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DDDAS: Dynamic Data Driven Applications Systems

Published on AidPage by IDILOGIC on Jun 24, 2005
Administered by:

National Science Foundation, Office of Budget, Finance and Award Management, Headquarters
(see all US Federal Agencies)

Explore all postings for this grant program:
  • Original Grant - Mar 11, 2005
Applications Due:

Jun 13, 2005

total funding: $15,000,000
max award: $2,000,000
min award: $50,000
cost sharing, matching: No
number of awards: 25
type of funding: Grant
Description:

Information technology-enabled applications/simulations of systems in science and engineering have become as essential to advances in these fields as theory and measurement. This triad of approaches is used by scientists and engineers to analyze the characteristics and predict the behavior of complex systems and the applications that represent them. However, accurate and comprehensive analysis and prediction of the behavior of complex systems over time is difficult. With traditional simulation and measurement approaches, even elaborate computational models of such systems produce applications and simulations that diverge from or fail to predict real system behaviors. This solicitation focuses explicitly on Dynamic Data Driven Applications Systems (DDDAS), a promising concept in which the computational and experimental measurement aspects of a computing
application are dynamically integrated, creating new capabilities in a wide range of science and engineering application areas. Computational aspects of DDDAS may be realized on a diverse set of computer platforms including computational grids, leadership-class supercomputers, mid-range clusters, distributed, high-throughput computing environments, high-end workstations, and sensor networks. Consequently, DDDAS-funded projects are expected to make significant contributions to research advances in computational science and engineering, high-end computing, measurement methods, and cyberinfrastructure. DDDAS is a paradigm whereby application/simulations and measurements become a symbiotic feedback control system. DDDAS entails the ability to dynamically incorporate additional data into an executing application, and in reverse, the ability of an application to dynamically steer the
measurement process. Such capabilities promise more accurate analysis and prediction, more precise controls, and more reliable outcomes. The ability of an application/simulation to control and guide the measurement process, and determine when, where and how it is best to gather additional data, has itself the potential of enabling more effective measurement methodologies. Furthermore, the incorporation of dynamic inputs into an executing application invokes new system modalities and helps create application software systems that can more accurately describe real-world complex systems. This enables the development of applications that adapt intelligently to evolving conditions, and that infer new knowledge in ways that are not predetermined by startup parameters. The need for such dynamic applications is already emerging in business, engineering and scientific processes, analysis, and
design. Manufacturing process controls, resource management, weather and climate prediction, traffic management, systems engineering, civil engineering, geo-exploration, social and behavioral modeling, cognitive measurement and bio-sensing are examples of areas likely to benefit from DDDAS. DDDAS creates a rich set of new challenges for applications, algorithms, systems’ software and measurement methods. The research scope described here requires strong, systematic collaborations between applications domain researchers and mathematics, statistics and computer sciences researchers, as well as researchers involved in the design and implementation of measurement methods and instruments. Consequently, most projects proposed in response to this solicitation are expected to involve teams of researchers. Following merit review of the proposals received, projects will be selected for
support by NSF, the National Institutes of Health (NIH) and the National Oceanic and Atmospheric Administration (NOAA).

Who can apply:

Unrestricted

Eligible functional categories:
Funding Sources:

Computer and Information Science and Engineering
Education and Human Resources
Engineering Grants
Mathematical and Physical Sciences
Social, Behavioral, and Economic Sciences

More Information:

NSF Publication 05-570

If you have problems accessing the full announcement, please contact: NSF Webmaster

Address Info:

National Science Foundation

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