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Building research software infrastructure to prevent disasters like Hurricane Maria. NSF RAPID Researchers Meeting, Broomfield Colorado, July 11, 2018

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Christina Bandaragoda 1, Miguel Leon 2, Jimmy Phuong 3, Graciela Ramirez-Toro 4, Melitza Crespo Medina 4, Kelsey Pieper 5, William Rhoads 5, Tim Ferguson-Sauder 6, Jeffery S Horsburgh 7, Jerad Bales 8, Martin Seul 8, Emily Clark 8, Sean Mooney 3, Kari Stephens 3, Erkan Istanbulluoglu 1, Julia Hart 1, Marc Edwards 5, Amy Pruden 5, Virginia Riquelme 5, Ishi Keenum 5, Ben Davis 5, Matthew Blair 5, Greg House 5, David G Tarboton 7, Amber Spackman Jones 7, Eric Hutton 9,10,11, Gregory E Tucker 9,10,11, Lynn McCready 9, Scott Dale Peckham 11, W. Christopher Lenhardt 13, Ray Idaszak 13, William G McDowell 13 David Arctur 14

(1)University of Washington, Seattle, WA, United States, (2) University of Pennsylvania, Earth & Environmental Science, Philadelphia, PA (3) University of Washington Seattle Campus, Biomedical and Health Informatics, Seattle, WA, United States, (4) Center for Environmental Education Conservation and Research of Inter American University of Puerto Rico, (5) Virginia Tech, Blacksburg, VA, United States, (6) Olin College, Needham, MA (7) Utah State University, Logan, UT, (8) Consortium of Universities for the Advancement of Hydrological Science, Boston, MA (9) Community Surface Dynamics Modeling System, Boulder, CO, United States, (10) Cooperative Institute for Research in Environmental Sciences, Boulder, CO (11) University of Colorado, Boulder, CO, United States, (12) Renaissance Computing Institute, Chapel Hill, NC, United States, (13) University of New Hampshire. (14) University of Texas

Building research software infrastructure to prevent disasters like Hurricane Maria

After every natural disaster, it is difficult to answer elementary questions on how to provide high quality water supplies and health services. There is no existing digital infrastructure to scientifically determine the hurricane impact on drinking water quality, the severity of a hazard to human health, or baseline data on the sophistication, connectivity, and operations of the distributed physical and related digital infrastructure systems. We test data publication mechanisms after Hurricane Maria in Puerto Rico to understand risk to human health by (1) assessing the spatial and temporal presence of waterborne pathogens in multiple types of systems, (2) demonstrate usability of CUAHSI HydroShare as a clearinghouse for data related to Hurricane Maria, Harvey and Irma and (3) and develop a prototype cyberinfrastructure to assess environmental and public health impacts. Our resulting archive and research software engineering practices provide a prototype cyberinfrastructure system for researchers to study natural disasters.

How can data sharing and archiving capabilities be enhanced to ensure the greatest scientific impact?
Recovery efforts from natural disasters can be more efficient with data-driven information on current needs and future risks. We advance open-source software infrastructure to support scientific investigation and data-driven decision making with a data sharing system using a water quality assessment developed to investigate post-Hurricane Maria drinking water contamination in Puerto Rico. One limitation to effective disaster response is easy and rapid access to diverse information about available resources and maps of community resource needs and risks. Research products are made Findable, Accessible, Interoperable, and Reproducible (FAIR) using a collaborative, online sharing platform – HydroShare. Curating a central repository of assembled research data has the potential to greatly facilitate coordinated disaster responses of all types, with opportunities to improve planning, preparedness, and monitoring of the recovery process.

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Bandaragoda, C., M. Leon, J. Phuong (2018). Building research software infrastructure to prevent disasters like Hurricane Maria. NSF RAPID Researchers Meeting, Broomfield Colorado, July 11, 2018, HydroShare,

This resource is shared under the Creative Commons Attribution CC BY.


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