The OFRN Round 5 Sustaining Ohio's Aeronautical Readiness and Innovation in the Next Generation (SOARING) Opportunity Announcement is focused on expanding Ohio's research and development capabilities across the state's academic institutions and business in support of Ohio-based federal partner needs, which ultimately promotes Ohio's economic growth. OFRN Round 5 Areas of Interest (AOIs) include topics in Unmanned Aerial Systems (UAS), Artificial Intelligence, Human Factors, Data Analytics, Space Commercialization, Quantum Communications and Advanced Power Systems. This announcement seeks to leverage Ohio's unique research capabilities and its federal partner's expertise to accelerate technology development and innovation by increasing collaboration across government, academic, and industry organizations.
The RISA program supports the development of knowledge, expertise, and abilities of decision-makers to plan and prepare for climate variability and change. Through regionally-focused and interdisciplinary research and engagement teams, RISA builds and expands the Nation's capacity to adapt and become resilient to extreme weather events and climate change. RISA teams accomplish this through co-developed applied research and partnerships with public and private communities. A central tenet of the RISA program is that learning about climate adaptation and resilience is facilitated by and sustained across a wide range of experts, practitioners, and the public. As such, the RISA program supports a network of people, prioritizing wide participation in learning by doing, learning through adapting, and managing risk with uncertain information. Early decades of the program focused on understanding the use of climate information at regional scales (e.g., through experimental seasonal outlooks), improving predictions and scenarios, building capacity for drought early warning, and advancing the science of climate impact assessments. More recently, emphasis has shifted to address the growing urgency to advance approaches that tackle the complex societal issues surrounding adaptation planning, implementation, and building community resilience. To do so, RISA continues to prioritize collaborative approaches that incorporate multiple knowledge sources and integrate social, physical, and natural science, resulting in long-term support of and increased capacity for communities.
Growing Convergence Research (GCR) at the National Science Foundation was identified as one of 10 Big Ideas. Convergence research is a means for solving vexing research problems, in particular, complex problems focusing on societal needs. It entails integrating knowledge, methods, and expertise from different disciplines and forming novel frameworks to catalyze scientific discovery and innovation.
GCR identifies Convergence Research as having two primary characteristics:
Research driven by a specific and compelling problem. Convergence Research is generally inspired by the need to address a specific challenge or opportunity, whether it arises from deep scientific questions or pressing societal needs.
Deep integration across disciplines. As experts from different disciplines pursue common research challenges, their knowledge, theories, methods, data, research communities and languages become increasingly intermingled or integrated. New frameworks, paradigms or even disciplines can form sustained interactions across multiple communities.
A distinct characteristic of convergence research, in contrast to other forms of multidisciplinary research, is that from the inception, the convergence paradigm intentionally brings together intellectually diverse researchers and stakeholders to frame the research questions, develop effective ways of communicating across disciplines and sectors, adopt common frameworks for their solution, and, when appropriate, develop a new scientific vocabulary. Research teams practicing convergence aim at developing sustainable relationships that may not only create solutions to the problem that engendered the collaboration, but also develop novel ways of framing related research questions and open new research vistas.
The Cyberinfrastructure for Sustained Scientific Innovation (CSSI) umbrella program seeks to enable funding opportunities that are flexible and responsive to the evolving and emerging needs in cyberinfrastructure (CI). This program continues the CSSI program by removing the distinction between software and data elements/framework implementations, and instead emphasizing integrated CI services, quantitative metrics with targets for delivery and usage of these services, and community creation.
The CSSI umbrella program anticipates two classes of awards:
Elements: These awards target small groups that will create and deploy robust services for which there is a demonstrated need, and that will advance one or more significant areas of science and engineering.
Framework Implementations: These awards target larger, interdisciplinary teams organized around the development and application of services aimed at solving common research problems faced by NSF researchers in one or more areas of science and engineering, and resulting in a sustainable community framework providing CI services to a diverse community or communities.
Prospective Principal Investigators (PIs) should be aware that this is a multi-directorate activity and that they are encouraged to submit proposals with broad, interdisciplinary interests. Further, not all divisions are participating at the same level and division-specific priorities differ. Prospective PIs should also refer to the directorate/division-specific descriptions contained in Section II of this solicitation.
This Funding Opportunity Announcement (FOA) aims to support research to strengthen the healthcare response to Coronavirus Disease 2019 (COVID-19) caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and future public health emergencies, including pandemics. While research related to the direct clinical effects of COVID-19 are supported by other funding opportunities, the purpose of this funding opportunity is to focus on the role and impact of digital health interventions [e.g., mobile health (mhealth), telemedicine and telehealth, health information technology (IT), and wearable devices] to address access, reach, delivery, effectiveness, scalability and sustainability of health assessments and interventions for secondary effects (e.g., behavioral health or self-management of chronic conditions) that are utilized during and following the pandemic, particularly in populations who experience health disparities and vulnerable populations.
The Core Infrastructure Fund (CIF) strives to uphold and increase capacity for individuals, organizations, and companies working to fortify the foundational components of demonstrably important technology relied upon by people in repressive countries.
