I took two weeks off as work was pretty crazy, but we’re back to covering data visualisation and design with a graphic about trains. And anybody who knows me knows how I love trains. One of the early acts of the Biden administration was funding a proper expansion of rail service in the United States.
Last week the Washington Post published an article that explored some of the difficulties Amtrak, the national rail company, faces in that expansion. Most of it has to deal with the fact that outside the Northeast Amtrak largely uses rail lines owned by freight companies.
The article uses a map to show Amtrak routes and, in particular, where Amtrak wants to increase service or create new service.
As far as the map goes, it does a nice job needing not to reinvent the wheel. When an existing route will have expanded service, e.g. the Northeast Corridor, the blue line sits next to the dotted white line. What remains a bit unclear to me is the use of black text for Chicago, Atlanta, Dallas, and Los Angeles. The bold type for New Orleans and Mobile makes sense because of the story’s focus on that particular route. Chicago is mentioned once, but Dallas is not. So that is unclear.
But what really stood out to me was what happened when I re-read the story on my mobile. The graphic split from a full map to three narrow graphics, each featuring 1/3 of the United States. The designers moved the text labels so that they are fully visible in each graphic.
Overall, the piece does a great job at showing the map, but in particular it shines when it swaps out the large map for the smaller graphics on small screens. And the attention to detail in moving the text labels makes it all the better.
Last week the Washington Post published a nice long-form article about the troubles facing the Colorado River in the American and Mexican west. The Colorado is the river dammed by the Hoover and Glen Canyon Dams. It’s what flows through the Grand Canyon and provides water to the thirsty residents of the desert southwest.
But the river no longer reaches the ocean at the Gulf of California.
Why? Part drought, part population growth, and part economic activity. The article does a great job of exploring the issue and it does so through the occasional use of information graphics. This screenshot captures the storage capacity of the two main dams, Lake Mead and Lake Powell, created by the Hoover and Glen Canyon Dams, respectively. You may have heard of these recently because the water shortages presently affecting the region have brought reservoir levels to some of their lowest levels in years. And that means people have been finding all sorts of things.
But the graphic does a nice job of showing just how low things have gotten of late. Naturally I am curious what the data looks like on a longer timeline. Hoover Dam, of course, began during the administration of Herbert Hoover but was completed during the Franklin Roosevelt administration—who also renamed the dam as Boulder Dam though Congress reversed that change in 1947. Lake Powell came along three decades later and so the timelines would not be the exact same, but I am curious all the same.
The overall article makes sparse use of the graphics and they occupy much less space in the design than the numerous accompanying photographs. But the balance in terms of content works, I just would have preferred the charts and maps a bit larger.
Contrast this to what we explored last week in a New York Times piece, specifically the online version. There we saw graphics with no headers, data descriptors, axes labels, &c. Here we see the Washington Post was able to create a captivating piece but treat the data and information—and the reader—with respect. There are fewer graphics in this piece, but the way they were handled puts this leaps and bounds above the online version we looked at last week.
Credit for the piece goes to a lot of people, but the graphics specifically to John Muyskens. The rest of the credits go to the author Karin Brulliard and then just copying and pasting from the page: Editing by Amanda Erickson and Olivier Laurent. Photography by Matt McClain. Video by Erin Patrick O’Connor and Jesús Salazar. Video editing by Jesse Mesner-Hage and Zoeann Murphy. Graphics by John Muyskens. Graphics editing by Monica Ulmanu. Design and development by Leo Dominguez. Design editing by Matthew Callahan and Joe Moore. Copy editing by Susan Stanford. Additional editing by Ann Gerhart.
As Russia redeploys its forces in and around Ukraine, you can expect to hear more about how they are attempting to reconstitute their battalion tactical groups. But what exactly is a battalion tactical group?
Recently in Russia, the army has been reorganised increasingly away from regiments and divisions and towards smaller, more integrated units that theoretically can operate more independently: battalion tactical groups. They typically comprise less than a thousand soldiers, about 200 of which are infantry. But they also include a number of tanks, infantry fighting vehicles (IFVs), armoured personnel carriers (APCs), artillery, and other support units.
In an article from two weeks ago, the Washington Post explained why the Russian army had stalled out in Ukraine. And as part of that, they explained what a battalion tactical group is with a nice illustration.
