#SWDchallenge: think globally
It's hot, and I don't like it.
We recently hit the 101° F mark here in the Twin Cities, our hottest day in 10 years; that fact, PLUS the large handful of 90° days we also experienced before we even officially hit the first day of summer, is making me dread the next few months. (As I am a native New Englander who has voluntarily and enthusiastically relocated to Minnesota, you can probably guess which of the four seasons I prefer.)
Obviously, rising temperatures are not just a local anomaly. As reported by NOAA and the EPA, unusually hot summer days (and nights) have become more frequent in recent decades. Globally, this trend has been visualized most popularly by Ed Hawkins (based on a design by Ellie Highwood) in the famous "warming stripes" chart:
“Warming stripes,” created by Ed Hawkins and inspired by Ellie Highwood, have been seen across dozens of media outlets since its original publication in the 2010s.
This visualization is incredibly successful—historically so, in my estimation. It succeeds in leveraging a massive, global data set to create a simple, striking, and memorable image that conveys an unmistakeable takeaway. It does so at a glance, using our natural associations of color and temperature to augment the immediacy of our understanding. (I also am a fan of this XKCD visualization, which covers similar territory but in a very different and interactive format.)
While the topic of climate change is, to put it mildly, a real downer, there are other, more positive discussion areas of global relevance to cover—and other skilled communicators have created some outstanding visualizations to get their messages out.
In 2015, Tynan DeBold and Dov Friedman from the Wall Street Journal created heatmaps, using data from Project Tycho, to show how effectively 20th century vaccines have curtailed or even eradicated once-common, debilitating and deadly diseases in the U.S. Their article included interactive views for multiple diseases, in which the color of a square associated with a state and a year reflected the number of cases of that disease; the reference line denoting when a vaccine was introduced emphasized the dramatic decline in cases in subsequent years.
This Wall Street Journal heatmap showing the prevalance of measles in the U.S. before and after the introduction of the vaccine was created in 2015 by Tynan DeBold and Dov Friedman.
Hans Rosling, and the Swedish foundation he co-founded called Gapminder, are perhaps most famous for their animated bubble charts depicting the rise in life expectancy, population, and income across the world. In this video for the BBC, Rosling takes us through 200 years of these changes in just four minutes. Although we are seeing 120,000 data points, the presentation is so captivating that we focus not on the details, but on the big picture and the main takeaway: that for almost the entire world, things have been improving continuously and dramatically.
Synthesizing large-scale data—across long timeframes, geographic regions, or both—into an at-a-glance takeaway can be challenging. It can test not only our presentation skills, but our analytic acumen. How do we find the interesting insights in so much data? How do we edit our final view to be focused and compelling, without leaving too much context on the cutting room floor?
The challenge
Your challenge this month is to analyze any global data set, and create a visual that delivers a simple, memorable, and compelling message based on that data.
For the purposes of this exercise, "global" can mean:
worldwide at a country level;
worldwide with latitude/longitudinal data (for those of you who want to flex your GIS muscles);
states/provinces/territories within a country;
cities worldwide;
anything else that feels large in scope.
We're also hoping to see some aspect of change over time. Each of the examples we mentioned above takes on at least a century's worth of data. That isn't a minimum requirement for this challenge, but ideally you'd tackle something for which there's been a long enough length of time for some meaningful change to have taken place. You could opt to show "before" and "after" across a long time gap, or maybe you'd prefer to show year-by-year or decade-by-decade change. The specifics are up to you.
Upload your submission and commentary here by July 31 at 5PM Eastern.
Think globally, visualize simply—we are excited to see what you come up with!
Related resources
You are free to use any large-scale data sets that are openly available to share. Many research organizations, non-profits, and governmental bodies collect and share open data that could be a good fit for this project. Here are a few that you might find useful:
United Nations Sustainable Development Goals | More than three dozen different entities within the United Nations are actively supporting SDGs, and almost all of them have their own openly available data portal. Scroll down the linked page until you see the header "Key entities working to support Sustainable Development and Climate Action," where you'll be able to click through to each of those entities' web pages.
Project Tycho | The data source for the aforementioned vaccines article, this is a University of Pittsburgh-affiliated project with the goal of unlocking global health data for use by researchers, students, journalists, officials, and other interested individuals.
Gapminder | Led by the late Hans Rosling's wife and son, Gapminder "identifies systematic misconceptions about important global trends and proportions and uses reliable data to develop easy to understand teaching materials to rid people of their misconceptions."
Our World in Data | Part of the U.K.-based nonprofit Global Change Data Lab, OWID's mission is to publish the “research and data to make progress against the world’s largest problems”.
Data is Plural | While less specifically focused on big global problems, this collection of datasets curated by Jeremy Singer-Vine is a good place to find large-scale but unusual topics for investigation. Technically, "Data is Plural" is a weekly newsletter with five datasets per edition, but the entire repository is available online.
Given the theme this month, we expect (but certainly don't require!) to see a fair few maps among the submissions. If you plan to go down this route, our recent article "when should I use a map?" and the SWD podcast featuring Cartography author Kenneth Field could provide some useful guidance during your design process.
