Lookable is a student-friendly, no-code web tool that turns a plain-English question about data into a properly cited chart using open data.

This 90-minute event will begin with a 10-minute mini-talk on the importance of fast, ethical visualization in student research, how AI apps should not steal data and should help users run algorithms client-side as a way to avoid this, and guidance on open-data sources and licensing. A 20-minute live demo will follow, showcasing the Lookable prototype and the steps to use it: 1/ “type a topic 2/ “see a chart” 3/ “see the source data” 4/ export and share 5/ apply filters, trend lines, and color-blind-safe palettes to the dataset through A. I chat. During a 45-minute hands-on lab, students will each create a chart based on any data inquiry they have in any discipline taught at the GC. This data will only be ethically scraped by the software from approved open sources, and respects robots.txt and other anti-scraping measures. The session will conclude with a 15-minute wrap that covers exporting PNG/SVG files for papers and slides, citing data correctly, and making this a repeatable workflow for evidence-based communication with source links, accessibility features with clear labels and time for a short question and answer session with the creator, Rohan Ramnarain, a current student in the M.S. in Data Analysis and Visualization program at the GC.

Time: 6:30 pm EST

Free!

Registration