Russia’s problem is that in the first month of the war, Ukrainian anti-armour weapons like US-made Javelins and UK-made NLAWs have ripped apart Russian tanks, IFVs, and APCs. Atop that, Ukrainian drones and artillery took out more armour. The units that Russia withdrew from Ukraine now have to be rebuilt and resupplied. Once fresh, Russia can deploy these into the Donbas and southern Ukraine.
This graphic isn’t terribly complicated, but the nice illustrations go a long way to showing what comprises a battalion tactical group. And when you see photos of five or six tanks destroyed along the side of a Ukrainian road, you now understand that constitutes half of a typical unit’s available armour. In other words, a big deal.
I expect to hear more out of Russia and Ukraine in coming days about how Russia is providing new vehicles and fresh soldiers to resupply exhausted units.
Credit for the piece goes to Bonnie Berkowitz and Artur Galocha.
Taking a break from going through the old articles and things I’ve saved, let’s turn to a an article from the Washington Post published earlier this week. As the title indicates, the Post’s article explores slaveholders in Congress. Many of us know that the vast majority of antebellum presidents at one point or another owned slaves. (Washington and Jefferson being the two most commonly cited in recent years.) But what about the other branches of government?
The article is a fascinating read about the prevalence of slaveholders in the legislative branch. For our purposes it uses a series of bar charts and maps to illustrate its point. Now, the piece isn’t truly interactive as it’s more of the scrolling narrative, but at several points in American history the article pauses to show the number of slaveholders in office during a particular Congress. The screenshot below is from the 1807 Congress.
That year is an interesting choice, not mentioned explicitly in the article, because the United States Constitution prohibited Congress from passing limits on the slave trade prior to 1808. But in 1807 Congress passed a law that banned the slave trade from 1 January 1808, the first day legally permitted by the Constitution.
Graphic-wise, we have a set of bar charts representing the percentage and then a choropleth map showing each state’s number of slaveholders in Congress. As we will see in a moment, the map here is a bit too small to work. Can you really see Delaware, Rhode Island, and (to a lesser extent) New Jersey? Additionally, because of the continuous gradient it can be difficult to distinguish just how many slaveholders were present in each state. I wonder if a series of bins would have been more effective.
The decision to use actual numbers intrigues me as well. Ohio, for example, has few slaveholders in Congress based upon the map. But as a newly organised state, Ohio had only two senators and one congressman. That’s a small actual, but 33% of its congressional delegation.
Overall though, the general pervasiveness of slaveholders warrants the use of a map to show geographic distribution was not limited to just the south.
Later on we have what I think is the best graphic of the article, a box map showing each state’s slaveholders over time.
Within each state we can see the general trend, including the legacy of the Civil War and Reconstruction. The use of a light background allows white to represent pre-statehood periods for each state. And of course some states, notably Alaska and Hawaii, joined the United States well after this period.
But I also want to address one potential issue with the methodology of the article. One that it does briefly address, albeit tangentially. This data set looks at all people who at one point or another in their life held slaves. First, contextually, in the early years of the republic slavery was not uncommon throughout the world. Though by the aforementioned year of 1807 the institution appeared on its way out in the West. Sadly the cotton gin revolutionised the South’s cotton industry and reinvigorated the economic impetus for slavery. There after slavery boomed. The banning of the slave trade shortly thereafter introduced scarcity into the slave market and then the South’s “peculiar institution” truly took root. That cotton boom may well explain how the initial decline in the prevalence of slaveholders in the first few Congresses reversed itself and then held steady through the early decades of the 19th century.
And that initial decline before a hardening of support for slavery is what I want to address. The data here looks only at people who at one point in their life held slaves. It’s not an accurate representation of current slaveholders in Congress at the time they served. It’s a subtle but important distinction. The most obvious result of this is how after the 1860s the graphics show members of Congress as slaveholders when this was not the case. They had in the past held slaves.
That is not to say that some of those members were reluctant and, in all likelihood, would have preferred to have kept their slaves. And therefore those numbers are important to understand. But it undermines the count of people who eventually came to realise the error of their ways. The article addresses this briefly, recounting several anecdotes of people who later in life became abolitionists. I wonder though whether these people should count in this graphic as—so far as we can tell—their personal views changed so substantially to be hardened against slavery.
I would be very curious to see these charts remade with a data set that accounts for contemporary ownership of slaves represented in Congress.
