Feb 19: The US Covid Atlas @ Computation + Journalism Symposium 2021

The US COVID Atlas project will be presenting insights and reflections on the recent development of the Atlas 2.0 at the Northeastern Computation + Journalism Symposium, Data Journalism in an Expanded Field. Details below!

Feb 19, 2021, Register Here
Speaker: Dylan Halpern, Principal Software Engineer

COVID-19 has dominated attention, media, and life around the world in 2020. At the start of the pandemic, intense interest sparked a variety of specialized data reporting and visualization dashboards, including the US Covid Atlas. The US COVID Atlas started in March 2020 and developed throughout the year as an analytics and visualization platform that aggregates and reports insights focused on geospatial and time-series findings with the unique contribution of hotspot analysis functions (spatial autocorrelation / LISA). As the year progressed, data quality and granularity improved and our ability to communicate the state of the crisis improved, opening new opportunities to tell the stories of COVID impact. For the US COVID Atlas, a viral social media post sparked new innovation on the visualization capacities of the site, and new visual and data features work to capture attention when COVID fatigue is ubiquitous.

This talk considers data visualization, curation, and storytelling in the evolution of the US COVID Atlas project led by University of Chicago’s Center for Spatial Data Science and lessons learned from user and community engagement processes. Additionally, this talk explores the capacities of the COVID Atlas as a remixable, free and open source toolkit that runs locally on the client browser while still delivering a variety of COVID metrics and variables, spatial autocorrelation capacities (LISA), and state-of-the art GPU based cartography. The flexibility of such data analytics tools reduce the need for server infrastructure or costs; also, this capacity means that more advanced geospatial insights can be delivered offline in the case of sensitive data.

%d bloggers like this: