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 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.

This workshop focuses on the presentation of preliminary data for the purpose of collaborative design that ensures the research products are delivered based on the preferences of future users. Participants answered the questions 1 ) What information about water do people need after a disaster? 2) How is information about water most effectively shared? 3) What are the difficulties faced when trying to communicate this type of information? Results were grouped to understand the information needs of academic water data researchers, federal drinking water regulators, local utilities (PRASA and community system operators, health researchers, and household data owners.

The National Science Foundation funded Collaborative RAPID: Building Infrastructure for Preventing Drinking Water Disasters project policies support data sharing mechanisms informed by federal and project guidelines. The workshop was hosted by Inter American University of Puerto Rico, Center for Environmental Education, Conservation and Research (CECIA-IAUPR) and the National Science Foundation Collaborative RAPID Project Team (NSF 1810647 ) . Participants include scientists and professionals from University of Puerto Rico San Juan, Region 2 Caribbean Environmental Protection Division (CEPD) Region 2 US EPA , Western Hemisphere Association of Sanitary and Environmental Engineers and Scientists, US Department of Health Potable Water Program, Puerto Rico Aqueduct and Sewer Authority (PRASA), and Patillas Community Water Systems.

Links to online data resources:
Hurricane Maria 2017 StoryMaps at https://arcg.is/00f1ij
Collaborative RAPID project Wiki: https://github.com/hydroshare/PuertoRicoWaterStudies/wiki
CUAHSI Community Project Landing page: https://www.cuahsi.org/projects/maria2017
HydroShare Puerto Rico Water Studies Group Resources: https://www.hydroshare.org/group/43
Collaborative RAPID Project Team: https://github.com/hydroshare/PuertoRicoWaterStudies/wiki/Collaborators

Workshop Outcomes:
1. User driven data priorities by scenario card sorting
2. Recruitment for Design Interviews for population health data
3. Collaborative Design for Information Distribution
4. RAPID project refined personas
5. Puerto Rico Water Studies Group collaborative authorship experiment (this resource)