to leading the nation in foundational data science research.
NSF is pleased to announce Transdisciplinary Research in Principles of Data Science, or TRIPODS, a collection of research projects tied to Harnessing the Data Revolution Big Idea. This big idea aims to accelerate discovery and innovation in data science algorithms, data cyberinfrastructure, and education and workforce development.
"With NSF's $25 million investment, these interdisciplinary teams will be able to tackle some of the most important theoretical and technical questions in data science," said Division Director for Mathematical Sciences Juan Meza.
Additionally, these TRIPODS institutes contribute to fostering a robust workforce in STEM, by engaging students and trainees from diverse disciplines, hosting summer school programs and other outreach events, and maintaining connections with industry to focus on real-world applications for data science.
Given the importance and scope of these fundamental challenges, NSF is supporting two teams over five years focused on these topics in related but distinct ways.
Foundations of Data Science Institute is a collaboration between the University of California-Berkeley and Massachusetts Institute of Technology, partnering with Boston University, Northeastern University, Harvard University, Howard University and Bryn Mawr College. The goal is to better understand issues within data science including modeling, inference, computational efficiency and societal impacts. Research themes include the complex interactions between decision makers, the data they use and competing actors as well as methods for making use of vast amounts of data.
Institute for Foundations of Data Science is a collaboration between the University of Washington partnering with, University of Wisconsin-Madison, University of California-Santa Cruz and University of Chicago. Their research will lead to methods that are more computationally efficient, robust to errors and incomplete or ambiguous data, and better able to respond and act in changing environments. The team will also study the ethical and societal implications of data-driven algorithms, including privacy, unfairness and bias.
Both teams are dedicated to diversity and inclusion and will feature extensive activities for different educational levels and career pathways. For instance, the Foundations of Data Science Institute plans to recruit participants for its workshops from groups traditionally underrepresented in fields related to data science and arrange meetings that enable them to work with senior researchers. Likewise, the Institute for Foundations of Data Science will organize events targeting diverse groups of middle school, high school and undergraduate students through local partnerships.
"The TRIPODS program continues to lead the way in Harnessing the Data Revolution by addressing the most challenging and fundamental problems in data science," said Division Director for Computing and Communication Foundations Rance Cleaveland.
For more announcements, visit NSF's announcement site.
Check out the latest from NSF’s Science Matters blog - September 2, 2020
09/03/2020
SCIENCE MATTERS
sciencematters@nsf.gov
Check out the latest from NSF’s Science Matters blog.
Wed, 02 Sep 2020
A strong S&E ecosystem depends on partnerships: Maintaining US leadership in AI
Though you may not realize it, as you scroll through the morning's headlines on your smartphone, you hold in your hands the culmination of years of federally funded academic research.
Many of a smartphone's component parts—from the touchscreen interface to its wireless connectivity—resulted from key breakthroughs made in university research labs. Years later, companies picked up these technologies, hardening the capabilities and integrating them into the device upon which we now rely.
For nearly half a century, American ingenuity has pioneered the transformations that have enabled modern digital life and its devices—like your smartphone. This ingenuity has relied on collaboration between academic faculty and students, industry researchers, and government funders. It’s what makes America’s information technology ecosystem uniquely innovative.
Research conducted at U.S. universities with federal funding, combined with industrial innovation, has led to new products that have contributed billions of dollars to economic growth and major improvements to our way of life.
As recently highlighted in the National Science Board's Vision 2030 report, to continue pushing forward the foundations of emerging disciplines like artificial intelligence, which are especially ripe for industry collaboration, new and dynamic partnerships must be created to link foundational and use-inspired research in creative, sustained ways....
Continue Reading
For more National Science Foundation Science Matters blog, visit our blog site.
Accelerating research to impact society at scale
09/03/2020
ANNOUNCEMENT
Accelerating research to impact society at scale
September 03, 2020
Research drives the development of innovations that improve our daily lives. That's why the U.S. National Science Foundation works to make the transition from use-inspired research into practical applications as fast and productive as possible. NSF created the Convergence Accelerator program as a cornerstone for efforts to address national-scale societal challenges, integrating multidisciplinary research and innovation processes to transition research and discovery toward impactful solutions.
NSF is pleased to announce the investment of more than $28 million to advance nine research teams who will address national-scale societal challenges and generate knowledge to transition ideas from research into practice. The teams will develop solutions in three topic areas to include Open Knowledge Networks, AI and Future Jobs, and National Talent Ecosystem.