Ideal applications are: open in nature, collaborative, promote a broader understanding of existing challenges and limitations, are preemptive in approach, and/or exist at the core of the Internet's ecosystem. Common applicants come from the community of developers and organizers working on open-source projects recognized as critical dependencies of one or more active platforms or tools strengthening Internet freedom and digital security.
Ideal applications for this fund focus on supporting:
Key developers or organizers so they can work full time on crucial core efforts in need of additional support;
New developers or organizers focused on improving security standards, quality assurance, and best practices within core infrastructure projects;
Developers, authors, or organizers drafting or promoting digital security and civil society needs within standards and protocols;
Researchers exploring new methods of circumvention that would improve the resiliency of widely utilized tools;
Specific outcomes, such as the necessary maintenance and upgrades to existing open source projects (database, hosting, or other tool migration; rewriting test suites; major new features);
Efforts that make existing projects more accessible and easier to contribute to (ex. documentation, tool migration, refactoring code, testing);
Efforts that develop new or evolve existing organizational and governance structures and sustainability models beyond work-for-hire;
Efforts that increase the understanding and awareness of relevant actors in this space, their roles, and how they contribute to maintaining the Internet's core ecosystem;
Artificial Intelligence (AI) has advanced tremendously and today promises personalized healthcare; enhanced national security; improved transportation; and more effective education, to name just a few benefits. Increased computing power, the availability of large datasets and streaming data, and algorithmic advances in machine learning (ML) have made it possible for AI development to create new sectors of the economy and revitalize industries. Continued advancement, enabled by sustained federal investment and channeled toward issues of national importance, holds the potential for further economic impact and quality-of-life improvements.
The Nation's advanced research cyberinfrastructure (CI) ecosystem catalyzes discovery and innovation across all areas of science and engineering (S&E) research and education. The increasingly complex and rapidly evolving S&E landscape requires an agile, integrated, robust, trustworthy, and sustainable CI ecosystem that will drive new thinking and transformative discoveries in all areas of research and education. The success of this vision depends on the ability of the research community to be able to easily and effectively access and use state-of-the-art research CI resources and services in a timely way. This, in turn, drives a set of requirements on the development, operation, and evolution of the CI ecosystem. First, research CI resources and services must be designed to leverage and drive innovations, and they must be user-centric and interoperable to enable the efficient, flexible end-to-end discovery pathways that are increasingly essential for the conduct of research. Second, the information, expertise, and services needed to maximally utilize the CI ecosystem must be disseminated broadly and concertedly to the research community. The NSF Cyberinfrastructure Centers of Excellence (CI CoE) Program aims to realize the above vision by supporting hubs of expertise and innovation targeting specific areas, aspects, or stakeholder communities of the research CI ecosystem.
The Cyberinfrastructure for Sustained Scientific Innovation (CSSI) umbrella program seeks to enable funding opportunities that are flexible and responsive to the evolving and emerging needs in cyberinfrastructure. This program continues the CSSI program by removing the distinction between software and data elements/framework implementations, and instead emphasizing integrated cyberinfrastructure services, quantitative metrics with targets for delivery and usage of these services, and community creation.
PFI has five broad goals, as set forth by the American Innovation and Competitiveness Act of 2017 ("the Act", S.3084 - 114th Congress; Sec. 602. Translational Research Grants): (1) identifying and supporting NSF-sponsored research and technologies that have the potential for accelerated commercialization; (2) supporting prior or current NSF-sponsored investigators, institutions of higher education, and non-profit organizations that partner with an institution of higher education in undertaking proof-of-concept work, including the development of technology prototypes that are derived from NSF-sponsored research and have potential market value; (3) promoting sustainable partnerships between NSF-funded institutions, industry, and other organizations within academia and the private sector with the purpose of accelerating the transfer of technology; (4) developing multi-disciplinary innovation ecosystems which involve and are responsive to the specific needs of academia and industry; (5) providing professional development, mentoring, and advice in entrepreneurship, project management, and technology and business development to innovators.
ecoTech™ Grants were created to combat the notion that students needed to choose between "the screen" or "the green" and to encourage educators and students to explore the role technology can play in designing and implementing solutions to some of our most pressing environmental challenges. We believe that technology can present innovative ways to address environmental challenges - and that when dealing with digital natives, we do ourselves a disservice by asking them to unplug.
Originally developed in partnership with the Ray C. Anderson Foundation and now funded with ongoing support from Voya Financial Foundation, ecoTech™ Grants are specifically offered to engage children in inquiry-based, STEM-related projects that leverage technology and/or use nature-based design to address environmental problems in local communities.
Examples of previous ecoTech™ Grant funded projects have involved: the integration of robotics and sensors to explore water bodies, collect data, and organize clean-ups; the development of aquaponic and hydroponic systems using arduinos and remote sensing; renewable energy design challenges; biotechnology research; nature-based design applications; and many others.