Regardless of the methodology issue, this is still a fascinating and important read.
Credit for the piece goes to Adrian Blanco, Leo Dominguez, and Julie Zuazmer Weil.
Last month the Washington Post published a nice article that detailed the deep water cooling system that the city of Toronto, Canada uses to keep itself cool. For the unfamiliar, deep water cooling at its simplest means sucking up very cold water from the bottom of a lake or ocean or wherever you can get very cold water, and then pumping that inland to absorb heat before cycling it back.
Of course, for the longer explanation—and what makes Toronto’s system different—you should read the article. And for our purposes it includes some nice illustrations that diagram just how that system works. The screenshot below captures the basic process I just described, but there are additional illustrations that do a great job showing just how the system works.
What I particularly enjoy about this style is how the illustrations of the building and similar are minimal and restrained. This allows the diagrammatic elements to come to the forefront, which is important to make the system understood.
If you didn’t know, climate change is real and it threatens much of our current way of life. I don’t go so far as to say it threatens the extinction of mankind, because there are nearly seven billion of us and to wipe out every living soul would be a tall order. But, it could wipe out parts of our history.
If you didn’t know, the city of Washington in the District of Columbia was built on a swamp. Except, actually, it wasn’t. Most of the city was built on higher ground along the riverbank of the Potomac. True, there are low-lying areas affected by the tides and high water, such as the National Mall, but places like the Capitol were purposefully placed on high ground.
And that gets us to this article in the Washington Post. It takes a look at the impact of rising waters and flash flooding on the National Mall, home to some of the preeminent American museums. The article uses a map to show just how the museums are threatened by extreme weather events that will only increase in frequency as climate change ramps up.
The designer used colour to denote museums by their risk of flooding, and sadly there are several. But as the article describes, there are few short-term fixes that we can undertake to mitigate the risk of damage to the collections.
I’ve been searching to see if I could find a better motion graphic of this, alas not. I saw a post on Instagram from the Washington Post that featured a timelapse video or graphic of the spread of the Caldor Wildfire. The Caldor Wildfire presently rages southwest of Lake Tahoe and has now forced the evacuation of South Lake Tahoe, a city of more than 20,000 people.
The motion graphic just does a nice job of simply capturing the spread, in both direction and speed, of the wildfire. Obviously, the whole area could use the inches of rain that Hurricane Ida is dumping on the eastern half of the country.
Credit for the piece goes to the Washington Post graphics department.
We can move from the microscopic things that will kill us to the very big things that will kill us. Nuclear missiles.
Because satellite photography from late June indicated that China is presently building over 100 ICBM silos in its western deserts. China has long had nuclear weapons, but has also long kept its arsenal small, compared to the two nuclear behemoths: the United States and the Soviet Union/Russia. But you don’t begin building over 119 missile silos unless you intend to build ICBMs.
To be clear, this doesn’t mean that China will build 119 missiles. More than likely it’ll be a very expensive and potentially deadly shell game. How many missiles are underneath the silo covers? Can you keep track of them? But even if China builds a fraction of 100, modern ICBMs come with multiple independent reentry vehicles (MIRVs) that allow a single missile to target several cities independently.
We also know that China has been building shorter and more intermediate range ICBMs. But some of those are thought to be equipped with conventional warheads, designed to target and sink American supercarriers in the Pacific. The goal to deny American sea and airpower effective bases to defend Taiwan or other allies in the South China Sea.
We know about this most recent buildup because of a Washington Post article that used satellite photography to pinpoint those new silos.
Of course this isn’t news to the defence and intelligence agencies. For sometime now they’ve been warning of China’s build-out of its military capacities. The question will be is how does the United States and her allies respond?
Credit for the piece goes to Planet/Center for Nonproliferation Studies.
One trend people have begun to follow lately is that of rising prices for consumer goods. If you have shopped recently for things, you may have noticed that you have been paying more than you were just a few weeks ago. We call this inflation. The Bureau of Labour Statistics (BLS) tracks this for a whole range of goods. We call the the consumer price index (CPI)
Prices can vary wildly for some goods, most notably food and energy. For those of my readers who drive, recall how quickly petrol/gasoline prices can change. Because of that volatility, the Bureau of Labour Statistics strips out food and energy prices and the inflation that excludes food and energy is what we call Core CPI.