Over the next 24 months, these teams who are entering phase two of their research will continue to apply Convergence Accelerator fundamentals to include leveraging innovation processes and integrating multidisciplinary research and cross-cutting partnerships to develop solution prototypes and to build a sustainability model to continue impact beyond NSF support.
Currently, the convergence research teams comprise of 56 academic institutions, 40 non-profit, 21 government, 36 industry partners, 10 education sector organizations, and two healthcare sector organizations.
"Convergence Accelerator is producing true innovation," said Douglas Maughan, program head. "All 2019 cohort teams worked hard to further develop their initial concepts, strengthen their teams, and engage with customers and partners; however, phase two is where we expect to see high-impact deliverables."
Open Knowledge Networks include:
Systematic Content Analysis of Litigation Events Open Knowledge Network to Enable Transparency and Access to Court Records, led by Northwestern University.
A Multi-Scale Open Knowledge Network for Biomedicine, developed by University of California San Francisco
Knowledge Network Development Infrastructure with Application to COVID-19 Science and Economics, developed by the University of Michigan
Know Where Graph: Enriching and Linking Cross-Domain Knowledge Graphs Using Spatially-Explicit AI Technologies, led by the University of California Santa Barbara.
The Urban Flooding Open Knowledge Network: Delivering Flood Information to Any One, Any Time, Any Where, led by the University of Cincinnati
AI and Future Jobs, and National Talent Ecosystem include:
Learning Environments with Augmentation and Robotics for Next-gen Emergency Responders, led by Texas A&M
Skill-XR: An Affordable and Scalable X-Reality Platform for Skills Training and Analytics in Manufacturing Workforce Education, led by Purdue University.
Competency Catalyst Phase II, led by Eduworks Corporation
Inclusion AI for Neurodiverse Employment, led by Vanderbilt University
Learn more about Convergence Accelerator at nsf.gov.
September 03, 2020
Research drives the development of innovations that improve our daily lives. That's why the U.S. National Science Foundation works to make the transition from use-inspired research into practical applications as fast and productive as possible. NSF created the Convergence Accelerator program as a cornerstone for efforts to address national-scale societal challenges, integrating multidisciplinary research and innovation processes to transition research and discovery toward impactful solutions.
NSF is pleased to announce the investment of more than $28 million to advance nine research teams who will address national-scale societal challenges and generate knowledge to transition ideas from research into practice. The teams will develop solutions in three topic areas to include Open Knowledge Networks, AI and Future Jobs, and National Talent Ecosystem.
Over the next 24 months, these teams who are entering phase two of their research will continue to apply Convergence Accelerator fundamentals to include leveraging innovation processes and integrating multidisciplinary research and cross-cutting partnerships to develop solution prototypes and to build a sustainability model to continue impact beyond NSF support.
Currently, the convergence research teams comprise of 56 academic institutions, 40 non-profit, 21 government, 36 industry partners, 10 education sector organizations, and two healthcare sector organizations.
"Convergence Accelerator is producing true innovation," said Douglas Maughan, program head. "All 2019 cohort teams worked hard to further develop their initial concepts, strengthen their teams, and engage with customers and partners; however, phase two is where we expect to see high-impact deliverables."
Open Knowledge Networks include:
Systematic Content Analysis of Litigation Events Open Knowledge Network to Enable Transparency and Access to Court Records, led by Northwestern University.
A Multi-Scale Open Knowledge Network for Biomedicine, developed by University of California San Francisco
Knowledge Network Development Infrastructure with Application to COVID-19 Science and Economics, developed by the University of Michigan
Know Where Graph: Enriching and Linking Cross-Domain Knowledge Graphs Using Spatially-Explicit AI Technologies, led by the University of California Santa Barbara.
The Urban Flooding Open Knowledge Network: Delivering Flood Information to Any One, Any Time, Any Where, led by the University of Cincinnati
AI and Future Jobs, and National Talent Ecosystem include:
Learning Environments with Augmentation and Robotics for Next-gen Emergency Responders, led by Texas A&M
Skill-XR: An Affordable and Scalable X-Reality Platform for Skills Training and Analytics in Manufacturing Workforce Education, led by Purdue University.
Competency Catalyst Phase II, led by Eduworks Corporation
Inclusion AI for Neurodiverse Employment, led by Vanderbilt University
Learn more about Convergence Accelerator at nsf.gov.
