Group items matching

in title, tags, annotations or url

In 2016, the National Science Foundation (NSF) unveiled a set of "Big Ideas," 10 bold, long-term research and process ideas that identify areas for future investment at the frontiers of science and engineering (see https://www.nsf.gov/news/special_reports/big_ideas/index.jsp). The Big Ideas represent unique opportunities to position our Nation at the cutting edge of global science and engineering leadership by bringing together diverse disciplinary perspectives to support convergence research. As such, when responding to this solicitation, even though proposals must be submitted to the Directorate for Computer & Information Science & Engineering/Office of Advanced Cyberinfrastructure(CISE/OAC), once received, the proposals will be managed by a cross-disciplinary team of NSF Program Directors. NSF's Harnessing the Data Revolution (HDR) Big Ideais a national-scale activity to enable new modes of data-driven discovery that will allow fundamental questions to be asked and answered at the frontiers of science and engineering.

The purpose of this Dear Colleague Letter is to advise of funding opportunities at the National Science Foundation's Science of Science and Innovation Policy (SciSIP) Program for innovative projects using data from STAR METRICS (Science and Technology for America's Reinvestment: Measuring the Effect of Research on Innovation, Competitiveness and Science) or the National Center for Science and Engineering Statistics (NCSES).

The BIGDATA program seeks novel approaches in computer science, statistics, computational science, and mathematics, along with innovative applications in domain science, including social and behavioral sciences, geosciences, education, biology, the physical sciences, and engineering that lead towards the further development of the interdisciplinary field of data science

The NSF's vision for Advanced Computing Infrastructure (ACI), which is part of its Cyberinfrastructure for 21st Century Science and Engineering (CIF21), focuses specifically on ensuring that the science and engineering community has ready access to the advanced computational and data-driven capabilities required to tackle the most complex problems and issues facing today's scientific and educational communities. To accomplish these goals requires advanced computational capabilities within the context of a multilevel comprehensive and innovative infrastructure that benefits all fields of science and engineering. Previous solicitations have concentrated on enabling petascale capability through the deployment and support of a world-class High Performance Computing (HPC) environment. In the past decade the NSF has provided the open science and engineering community with a number of state-of-the art HPC assets ranging from loosely coupled clusters, to large scale instruments with many thousands of computing cores communicating via fast interconnects, and more recently with diverse heterogeneous architectures. Recent developments in computational science have begun to focus on complex, dynamic and diverse workflows. Some of these involve applications that are extremely data intensive and may not be dominated by floating point operation speed. While a number of the earlier acquisitions have addressed a subset of these issues, the current solicitation emphasizes this even further.

The CDS&E-MSS program accepts proposals that confront and embrace the host of mathematical and statistical challenges presented to the scientific and engineering communities by the ever-expanding role of computational modeling and simulation on the one hand, and the explosion in production of digital and observational data on the other. The goal of the program is to promote the creation and development of the next generation of mathematical and statistical theories and tools that will be essential for addressing such issues. To this end, the program will support fundamental research in mathematics and statistics whose primary emphasis will be on meeting the aforementioned computational and data-related challenges. This program is part of the wider Computational and Data-enabled Science and Engineering (CDS&E) enterprise in NSF that seeks to address this emerging discipline

The CDS&E-MSS program accepts proposals that confront and embrace the host of mathematical and statistical challenges presented to the scientific and engineering communities by the ever-expanding role of computational modeling and simulation on the one hand, and the explosion in production of digital and observational data on the other. The goal of the program is to promote the creation and development of the next generation of mathematical and statistical theories and tools that will be essential for addressing such issues. To this end, the program will support fundamental research in mathematics and statistics whose primary emphasis will be on meeting the aforementioned computational and data-related challenges. This program is part of the wider Computational and Data-enabled Science and Engineering (CDS&E) enterprise in NSF that seeks to address this emerging discipline

