The Data Journalism Podcast Data journalism in the face of ICE and subzero temperatures in MN
11 snips
Jan 29, 2026 MaryJo Webster, data editor at the Minnesota Star Tribune who leads a small data team, describes mobilizing for intense local crises. She talks about fast data work under pressure, scraping PACER and public records, keeping ready datasets for rapid reporting, and visualizing federal agent counts alongside local police to provide context.
AI Snips
Chapters
Transcript
Episode notes
Decide What To Publish Now
- Ask what you can safely say now, what needs more work, and what to defer for long-term reporting.
- Draw clear lines so breaking-data work stays accurate under time pressure.
Keep Ready Data For Context
- The Star Tribune maintains ready datasets like crime, crash, and death certificates to contextualize breaking events.
- Public and unique datasets let reporters rapidly check patterns and historical parallels.
Cross-Team Coordination Model
- The graphics and data teams share channels and planning meetings and appoint liaisons across desks.
- That coordination enabled rapid visualizations during the immigration surge story.