Happy Friday, everyone. I prefer to travel via Amtrak and intercity rail, but from my flat I can see two routes of the US interstate highway system: I-676 and I-76. And when I drive to my hometown outside Philadelphia, I use those two routes. Plus, I live not far from I-95, the main highway corridor running through the East Coast of the United States.
But what a lot of people do not know is that the numbering system for US interstate highways—by and large—has an underlying principle. (I say by and large because I frequently drive on one of the most infamous exceptions.) Thankfully, the YouTuber CCP Grey just released a video that details the numbering system.
The north-to-south routes
And if you’re curious about that exception, which runs through Altoona, Pennsylvania, here’s a screenshot. But you should watch the full video.
Here’s an interesting post from FiveThirtyEight. The article explores where different states have spent their pandemic relief funding from the federal government. The nearly $2 trillion dollar relief included a $350 billion block grant given to the states, to do with as they saw fit. After all, every state has different needs and priorities. Huzzah for federalism. But where has that money been going?
Enter the bubbles.
I mean bubbles need water distribution systems, right?
This decision to use a bubble chart fascinates me. We know that people are not great at differentiating between area. That’s why bars, dots, and lines remain the most effective form of visually communicating differences in quantities. And as with the piece we looked at on Monday, we don’t have a legend that informs us how big the circles are relative to the dollar values they represent.
And I mention that part because what I often find is that with these types of charts, designers simply say the width of the circle represents, in this case, the dollar value. But the problem is we don’t see just the diameter of the circle, we actually see the area. And if you recall your basic maths, the area of a circle = πr2. In other words, the designer is showing you far more than the value you want to see and it distorts the relationship. I am not saying that is what is happening here, but that’s because we do not have a legend to confirm that for us.
This sort of piece would also be helped by limited duty interactivity. Because, as a Pennsylvanian, I am curious to see where the Commonwealth is choosing to spend its share of the relief funds. But there is no way at present to dive into the data. Of course, if Pennsylvania is not part of the overall story—and it’s not—than an inline graphic need not show the Keystone State. In these kinds of stories, however, I often enjoy an interactive piece at the end wherein I can explore the breadth and depth of the data.
So if we accept that a larger interactive piece is off the table, could the graphic have been redesigned to show more of the state level data with more labelling? A tree map would be an improvement over the bubbles because scaling to length and height is easier than a circle, but still presents the area problem. What a tree map allows is inherent grouping, so one could group by either spending category or by state.
I would bet that a smart series of bar charts could work really well here. It would require some clever grouping and probably colouring, but a well structured set of bars could capture both the states and categories and could be grouped by either.
Overall a fascinating idea, but I’m left just wanting a little more from the execution.
The National Oceanic and Atmospheric Administration (NOAA) released its 2022 report, Sea Level Rise Technical Report, that details projected changes to sea level over the next 30 years. Spoiler alert: it’s not good news for the coasts. In essence the sea level rise we’ve seen over the past 100 years, about a foot on average, we will witness in just thirty years to 2050.
Now I’ve spent a good chunk of my life “down the shore” as we say in the Philadelphia dialect and those shore towns will all have a special place in my life. But that looks more to be like a cherished memory fading into time. I took a screenshot of the Philadelphia region and South Jersey in particular.
Not just the Shore, but also the Beaches
To be fair, that big blob of blue is Delaware Bay. That’s already the inlet to the Atlantic. But the parts that ought to disturb people are just how much blue snakes into New Jersey and Delaware, how much/little space there is between those very small ribbons of land land off the Jersey coast.
You can also see little blue dots. When the user clicks on those, the application presents the user with a small interactive popup that models sea level rise on a representative photograph. In this case, the dot nearest to my heart is that of the Avalon Dunes, with which I’m very familiar. As the sea level rises, more and more of the street behind protected by the dunes disappears.
My only real issue with the application is how long it takes to load and refresh the images every single time you adjust the zoom or change your focus. I had a number of additional screenshots I wanted to take, but frankly the application was taking too long to load the data. That could be down to a million things, true, but it frustrated me nonetheless.
Regardless of my frustration, I do highly recommend you check out the application, especially if you have any connection to the coast.
