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.
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.
On Friday, I mentioned in brief that the East Coast was preparing for a storm. One of the cities the storm impacted was Boston and naturally the Boston Globecovered the story. One aspect the paper covered? The snowfall amounts. They did so like this:
All the lack of information
This graphic fails to communicate the breadth and literal depth of the snow. We have two big reasons for that and they are both tied to perspective.
First we have a simple one: bars hiding other bars. I live in Greater Centre City, Philadelphia. That means lots of tall buildings. But if I look out my window, the tall buildings nearer me block my view of the buildings behind. That same approach holds true in this graphic. The tall red columns in southeastern Massachusetts block those of eastern and northeastern parts of the state and parts of New Hampshire as well. Even if we can still see the tops of the columns, we cannot see the bases and thus any real meaningful comparison is lost.
Second: distance. Pretty simple here as well, later today go outside. Look at things on your horizon. Note that those things, while perhaps tall such as a tree or a skyscraper, look relatively small compared to those things immediately around you. Same applies here. Bars of the same data, when at opposite ends of the map, will appear sized differently. Below I took the above screenshot and highlighted two observations that differed in only 0.5 inches of snow. But the box I had to draw—a rough proxy for the columns’ actual heights—is 44% larger.
These bars should be about the same.
This map probably looks cool to some people with its three-dimensional perspective and bright colours on a dark grey map. But it fails where it matters most: clearly presenting the regional differences in accumulation of snowfall amounts.
Compare the above to this graphic from the Boston office of the National Weather Service (NWS).
No, it does not have the same cool factor. And some of the labelling design could use a bit of work. But the use of a flat, two-dimensional map allows us to more clearly compare the ranges of snowfall and get a truer sense of the geographic patterns in this weekend’s storm. And in doing so, we can see some of the subtleties, for example the red pockets of greater snowfall amounts amid the wider orange band.
Credit for the Globe piece goes to John Hancock.
Credit for the NWS piece goes to the graphics department of NWS Boston.
We’re going to start this week out with some good news and for that we turn to China. 30 years ago, child traffickers kidnapped four-year old Li Jingwei from his family and sold him to another family over 1,000 miles away. A BBC article from earlier this month covered Li Jingwei’s reunion with his family. How did it happen? Because of a map he drew and shared with the internet.
Here’s a screenshot of that map.
It’s missing a Starbucks though
We all create mental maps of our surroundings. And not surprisingly they grow larger as we get older. But this man’s ability to recall details of his family hometown allowed internet sleuths, and eventually the police, to identify the village. DNA tests then connected Li to a woman whose son had been abducted.
When we draw out these maps ourselves they become a link to the cartographic world. And that this man was able to use his own mental map to find his home. Well, like I said, we’re going to start the news off with some good news.
Those who know me know one of my pet peeves are when maps of the United States do not display Alaska and Hawaii. I even noted yesterday that those two states were so late of additions to the United States and it made sense as to why they were not included.
So when I was going through some old photos yesterday, I stumbled across this of a poster on the Philadelphia subway system. I had flagged it for posting, but I guess I never did.
Where are my 49th and 50th states at?
I understand this is an advert and so for creative purposes, creative liberty. And it could be that this service does not exist in either Alaska or Hawaii.
But, the statement here is that Metro covers 99% of the United States. Geographically, to do so Metro must cover Alaska because in terms of land area, Alaska comprises nearly 18% of the entire United States. Yeah, Alaska is big. Now, if you’re talking covering 99% of the people of the United States, Metro has some wiggle room. Combined, both Alaska and Hawaii comprise 0.6% of the United States population. That would still leave 0.4% of the American population not covered, and by definition that must be some part of the contiguous lower 48. But above we can see the whole map is purple.
In other words, this is not an accurate map. They should have found some way of incorporating Alaska and Hawaii.
Credit for the piece goes to Metro’s designer or design agency.
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.
Almost half of Congress in the early years had, at one point or another, owned slaves.
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.
How the trends changed over time over geography.
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.
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.
Note the Capitol and the White House will both be fine.
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.
When I was in the Berkshires, one thing I noticed was signs about bears. Bear crossing. Don’t feed the bears. Be beary careful. Okay, not so much the latter. But it was nonetheless odd to a city dweller like myself where I just need to be wary of giant rats.
Less than a month later, I read an article in the Boston Globe about how the black bear population in Massachusetts is expanding from the western and central portions of the state to those in the east.
The graphic in the article actually comes from the Massachusetts Division of Fisheries and Wildlife, so credit goes to them, but it shows the existing range and the black bears’ new range.
I understand the inclusion of the highways in red, green, and black, but I wish they had some even simple labelling. In the article they mention a few highways, but my familiarity with the highway system in Massachusetts is not great. Also, because the designer used thin black lines to demarcate the towns, one could think that the black lines, especially out west, represent counties or other larger political geography units.
Credit for the piece goes to the Massachusetts Division of Fisheries and Wildlife.
Housekeeping first, as you may have noticed, I haven’t been publishing as much lately. That’s because I’ve been on holiday. After a tremendously busy year, I need to use up all the time I didn’t spend on holiday. Consequently, I’m only going to be posting a handful or so more times before the end of the year. The plan is to return in early January to my regular posting schedule. For this week that means the next few days before I’m off for American Thanksgiving.
But on with the show.
One of the things I haven’t been doing too much of is travelling. There are many reasons for this, but one is that air travel in the United States has, of late, been, shall we say unreliable. Hundreds if not thousands of flight cancellations, sometimes with no obvious cause. And in one notorious case, Southwest claimed inclement weather cancelled flights in Florida, but it was the only airline to cancel significant numbers of flights. In other words, it wasn’t the weather.
The Wall Street Journal recently posted an article that explored the issue, doing so via a great example. It followed the literal path of one Southwest aircraft over one long holiday weekend. The screenshot below captures two of the graphics with a wee bit of text between.
What’s nice about the graphics’ design is how they use small multiples and consistent colours. The intended route is always on the left and what actually happened is on the right. Red and blue colours depict those throughout.
The only thing I quibble with is the embedded HTML text. Sometimes the page loads fine for me, other times it looks like it did this morning for this screenshot. Note how for some city labels the final letters get dropped to a second line, e.g. the “o” in Chicago or the “e” in Baltimore.
This is far from a deal breaker on this being a good graphic, but I find it mildly annoying, especially when in situations like the bottom left Orlando, there’s no obvious reason as to why, because the little airplane departure icon sits atop the final letter.
I understand the idea behind using native HTML text in graphics, but when things like this happen, I wonder if it wouldn’t simply be better to include the text as part of the graphic and avoid these potential mishaps altogether.
We are at that point in the year where I begin to use up my holiday time for work. I just returned from two weeks away, but I am out again tomorrow, so no post. Ergo, this Thursday is my Friday. And so I’ll leave you with a post from xkcd that talks vexillology, or the study of flags.