The National Science Foundation (NSF) Directorates for Engineering (ENG) and Geosciences (GEO), the Divisions of Integrative Organismal Systems (IOS) and Environmental Biology (DEB), in the Directorate for Biological Sciences (BIO), the Division of Computer and Network Systems in the Directorate Computer and Information Science and Engineering (CISE/CNS), and the Division of Chemistry (CHE) in the Directorate for Mathematical and Physical Sciences, in collaboration with the US Department of Agriculture National Institute of Food and Agriculture (USDA NIFA) encourage convergent research that transforms existing capabilities in understanding dynamic soil processes, including soil formation, through advances in sensor systems and modeling. The Signals in the Soil (SitS) program fosters collaboration among the two partner agencies and the researchers they support by combining resources and funding for the most innovative and high-impact projects that address their respective missions. To make transformative advances in our understanding of soils, multiple disciplines must converge to produce environmentally-benign novel sensing systems with multiple modalities that can adapt to different environments and collect and transmit data for a wide range of biological, chemical, and physical parameters. Effective integration of sensor data will be key for achieving a better understanding of signaling interactions among plants, animals, microbes, the soil matrix, and aqueous and gaseous components. New sensor networks have the potential to inform models in novel ways, to radically change how data is obtained from various natural and managed (both urban and rural) ecosystems, and to better inform the communities that directly rely on soils for sustenance and livelihood.

PD 15-1637, Structural and Architectural Engineering (SAE) program replaces Hazard Mitigation and Structural Engineering (HMSE) program. The overall goal of the Structural and Architectural Engineering (SAE) program is to evolve sustainable structures, such as buildings, that can be continuously occupied and /or operational during the structure??s useful life. The SAE program supports fundamental research for advancing knowledge and innovation in structural and architectural engineering that enables holistic approach to design, construction, operation, maintenance, retrofit, repair and end-of-life disposal of structures. For buildings, holistic approach incorporates the foundation-structure-envelope-nonstructural system, as well as the facade and roofing. Research topics of interest for sustainable structures include the following: strategies for structures that over their lifecycle are cost-effective, make efficient use of resources and energy, and incorporate sustainable structural and architectural materials; deterioration due to fatigue and corrosion; serviceability concerns due to large deflections and vibrations; and advances in physics-based computational modeling and simulation. Research is encouraged that integrates discoveries from other science and engineering fields, such as materials science, building science, mechanics of materials, dynamic systems and control, reliability, risk analysis, architecture, economics and human factors. The program also supports research in sustainable and holistic foundation-structure-envelope-nonstructural systems and materials as described in the following reports: ?? National Science and Technology Council, High Performance Buildings; Final Report: Federal R & D Agenda for Net Zero Energy, High-Performance Green Buildings. Building Technology Research and Development (BTRD) Subcommittee, OSTP, U.S. Government, September 2008. http://www.whitehouse.gov/files/documents/ostp/NSTC%20Reports/Federal%20RD%20Agenda%20for%20Net%

The Office ofAdvanced Cyberinfrastructure (OAC) supports translational research and education activities in all aspects of advanced cyberinfrastructure (CI) that lead to deployable, scalable, and sustainable systems capable of transforming science and engineering research. Advanced CI includes the spectrum of computational, data, software, networking, and security resources, tools, and services, along with the computational and data skills and expertise, that individually and collectively can transform science and engineering. OAC supports advanced CI research to address new CI frontiers for discovery leading to major innovations, and supports the development and deployment processes, as well as expert services, necessary for realizing the research CI that is critical to the advancement of all areas of science and engineering research and education. OAC research investments are characterized by their translational nature, i.e., building on basic research results and spanning the design to practice stages. They are further characterized by one or more of the following key attributes: multi-disciplinary, extreme-scale, driven by science and engineering research, end-to-end, and deployable as robust research CI. Areas of translational research supported by OAC include systems architecture and middleware for extreme-scale systems, scalable algorithms and applications, and the advanced CI ecosystem. Principal investigators (PIs) are strongly encouraged to contact an OAC cognizant program director listed in this solicitation with a 1-page project summary for further guidance. For foundational computer and information science and engineering research, PIs are referred to the core research programs of the Computer and Communication Foundations (CCF), Computer and Network Systems (CNS), and Information and Intelligent Systems (IIS) divisions of CISE. Proposers are invited to submit proposals in one project class, which is defined as follows:

The Big Ideas represent unique opportunities to position our Nation at the cutting edge of global science and engineering leadership by bringing together diverse disciplinary perspectives to support convergence research. As such, when responding to this solicitation, even though proposals must be submitted tothe Division of Information and Intelligent Systems (IIS) within the Directorate for Computer and Information Science and Engineering (CISE),once received, the proposals will be managed by a cross-disciplinary team of NSF Program Directors. NSF'sHarnessing the Data Revolution (HDR)Big Idea is a visionary, national-scale activity to enable new modes of data-driven discovery, allowing fundamentally new questions to be asked and answered in science and engineering frontiers, generating new knowledge and understanding, and accelerating discovery and innovation.

