Trial and Error in Data Viz at the ACLU

Visualizing data the “right” way requires many considerations — the topic, the quality of your data, your audience, your time frame, and the various channels of (sometimes conflicting) feedback you received.

Trial and Error in Data Viz at the ACLU

January 21, 2021

Visualizing data the “right” way requires many considerations — the topic, the quality of your data, your audience, your time frame, and the various channels of (sometimes conflicting) feedback you received. In this presentation, I’ll introduce some reflections on these considerations and ways I’ve incorporated feedback (or not) into my work as Data Journalist at the ACLU. Lastly, I’ll present some of the sillier trials and errors I’ve made that were arguably necessary to my process in creating effective data visualizations using R.

Additional Videos

Sophie Beiers, Nicholas Pylypiw, Dorris Scott, Pamela Pairo, and Michael Chirico Q&A


About the speaker

Sophie Beiers

Sophie Beiers works on the ACLU’s Analytics team as a Data Journalist where she analyzes and visualizes data for their lawyers’ legal arguments and for external advocacy pieces. Prior to her time at the ACLU, she received her master’s degree in Quantitative Methods in Social Sciences at Columbia University where she also TA’d at the Lede Program for Data Journalism. Before NYC, she kicked off her career in analytics in San Francisco at the education nonprofit “YouthTruth.” Sophie is a Bay Area native but currently lives in Portland, OR and enjoys running, hiking, and making pottery in her free time.