Today we have an interesting little post, a choropleth map in a BBC article examining the changes occurring in the voting systems throughout the United States. Broadly speaking, we see two trends in the American political system when it comes to voting: make it easier because democracy; make it more restrictive because voter fraud/illegitimacy. The underlying issue, however, is that we have not seen any evidence of widespread or concerted efforts of voter fraud or problems with elections.
Think mail-in ballots are problematic? They’ve been used for decades without issues in many states. That doesn’t mean a new state could screw up the implementation of mail-in voting, but it’s a proven safe and valid system for elections.
Think that were issues of fraudulent voters? We had something like sixty cases brought before the courts and I believe in only one or two instances were the issues even remotely proven. The article cites some Associated Press (AP) reporting that identified only 500 cases of fraudulent votes. Out of over 14 million votes cast.
500 out of 14,000,000.
Anyway, the map in the article colours states by whether they have passed expansive or restrictive changes to voting. Naturally there are categories for no changes as well as when some expansive changes and some restrictive changes were both passed.
Normally I would expect to see a third colour for the overlap. Imagine we had red and blue, a blend of those colours like purple would often be a designer’s choice. Here, however, we have a hatched pattern with alternating stripes of orange and blue. You don’t see this done very often, and so I just wanted to highlight it.
I don’t know if this marks a new stylistic design direction by the BBC graphics department. Here I don’t necessarily love the pattern itself, the colours make it difficult to read the text—though the designers outlined said text, so points for that.
But I’ll be curious to see if I, well, see more of this in coming weeks and months.
Credit for the piece goes to the BBC graphics department.
We’re starting this week with an article from the Philadelphia Inquirer. It looks at the increasing number of guns confiscated by the Transportation Security Administration (TSA) at Philadelphia International Airport. Now while this is a problem we could discuss, one of the graphics therein has a problem that we’ll discuss here.
We have a pretty standard bar chart here, with the number of guns “detected” at all US airports from 2008 through 2021. The previous year is highlighted with a darker shade of blue. But what’s missing?
We have two light grey lines running across the graphic. But what do they represent? We do have the individual data points labelled above each bar, and that gives us a clue that the grey lines are axis lines, specifically representing 2,000 and 4,000 guns, because they run between the bars straddling those two lines.
However, we also have the data labels themselves. I wonder, however, are they even necessary? If we look at the amount of space taken up by the labels, we can imagine that three labels, 2k, 4k, and 6k, would use significantly less visual real estate than the individual labels. The data contained in the labels could be relegated to a mouseover state, revealed only when the user interacts directly with the graphic. Here it serves as a “sparkle”, distracting from the visual relationships of the bars.
If the actual data values to the single digit are important, a table would be a better format for displaying the information. A chart should show the visual relationship. Now, perhaps the Inquirer decided to display data labels and no axis for all charts. I may disagree with that, but it’s a house data visualisation stylistic choice.
But then we have the above screenshot. In this bar chart, we have something similar. Bars represent the number of guns detected specifically at Philadelphia International Airport, although the time framer is narrower being only 2017–2021. We do have grey lines in the background, but now on the left of the chart, we have numbers. Here we do have axis labels displaying 10, 20, and 30. Interestingly, the maximum value in the data set is 39 guns detected last year, but the chart does not include an axis line at 40 guns, which would make sense given the increments used.
At the end of the day, this is just a frustrating series of graphics. Whilst I do not understand the use of the data labels, the inconsistency with the data labels within one article is maddening.
Well it’s Friday. Congratulations on making it to the weekend. I often spend my weekends working on personal projects, because I have goals and things I’m trying to do. In other words, I have ambitions. That’s why this piece from Indexed was so funny. One cannot go wrong with a Venn diagram.
Earlier this week marked the 70th anniversary of Queen Elizabeth’s accession to the throne of the United Kingdom and many Commonwealth realms. There are many graphics about the length of her reign and the numerous prime ministers and presidents she has met over the years. But I actually enjoyed this article from the BBC as it dovetails nicely with my interest in genealogy, which frequently looks at the same sort of materials.
In genealogy we often want to find photos, illustrations, or really any kind of documentation that ties an ancestor to a particular place at a particular time. What I never realised is that the birthplace of Her Majesty, the Queen, no longer exists.
