This data as JSON, CSV
||Data Science Training and Community Building through Hackweeks
||May 9 2019
||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.
||Crafting Data-Driven Stories for the Everyday Reader
||May 9 2019
||Journalists don’t write for other journalists—they write for the curious and community-minded public. In the same way, statistical journalism should not be a black box of visualizations and narrative meant only for data makers like us. Crafting data-driven stories for a general audience means giving readers an opportunity to interact with a fun and practical use case while explaining the interpretative thinking that lies under the hood of statistical methods. I am an undergraduate at Cal Poly that writes and builds interactive, data-driven publishings with a team of students. I'll walk you through how we ideate fascinating questions, make methods explainable, and use Jupyter Notebooks to share reproducible code.
||May 9 2019
||Daisy Bingham Room
||Datasette is a tool for instantly publishing structured data on the internet. It makes it easy to construct and execute arbitrary SQL queries (using SQLite) and export the results as CSV. It's accompanying tool csvs-to-sqlite makes it easy to convert CSV files into a SQLite database.
More info at https://github.com/simonw/datasette