This year’s primary election upsets in Alaska, Florida and Utah and the volatile Congressional campaigns currently underway — all of which take place amid widespread voter discontent and the rise of the Tea Party movement — illustrate the growing need for easily-accessible and easily-updated portals for political data and analysis.
Election-season data visualization is traditionally cast in the form of public opinion polling data delivered through the red/blue/purple national maps of state and district races. Although that is a useful shortcut to inform the classic horse-race electoral narrative, it leaves us hungry for context. Dividing the U.S. into blue and red states masks important trends and relationships, and the patterns within the binary electoral results remain opaque.
Recognizing the need to look at elections a different way, Patchwork Nation was born four years ago. Created from the inspiration of Dante Chinni and built into a living project in partnership with the PBS NewsHour and the Christian Science Monitor, it focuses on delivering more context while remaining visually intuitive for the reader. The Jefferson Institute is proud to have partnered with Patchwork Nation in their 2010 relaunch, which involved porting them to Drupal, adding a district layer to their already compelling map of U.S. counties, and deepening the delivery of data visualizations for individual counties and districts with the Knight News Challenge sponsored VIDI data visualization toolkit.
The site’s new back end is even more exciting. We’ve moved all the data series that Patchwork Nation uses to Drupal tables and designed an interface for administrators to build, post and embed maps, charts and graphs on the fly. All that visualization work was done in the past by the brilliant and overburdened IT staff of the NewsHour. Now, Chinni or any of his data-savvy colleagues can do it themselves, and the NewsHour’s IT staff can focus on more strategic challenges.
Patchwork Nation delivers a rare blend of data and analysis, simultaneously providing local, regional and national specificity. Geographically, it helps viewers understand how their community is similar to and different from their neighbors’ and others across the country. It places an emphasis on trend lines over snapshots, providing profiles of the electorate and voting history over time, complimented by analysis and anecdotal stories, and enriched with demographic and economic history to help readers understand the changing shape of the electorate itself.
In these days of shrinking newsroom IT budgets and increasing demand for journalistic data visualization, the project clearly demonstrates the advantages of directly empowering journalists with the tools to visualize the narratives within data.