It kind of makes sense, however, when you consider that as the daughter of the younger son she was never expected to take the throne. When her uncle abdicated, however, her father took the throne and then she became next in line and we all know the rest. But because of that lack of expectation her birthplace was just another London townhome. The article details how development changed the location, not the Blitz as is often thought.
You can see from the screenshot above how the article uses a slider device to compare the neighbourhood in London today vs. what it was in 1895, about 30 years before the Queen’s birth.
At this point we’re all familiar with sliders, but they do work really well when it comes to this kind of before-after comparison.
Credit for the piece goes to the BBC graphics department.
Just a quick little piece today, a neat illustration from the BBC that shows how the process of nuclear fusion works. The graphic supports an article detailing a significant breakthrough in the development of nuclear fusion. Long story short, a smaller sort-of prototype successfully proved the design underpinning a much larger fusion reactor currently under construction in France. We are potentially on our way to proving the viability of nuclear fusion as an energy source.
Why is that important? Well, first of all, no carbon emissions. Nuclear fusion powers the Sun, where hydrogen is fused with hydrogen to produce helium and in the process release an enormous amount of energy. Mankind wants to take that energy and use it to heat water to generate steam to spin turbines to create electricity.
And we use a lot of electricity.
So how does fusion work?
The BBC graphic shows how. This is a bit simplified, even for my tastes, but it’s generally pretty good. For example, I probably would have labelled protons and neutrons earlier (to the left) of the graphic. And my big question mark is about the widths of the arrows, because if the width of the arrows relates to the scale of the energy, as that is the crux of the matter. (See what I did there?)
Basically when we want to generate energy we want to add as little as possible to start a reaction to net as much output as possible. A little bit of energy is used to split a uranium isotope and that generates a tremendous amount of energy. Thus far with nuclear fusion, however, we use a lot of energy to fuse hydrogen into helium and get little back as output. In other words, a net loss.
The graphic omits how this reactor in the UK works, by using a doughnut-shaped vessel to contain the hydrogen reaction. To do this they use superconducting magnets to generate powerful electromagnetic fields. This contains the hydrogen that turns into a superheated plasma. After all, it’s not like there are any materials known to man that can safely contain the temperatures of the Sun. But we have evidence that as the amount of plasma scale up, the closer we get to breaking even. And that’s the goal for the French reactor.
The other big question in the room is how this helps us with climate change, because as I stated up top, no carbon emissions. Unfortunately, not much. The French reactor is still several years away from being complete. And if that works as expected, commercial-scale reactors powering electricity generation stations are many more years away. Fusion will help power us into the 22nd century. And so we will still need nuclear fission and renewables to get us through the 21st.
Credit for the piece goes to the BBC graphics department.
This is an older piece that I stumbled across doing some other work. I felt like it needed sharing. The interactive graphic shows the high and low note vocal ranges of major musical artists.
Good to see some of my favourite artists in the mix.
Interactive controls allow the user to sort the bars by the greatest vocal range, high notes, or low notes. Colour coding distinguishes male from female vocalists.
In particular I enjoy the bottom of the piece that uses the keyboard to show the range of notes. When the user mouses over a particular singer, the ends of the range display the particular song in which the singer hit the note.
Again, this is an older piece that I just discovered, but I did enjoy it. I would be curious to see how these things could change over time. As an artist ages, how does that change his or her vocal range? Are there differences between albums? This could be a fascinating point at which branching out for further research could be done.
Today is just a quick little follow-up to my post from Monday. There I talked about how a Boston Globe piece using three-dimensional columns to show snowfall amounts in last weekend’s blizzard failed to clearly communicate the data. Then I showed a map from the National Weather Service (NWS) that showed the snowfall ranges over an entire area.
Well scrolling through the weather feeds on the Twitter yesterday I saw this graphic from the NWS that comes closer to the Globe‘s original intent, but again offers a far clearer view of the data.
Much better
Whilst we miss individual reports being depicted as exact, that is to say the reports are grouped into bins and assigned a colour, we have a much more granular view than we did with the first NWS graphic I shared.
The only comment I have on this graphic is that I would probably drop the terrain element of the map. The dots work well when placed atop the white map, but the lighter blues and yellows fade out of view when placed atop the green.
But overall, this is a much clearer view of the storm’s snowfall.
Credit for the piece goes to the National Weather Service graphics department.
