Oceanhackweek: A Workshop to Explore Data Science in Oceanography; August 2019; Seattle, Washington

University Of Washington, Seattle WA

Investigators

Abstract

Oceanhackweek 2019 will be a 5-day intensive "learning hackathon", held during August 26-30, 2019 at the University of Washington. The hackathon provides an avenue for expediting the adoption of data science methodologies and computational tools for data-intensive research in the ocean sciences community. These skills are indispensable for modern-day oceanographers to tackle complex scientific questions by harnessing the data revolution. Oceanhackweek differs from traditional academic conferences and one-off hackathons by its immersive curriculum, collaborative learning environment, and a set of carefully crafted participant selection criteria that helps promote diversity and inclusivity. These designs help spurs collaborative interdisciplinary ideas and help ingest best data science practices into ocean sciences. The hackathon will focus on a variety of ocean data, including data from the Ocean Observing System, an ocean data facility supported by the National Science Foundation's Division of Ocean Sciences. Other databases that will be used include the CLIVAR and Carbon Hydrographic Data Office (CCHDO) and Rolling Deck to Repository (R2R) database. Oceanhackweek focuses not only on promoting data science literacy but also on building an inclusive and cohesive community of oceanographers for learning and sharing. The hackathon opportunity will be advertised nationally and internationally in traditional academic venues and via social media. Participants will be selected by an advisory committee that will seek to create a diverse community of ocean data users. The organizers plan to encourage and empower participants to bring the skills gained and the sense of community formed during the hackweek back to their own labs and institutions. Beyond the intensive in-person workshop, Oceanhackweek tutorials will be maintained as persistent open online resources to allow anyone to partake and self-learn. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.