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US-Japan Big Data and Disaster Research (BDD)

Status: Archived

Archived funding opportunity

This document has been archived.

Important information about NSF’s implementation of the revised 2 CFR

NSF Financial Assistance awards (grants and cooperative agreements) made on or after October 1, 2024, will be subject to the applicable set of award conditions, dated October 1, 2024, available on the NSF website. These terms and conditions are consistent with the revised guidance specified in the OMB Guidance for Federal Financial Assistance published in the Federal Register on April 22, 2024.

Important information for proposers

All proposals must be submitted in accordance with the requirements specified in this funding opportunity and in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. It is the responsibility of the proposer to ensure that the proposal meets these requirements. Submitting a proposal prior to a specified deadline does not negate this requirement.

Synopsis

The US National Science Foundation (NSF) and the Japan Science and Technology Agency (JST) are embarking upon a collaborative research program to address compelling research challenges that arise from leveraging Big Data approaches to transform, at both human and societal scales, disaster management.

Several recent reports have documented how transformative improvements in disaster management will require systems approaches to analyze large, noisy, and heterogeneous data and facilitate timely decision making in the face of shifting demands (Computing for Disasters, http://www.cra.org/ccc/files/docs/init/computingfordisasters.pdf; Big Data and Disaster Management, https://grait-dm.gatech.edu/wp-content/uploads/2014/03/BigDataAndDisaster-v34.pdf).

Specifically, disaster events and responses result in non-linear behaviors, and there exist large and unique interdependences among variables, multiple concurrent temporal and spatial scales, and few single optimal solutions. The resultant complexity causes algorithmic and data complexity, as well as challenges that arise in modeling chaotic systems. Other sources of complexity include the need for maintaining data security and privacy, as well as the resilience of the underlying computing and communications infrastructure during and following a disaster event.

At the same time, rapid advances in technology are enabling new opportunities for addressing disaster management. For example, new computer systems and networks – namely smartphones, tablets, and other types of edge devices; embedded and hybrid systems spanning automobiles, aircraft, chemical processing plants, and electrical power grids, etc.; sensor networks; and next-generation networking technologies spanning wireless, mobile, and cellular networks – are giving rise to potentially powerful data streams requiring novel analytics capabilities to facilitate timely and effective actions, as well as open questions about the resilience of these systems in the face of disasters.

This joint NSF/JST solicitation aims to address two specific challenges in the context of leveraging technological advances and using Big Data approaches to support effective disaster management:

  1. Capturing and processing the data associated with disasters to advance capabilities for disaster modeling as well as situational analysis and response modeling; and
  2. Improving the resilience and responsiveness of emerging computer systems and networks to facilitate the real-time data sensing, visualization, analysis, experimentation and prediction that is critical for time-sensitive decision making.

This NSF solicitation parallels an equivalent JST solicitation (available at http://www.jst.go.jp/sicp/announce_usjoint_bdd.html). Proposals submitted under this solicitation must describe joint research with Japanese counterparts who are requesting funding separately under the JST solicitation.

Program contacts

Name Email Phone Organization
Phillip Regalia
Program Director, CCF
pregalia@nsf.gov (703) 292-8910 CISE/CCF
Sylvia Spengler
Program Director, IIS
sspengle@nsf.gov (703) 292-8930 CISE/IIS
Min Song
Program Director, CNS
msong@nsf.gov (703) 292-8950

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