Lately, we have been seeing an increase in prices and inflation is on the rise. To an extent, this is not surprising. The pandemic disrupted supply chains and wiped out supplies and stores of goods. But with many people working remotely, many now have pent up savings they want to spend. But with low supply and high demand, basic economics suggests rising prices. As supplies increase in the coming months, however, the rise in prices will begin to cool off. In other words, most economists are not yet concerned and expect this spike in inflation to be passing in nature. But not everyone agrees.
Last week, the Washington Post had an article examining the cause of inflation for a number of industries. To do so, it used some charts looking at prices over the past two years. This screenshot is from the used car section.
I want to focus on the design of this graphic, though, not the content. The designers’ goal appears to be contrasting the inflation over the last year to that of the last two years. Easy peasy. Red represents one-year inflation and blue two-year.
Typically when you see a chart that look like this, an area or filled line chart, the coloured area reflects the total value of the thing being measured. You can also use the colour to make positive/negative values clearer. In this case, neither of those things are happening.
Because the blue, for example, starts at the beginning of the time series and at the bottom of the chart, it looks like an enormous amount of consistent blue growth. And when the line runs into May 2020, we begin to see what appears as a stacked area chart, with the blue area increasing at the expense of the red.
Another way of reading it could be that the 29.7% and 29.3% increases equal the shaded areas, but that’s also problematic. If the shaded area locked to the baseline like you’ll see in a moment, I could maybe see that working, but at this point it just leaves me confused.
Now you can use the area fill to make it clear when a line dips above or below the baseline, in this case 0%. And I took that approach when I reimagined the chart as seen below.
What we do here is we set the bottom of the area fill to the baseline. Consequently, where the chart is filled above 0 we have positive inflation, and where it falls below the 0 line we have negative inflation, or deflation.
We need to note here that the text in the original article talks about the monthly change in inflation, e.g. that used car prices have increased by 7.3% last month. That, however, is not what the chart looks at. Instead, the chart shows the change yearly, in other words, prices now vs last May. To an extent, the 29.7% increase is not terribly surprising given how terrible the recession was.
Ultimately, I don’t see the value in the filled blue and red areas of the chart because I am left more confused. Does the reader need to see how far back one year and two years are from May 2021? Don’t the date labels do that sufficiently well?
This is just a weird article that left me scratching my head at the graphics. But read the text, it’s super informative about the content. I just wish a bit more work went into the graphics. There are some nice illustrations beginning each section, but I kind of feel that more time was spent on the illustrations than the charts.
Credit for the piece goes to Abha Bhattarai and Alyssa Fowers.
With the release of the 2020 US Census’ topline data, we can see which state populations increased and which few decreased. And in that we can sort, or resort, states by population. The Washington Post did this a few weeks ago with an interactive ranking chart in a nice online article. (I’d be curious what the print version was, alas I only receive the New York Times.)
The piece begins with a nice intro motion graphic that selects states and shows how their ranking among the other states (plus the District of Columbia, DC), has evolved since 1920.
After scrolling down briefly, the reader enters a portion of the story displayed by keeping the hero graphic static whilst blurbs of texts scroll over the lines. As the blurbs move past, different states or sets of states become highlighted to draw attention to them.
This works really well. When discussing the case of Iowa vis-a-vis the growth of California, Texas, and Florida, I don’t need to see the story of Nebraska. Especially as the end of the piece features this hero graphic as an interactive, explore-the-data piece of content. I don’t have a screenshot of that, because it’s really just the above two but with a dropdown selector and a legend.
As the user scrolls through the story, they move past the semi-motion graphic and into a text-driven narrative for each region of the United States. I’ve highlighted only the Northeast, where I was born, raised, and presently live. As an aside, I remember my family completing the 2000 Census around the kitchen table. The 2010 Census I filled out at a small desk not long after I moved into my second flat in Chicago. And this most recent one I completed whilst under quarantine here in Philadelphia.
This section of the article uses static images with the region’s constituent states highlighted. Again, this works really well, because when looking at the Northeast, I’m still not interested in Nebraska. And also again, we have the interactive explorer at the end of the article.
Overall this is a really strong piece from the Post. I have some quibbles with the design, primarily I don’t understand the function of the connecting lines’ fades and curves. But I find neither too terribly distracting from the content of the graphic.
Credit for the piece goes to Harry Stevens and Nick Kirkpatrick.