This program has been archived.
US-Japan Big Data and Disaster Research (BDD)
|Phillip Regaliafirstname.lastname@example.org||(703) 292-8910|
|Sylvia Spengleremail@example.com||(703) 292-8930|
|Min Songfirstname.lastname@example.org||(703) 292-8950|
Important Information for Proposers
A revised version of the NSF Proposal & Award Policies & Procedures Guide (PAPPG) (NSF 20-1), is effective for proposals submitted, or due, on or after June 1, 2020. Please be advised that, depending on the specified due date, the guidelines contained in NSF 20-1 may apply to proposals submitted in response to this funding opportunity.
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:
Capturing and processing the data associated with disasters to advance capabilities for disaster modeling as well as situational analysis and response modeling; and
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.