Learning The Evolution of NPR’s Picture Stories
How NPR’s picture stories have changed—and the design principles and iterative work behind all the changes.
Learning Consider the Boolean
The challenge of using binary data structures in a complicated world.
Learning Understanding Households and Relationships in Census Data
The Census Bureau’s population counts make trends in household makeup easy to track. All you need are two things: an understanding of how the Census asks Americans about households and relationships, and where to find the right tables amid the haystack of tabulations. That’s what this post aims to help you with.
More case studies:
Jake Harris on data visualization, empathy, and representing people with dots
D’Vera Cohn on Everything You Ever Wanted to Know About Marriage Data But Were Afraid to Ask
Jeremy Merrill and Ken Schwencke explore the fine art of anticipating and catching errors while wrangling the eccentricities of US elections data.
Michael Maciag‘s walk-through of this under-utilized goldmine.
Emily Alpert Reyes on how to find promising needles in Census haystacks.
Jake Harris reverse-engineers Twee-Q to evaluate its use of data (and see if his ratio is as disappointing as Twee-Q says it is)
Jonathan Stray on how to protect yourself, your sources, and your scoop on sensitive stories
Jonathan Stray on what every single person in your news org should be doing to secure the newsroom.
Matt Waite thinks epistemology (and a little fake software) could save journalism—here’s why.
Zoe Fraade-Blanar on why and how good interaction design thinks about users.
Ronald Campbell on using census data to find facts in a world of speculation
Melody Kramer on how a user-centered design process and attention to newsroom culture can make or break your internal tools.
Jacob Harris on six ways to make mistakes with data—and how to avoid them.
Sarah Slobin discovers that all the facts and numbers didn’t add up to the humans in her story.
Paul Overberg explains base tables and how to get the best data from them (hint: ask good questions!).