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Data Science Training and Community Building through Hackweeks

Parker, Micaela

Project leader(s)
Huppenkothen, Daniela

Informal training activities enable researchers at all levels to rapidly learn data science tools and best practices that fit their research questions and make significant advances in their work. In this talk, I will describe a highly successful informal training that has emerged in recent years called Hackweeks. These hackathon-style events place a strong focus on cultivating data science literacy, building a community of practice, and developing resources within an existing domain-specific community. By bringing together researchers from many different universities to address methods challenges within a research domain, Hackweeks take advantage of a shared language and shared scientific objectives. The Hackweek structure is designed to foster collaboration and learning among people from various stages of their career and technical abilities, and catalyze a community through a shared interest in solving computational challenges within a field (Huppenkothen et al, 2018). Hackweeks originally came out of the Astronomy community (Astro Hack Week, entering its 6th year in 2019) and the model has been successfully propagated to: neuroscience (Neurohackweek, now a 2-week NIH-funded program called Neurohackademy), geospatial sciences (Geohackweek), oceanography (Oceanhackweek), and more.

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