The Computer and Information Science and Engineering (CISE) Community Research Infrastructure (CCRI) program drives discovery and learning in the core CISE disciplines of the three participating divisions [(Computing and Communication Foundations (CCF), Computer and Network Systems (CNS), and Information and Intelligent Systems (IIS)] by funding the creation and enhancement of world-class research infrastructure. This research infrastructure will specifically support diverse communities of CISE researchers pursuing focused research agendas in computer and information science and engineering. This support involves developing the accompanying user services and engagement needed to attract, nurture, and grow a robust research community that is actively involved in determining directions for the infrastructure as well as management of the infrastructure.This should lead to infrastructure that can be sustained through community involvement and community leadership, and that will enable advances not possible with existing research infrastructure. Further, through the CCRI program, CISE seeks to ensure that researchers from a diverse range of academic institutions, including minority-serving and predominantly undergraduate institutions, as well as researchers from non-profit, non-academic organizations, have access to such infrastructure.
NSF's Directorate for Computer and Information Science and Engineering (CISE) initiated the National Network of Big Data Regional Innovation Hubs (BD Hubs) program in FY 2015 (NSF 15-562). Four Big Data Hubs (BD Hubs)Midwest, Northeast, South, and Westwere established, one in each of the four Census Regions of the United States[1]. The BD Hubs provide the ability to engage local or regional stakeholders, e.g., city, county, and state governments, local industry and non-profits, and regional academic institutions, in big data research, and permit a focus on regional issues. These collaborative activities and partnerships play a critical role in building and sustaining a successful national big data innovation ecosystem. This solicitation continues the operation of a national network of BD Hubs. It builds on demonstrated strengths of the program, which has grown to include a set of BD Spokes affiliated with the BD Hubs, and is responsive to the recent developments in data science. For instance, the recently released report on Data Science for Undergraduates: Opportunities and Options from the National Academies of Sciences, Engineering, and Medicine exemplifies the urgency of multi-faceted education and training in data science. The BD Hubs will continue to nucleate regional collaborations and multi-sector projects, while fostering innovation in data science. The NSF BD Hubs program is aligned with NSFs Harnessing the Data Revolution (HDR) Big Idea, one of NSFs 10 Big Ideas for Future Investment. HDR 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.
NSF's Directorate for Computer and Information Science and Engineering (CISE) initiated the National Network of Big Data Regional Innovation Hubs (BD Hubs) program in FY 2015 (NSF 15-562). Four Big Data Hubs (BD Hubs)-Midwest, Northeast, South, and West-were established, one in each of the four Census Regions of the United States[1]. The BD Hubs provide the ability to engage local or regional stakeholders, e.g., city, county, and state governments, local industry and non-profits, and regional academic institutions, in big data research, and permit a focus on regional issues. These collaborative activities and partnerships play a critical role in building and sustaining a successful national big data innovation ecosystem.
The Office of Advanced 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.
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 Advanced Manufacturing (AM) program supports the fundamental research needed to revitalize American manufacturing to grow the national prosperity and workforce, and to reshape our strategic industries. The AM program accelerates advances in manufacturing technologies with emphasis on multidisciplinary research that fundamentally alters and transforms manufacturing capabilities, methods and practices. Advanced manufacturing research proposals should address issues related to national prosperity and security, and advancing knowledge to sustain global leadership. Areas of research, for example, include manufacturing systems; materials processing; manufacturing machines; methodologies; and manufacturing across the length scales. Researchers working in the areas of cybermanufacturing systems, manufacturing machines and equipment, materials engineering and processing, and nanomanufacturing are encouraged to transcend and cross domain boundaries. Interdisciplinary, convergent proposals are welcome that bring manufacturing to new application areas, and that incorporate challenges and approaches outside the customary manufacturing portfolio to broaden the impact of America's advanced manufacturing research. Proposals of all sizes will therefore be considered as justified by the project description. Investigators are encouraged to discuss their ideas with AM program directors well in advance of submission at AdvancedManufacturing@nsf.gov.
The Sloan and Ford Foundations would like to fund a set of research projects to further study these dynamics, with an eye toward better understanding the economics, maintenance and sustainability of digital infrastructure.
The goal of the Sensing, Learning, Autonomy, and Knowledge Engineering (SLAKE) program is to advance Air Force sensing capabilities by employing diverse sensor processing results at a representational or product level that is abstracted from the direct sensing output yet retains crucial information and corresponding uncertainties. Key research areas under SLAKE include development of sensor product representations suitable for efficient storage, efficient communication, and efficient resource allocation; robust conversion of sensor processing output to novel representation formats; accurate characterization of sensing uncertainties; rigorous incorporation of sensing uncertainties within novel algorithms for sensor resource management, task allocation, and information fusion; development and employment of virtual environments suitable for exercising specific algorithms and for analyzing specific system concepts; and sustained, efficient descriptions of mission context and mission operating environment. In support of technology maturation and transition, SLAKE also includes small unmanned aerial system (SUAS) integration and operation, advanced demonstration and validation.
The Cyberinfrastructure for Sustained Scientific Innovation (CSSI) umbrella program encompasses the long-running Data Infrastructure Building Blocks (DIBBs) and Software Infrastructure for Sustained Innovation (SI2) programs, as NSF seeks to enable funding opportunities that are flexible and responsive to the evolving and emerging needs in data and software cyberinfrastructure.
