2020 ESA Annual Meeting (August 3 - 6)

PS 48 Abstract - Using CUAHSI’s data services to facilitate interdisciplinary collaboration and dissemination of aquatic sciences data

Julia Masterman and Jerard Bales, Consortium of Universities for the Advancement of Hydrologic Science, Inc., Cambridge, MA
Background/Question/Methods

The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) supports a variety of mechanisms for engaging the aquatic sciences and broader earth science community. We will offer two examples of the use of CUAHSI’s services: (1) for education in the classroom and (2) for compilation of large data sets of disparate but related data.

Results/Conclusions

CUAHSI’s data services can be used to teach basic concepts of hydrology. Data can be discovered in the Hydrologic Information System (HIS) and in HydroShare (HS). These repositories offer (1) the capacity to retrieve data from multiple data providers simultaneously in a common format (HIS); (2) the ability to discover and retrieve hard to find project-specific data that are not available in typical data systems; and (3) application of pre-packaged teaching modules. Moreover, users can formally publish data sets and obtain an immutable digital object identifier. Data published in the HIS or HS are more likely to be discovered and used by aquatic scientists and professionals than data published in a larger, non-discipline specific data archive, and can more easily applied to collaborative research, and education activities.

HydroShare provides users working on large projects with the ability to compile and share disparate but related data with groups and communities. A group, for example, might be collaborators working on a specific project or in a specific location. A community, then, could be a set of related projects or sites. As an example, CUAHSI recently archived all data from the ten U.S. Critical Zone Observatories, discoverable by observatory or across all observatories. A second example is a comprehensive hydrologic data set compiled for Hurricane Harvey, in which observed water levels, river and stream flows, impacted structures, forecasts and model simulations, and other information from multiple sources were compiled into a single, readily discoverable data set.