The National Science Foundation (NSF) Directorates for Engineering (ENG) and Geosciences (GEO), the Divisions of Integrative Organismal Systems (IOS) and Environmental Biology (DEB), in the Directorate for Biological Sciences (BIO), the Division of Computer and Network Systems in the Directorate Computer and Information Science and Engineering (CISE/CNS), and the Division of Chemistry (CHE) in the Directorate for Mathematical and Physical Sciences, in collaboration with the US Department of Agriculture National Institute of Food and Agriculture (USDA NIFA) encourage convergent research that transforms existing capabilities in understanding dynamic soil processes, including soil formation, through advances in sensor systems and modeling. The Signals in the Soil (SitS) program fosters collaboration among the two partner agencies and the researchers they support by combining resources and funding for the most innovative and high-impact projects that address their respective missions. To make transformative advances in our understanding of soils, multiple disciplines must converge to produce environmentally-benign novel sensing systems with multiple modalities that can adapt to different environments and collect and transmit data for a wide range of biological, chemical, and physical parameters. Effective integration of sensor data will be key for achieving a better understanding of signaling interactions among plants, animals, microbes, the soil matrix, and aqueous and gaseous components. New sensor networks have the potential to inform models in novel ways, to radically change how data is obtained from various natural and managed (both urban and rural) ecosystems, and to better inform the communities that directly rely on soils for sustenance and livelihood.

The Science of Science & Innovation Policy (SciSIP) program supports research designed to advance the scientific basis of science and innovation policy. Research funded by the program thus develops, improves and expands models, analytical tools, data and metrics that can be applied in the science policy decision making process.

DMREF is the primary program by which NSF participates in the Materials Genome Initiative (MGI) for Global Competitiveness. MGI recognizes the importance of materials science and engineering to the well-being and advancement of society and aims to "deploy advanced materials at least twice as fast as possible today, at a fraction of the cost." MGI integrates materials discovery, development, property optimization, and systems design with a shared computational framework. This framework facilitates collaboration and coordination of research activities, analytical tools, experimental results, and critical evaluation in pursuit of the MGI goals. The MGI Strategic Plan highlights four sets of goals: -Leading a culture shift in materials science research to encourage and facilitate an integrated team approach; -Integrating experimentation, computation, and theory and equipping the materials community with advanced tools and techniques; -Making digital data accessible; and -Creating a world-class materials science and engineering workforce that is trained for careers in academia or industry.

DMREF is the primary program by which NSF participates in the Materials Genome Initiative (MGI) for Global Competitiveness. MGI recognizes the importance of materials science and engineering to the well-being and advancement of society and aims to "deploy advanced materials at least twice as fast as possible today, at a fraction of the cost." MGI integrates materials discovery, development, property optimization, and systems design with a shared computational framework. This framework facilitates collaboration and coordination of research activities, analytical tools, experimental results, and critical evaluation in pursuit of the MGI goals. The MGI Strategic Plan highlights four sets of goals: -Leading a culture shift in materials science research to encourage and facilitate an integrated team approach; -Integrating experimentation, computation, and theory and equipping the materials community with advanced tools and techniques; -Making digital data accessible; and -Creating a world-class materials science and engineering workforce that is trained for careers in academia or industry.

This solicitation includes two classes of science data pilot awards: 1. Early Implementations are large "at scale" evaluations, building upon cyberinfrastructure capabilities of existing research communities or recognized community data collections, and extending those data-focused cyberinfrastructure capabilities to additional research communities and domains with broad community engagement. 2. Pilot Demonstrations address advanced cyberinfrastructure challenges across emerging research communities, building upon recognized community data collections and disciplinary research interests, to address specific challenges in science and engineering research.

The purpose of this Dear Colleague Letter is to advise you about funding opportunities at the National Science Foundation for the research community to propose research projects or workshops that will gather data on the implementation and impacts of recent science policy initiatives including, but not limited to those noted earlier.  Especially encouraged are proposals that will: Develop new, or improve existing, analytical frameworks for evaluating the impacts of federal science policy initiatives; Explore different agencies' approaches to the implementation of particular policies to examine how variations in approach affect the achievement of intended policy outcomes; Collect case-study or quantitative data that facilitate identification of best practices in science and innovation policy implementation.

