Community science and education with the Hackweek model
Scientific modeling can be very technical, and even more challenging to communicate towards a diverse audience. Yet, most researchers spend the bulk of their efforts resolving data access, data quality, and exploratory analyses. By collaborating with the UW eScience Institute, the hackweek and incubator models offers a boot-camp experience and the opportunity to apply data science skills towards interdisciplinary real-world problems. Participants gain exposure to open-source software for virtual computing environments, version control, and analytics with climate, geomorphology, and hydrometeorology case studies.
Geohackweek 2016
Geohackweek 2017
Waterhackweek 2018
Geohackweek 2016
Geohackweek 2017
Waterhackweek 2018
HydroShare
HydroShare is an online, open-source, collaborative Hydrologic Information System for data sharing and publishing hydrologic and spatially distributed datasets. Developed for a broad set of hydrologic data types, models, and code, hydrologic researchers can use HydroShare to collaborate seamlessly in a high performance computing environment. We conduct user experience surveys to improve this software and the modeling capacities with use-cases from participating hydrologic researchers, modelers, and educators.
Observed Gridded Hydrometeorology (OGH)
Due to advances in spatial interpolation methods, hydrometeorologic time-series data are now available at greater spatial resolution and time-intervals around the globe. However, the data sets are available in a number of data formats, are difficult to access, and the data are disconnected from their metadata. Observed Gridded Hydrometeorology (OGH) is a Python library that offers a host of functions to simplify spatial data wrangling with a pipeline for computing spatial-temporal scan statistics. Researchers who are interested in climate endpoints at the regional watershed scale can use OGH to access gridded meteorological data products, visualize temporal trends, and generate new data products from mathematical corrections to the long-term mean.
Hurricane Maria and Puerto Rico's Population Health
In 2017, Hurricane Maria devastated Puerto Rico, leaving the island in a prolonged state of emergency. Roads and electrical grids were destroyed, and millions of Puerto Rican residents remain without access to clean water resources, telecommunication, and limited hospital services. An alarming number of reports indicate that the population may have been exposed to contaminated water, both bacterial and chemical in nature. Health experts remain concerned that the ongoing water quality issues will heighten the risk of disease among Puerto Rican residents. Funded by an NSF RAPID grant, we are collaborating with Puerto Rican community and population health experts to use hydrologic information for prioritizing population health needs in a data-driven approach. This multi-institutional effort will also develop the infrastructure to integrating demographic information, population health trends, with a water-sampling campaign to consider regulated and unregulated contaminants of disease concern.
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