The goal of the interagency Smart and Connected Health (SCH): Connecting Data, People and Systems program is to accelerate the development and integration of innovative computer and information science and engineering approaches to support the transformation of health and medicine. Approaches that partner technology-based solutions with biomedical and biobehavioral research are supported by multiple agencies of the federal government including the National Science Foundation (NSF) and the National Institutes of Health (NIH). The purpose of this program is to develop next-generation multidisciplinary science that encourages existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as networking, pervasive computing, advanced analytics, sensor integration, privacy and security, modeling of socio-behavioral and cognitive processes and system and process modeling. Effective solutions must satisfy a multitude of constraints arising from clinical/medical needs, barriers to change, heterogeneity of data, semantic mismatch and limitations of current cyberphysical systems and an aging population. Such solutions demand multidisciplinary teams ready to address issues ranging from fundamental science and engineering to medical and public health practice.

The goal of the interagency Smart and Connected Health (SCH): Connecting Data, People and Systems program is to accelerate the development and integration of innovative computer and information science and engineering approaches to support the transformation of health and medicine. Approaches that partner technology-based solutions with biomedical and biobehavioral research are supported by multiple agencies of the federal government including the National Science Foundation (NSF) and the National Institutes of Health (NIH). The purpose of this program is to develop next-generation multidisciplinary science that encourages existing and new research communities to focus on breakthrough ideas in a variety of areas of value to health, such as networking, pervasive computing, advanced analytics, sensor integration, privacy and security, modeling of socio-behavioral and cognitive processes and system and process modeling. Effective solutions must satisfy a multitude of constraints arising from clinical/medical needs, barriers to change, heterogeneity of data, semantic mismatch and limitations of current cyberphysical systems and an aging population. Such solutions demand multidisciplinary teams ready to address issues ranging from fundamental science and engineering to medical and public health practice.

Hazards SEES seeks research projects that will productively cross the boundaries of the atmospheric and geospace, earth, and ocean sciences; computer and information science; cyberinfrastructure; engineering; mathematics and statistics; and social, economic, and behavioral sciences. Successful proposals will integrate across these multiple disciplines to promote research that advances new paradigms that contribute to creating a society resilient to hazards. Hazards SEES intends to transform hazards and disaster research by fostering the development of interdisciplinary research that allows for appropriately targeted data collection, integration, and management; modeling (including predictive models for real-time decision making); visualization and simulation; data analytics and data-driven discovery; real-time sensing; cross-cutting knowledge development; and synthesis of applicable models and theory. 

In 2016, the National Science Foundation (NSF) unveiled a set of "Big Ideas," 10 bold, long-term research and process ideas that identify areas for future investment at the frontiers of science and engineering (see https://www.nsf.gov/news/special_reports/big_ideas/index.jsp). The Big Ideas represent unique opportunities to position our Nation at the cutting edge of global science and engineering leadership by bringing together diverse disciplinary perspectives to support convergence research. As such, when responding to this solicitation, even though proposals must be submitted to the Division of Information and Intelligent Systems (IIS) within the Directorate for Computer and Information Science and Engineering (CISE), once received, the proposals will be managed by a cross-disciplinary team of NSF Program Directors.

The CDS&E-MSS program accepts proposals that confront and embrace the host of mathematical and statistical challenges presented to the scientific and engineering communities by the ever-expanding role of computational modeling and simulation on the one hand, and the explosion in production of digital and observational data on the other. The goal of the program is to promote the creation and development of the next generation of mathematical and statistical theories and tools that will be essential for addressing such issues. To this end, the program will support fundamental research in mathematics and statistics whose primary emphasis will be on meeting the aforementioned computational and data-related challenges. This program is part of the wider Computational and Data-enabled Science and Engineering (CDS&E) enterprise in NSF that seeks to address this emerging discipline. The research supported by the CDS&E-MSS program will aim to advance mathematics or statistics in a significant way and will address computational or big-data challenges.

The Center would like to enhance its efforts to support analytic and methodological research in support of its surveys, and to engage in the education and training of researchers in the use of large-scale nationally representative datasets.  NCSES welcomes efforts by the research community to use NCSES data for research on the science and technology enterprise, to develop improved survey methodologies for NCSES surveys, to create and improve indicators of S&T activities and resources, and strengthen methodologies to analyze and disseminate S&T statistical data. To that end, NCSES invites proposals for individual or multi-investigator research projects, doctoral dissertation improvement awards, workshops, experimental research, survey research and data collection and dissemination projects under its program for Research on the Science and Technology Enterprise:  Statistics and Surveys.