Undersea Mining

Today’s piece isn’t strictly about data visualisation. Instead it’s a nice article from the BBC that explores the nascent industry of undersea mining. What caught my interest was the story of Soviet submarine K-129, which sank mysteriously in the middle of the Pacific. But that isn’t even half the story, so if you are interested go and read the article for that bit.

But that sinking may have created the beginning of the undersea mining industry. And so as I read on, I found a nice mixture of text, photography, and graphics explaining processes and such. This screenshot is a comparison of the size of an undersea mining zone compared to a land-based copper mine.

An undersea mine vs. a surface mine
An undersea mine vs. a surface mine

Some of the graphics could use some polish and finesse, but I do appreciate the effort that goes into creating pieces like this. You will note that four different people had to work together to get the piece online. But if this is perhaps the future of BBC content, this is a great start.

Credit for the piece goes to David Shukman, Ben Milne, Zoe Barthlomew, and Finlo Rohrer.

More Murder in Merica

Today’s post was going to be something not this. But it is remarkable how many people die in the United States in mass shootings. It is, generally speaking, not a problem experienced in the rest of the developed world. The question is do we want gun violence to really define American exceptionalism?

Anyways, the Washington Post has a frightening piece exploring all the deaths, the guns, the killers, and the frequency of the killings.

Too many illustrations there
Too many illustrations there

Credit for the piece goes to Bonnie Berkowitz, Denise Lu, and Chris Alcantara.

All Your Base Are Belong to Internets

Over the weekend news broke that since November, plans for military bases around the world were available to anyone and everyone on the internets. How? Why?

Well, it turns out that soldiers using wearable tech to track their rides or cycling routes had forgotten to disable that feature whilst on military installations. And so when the company collecting the data published a global heatmap of activities, well, this happened.

You can even make out the perimeter of the former British airfield.
You can even make out the perimeter of the former British airfield.

This is not one of the worst offenders, because this is the site of what was formerly Camps Leatherneck and Bastion, the American and British, respectively, military bases in Helmand Province, Afghanistan. But we all know those bases exist and where they are. But, what is interesting and perhaps worrying for military planners is that sites like this do not show up on publicly available sites like Google Maps, for example. Take the same heatmap and look at it on satellite view and you get…a whole lot of nothing.

A view of the two military bases from well before they were constructed.
A view of the two military bases from well before they were constructed.

The problem is that when this technology is applied to places like, say, Syria. Given the civil war there, it is far more likely that users of wearable tech belong to or are working with one of the western military forces operating in the country. After all, the rest of the country is dark. So what is this set of rectangles and a grid-like pattern?

A bunch of rectangles and squares. It looks like a built up area, if not base.
A bunch of rectangles and squares. It looks like a built up area, if not base.

Well, by looking at the satellite photography, it is clearly a field situated between two small hamlets.

Nothing to see…I just run very straight routes through the middle of Syrian fields…
Nothing to see…I just run very straight routes through the middle of Syrian fields…

Most likely it is an American base. Could be Russian, though. But now we know where it is and have a rough understanding of its layout. You can see why military planners are concerned.

And it all owes to the ubiquity of tracking data on wearables, mobiles, vehicles, &c. And as we continue to generate data and want to see it visualised, are there or should there be boundaries? Alas, not a conversation for this blog to solve, but a conversation we should all continue to have.

Credit for the piece goes to the Strava design team.

Gerrymandering Again

The last two weeks we twice looked at gerrymandering as it in particular impacted Pennsylvania, notorious for its extreme gerrymandered districts. And now that the state will have to redraw districts to be less partisan, will Pennsylvania usher in a series of court orders from other state supreme courts, or even the federal Supreme Court, to create less partisan maps?

To that specific question, we do not know. But as we get ever closer to the 2020 Census that will lead to new maps in 2021, you can bet we will discuss gerrymandering as a country. Maybe to jumpstart that dialogue, we have a fantastic work by FiveThirtyEight, the Gerrymandering Project.

Since we focus on the data visualisation side of things, I want to draw your attention to the Atlas of Redistricting. This interactive piece features a map of House districts, by default the current map plan. The user can then toggle between different scenarios to see how those scenarios would adjust the Congressional map.

The setup today
The setup today

If, like me, you live in an area with lots of people in a small space, you might need to see Pennsylvania or New Jersey in detail. And by clicking on the state you can quickly see how the scenarios redraw districts and the probabilities of parties winning those seats. And at the bottom of the map is the set of all House seats colour-coded by the same chance of winning.

But what I really love about this piece is the separate article that goes into the different scenarios and walks the user through them, how they work, how they don’t work, and how difficult they would be to implement. It’s not exactly a quick read, but well worth it, especially with the map open in a separate tab/window.

Overall, a solid set of work from FiveThirtyEight diving deep into gerrymandering.

Credit for the piece goes to Aaron Bycoffe, Ella Koeze, David Wasserman and Julia Wolfe.

Gerrymandering Pennsylvania

Here in Pennsylvania this week, the state Supreme Court will hear arguments on the legality of congressional districts drawn by Republicans in 2010. The state is rather evenly split between Republicans and Democrats, e.g. Donald Trump won by less than one percentage point or less than 45,000 votes. But 13 of its 18 congressional districts are represented by Republicans, roughly 72%.

This graphic is from the New York Times Upshot and it opens a piece that explores gerrymandering in Pennsylvania. The graphic presents the map today as well as a nonpartisan map and an “extreme” gerrymander. The thing most noticeable to me was that even with the nonpartisan geography, the Democrats are still below what they might expect for a near 50-50 split. Why? One need only look at Philadelphia and Pittsburgh where, using the Times’ language, the Democrats “waste” votes with enormous margins, leaving the suburban and rural parts of the state open for Republican gains.

Three different ways of drawing Pennsylvania's congressional districts
Three different ways of drawing Pennsylvania’s congressional districts

Credit for the piece goes to Quoctrung Bui and Nate Cohn.

Where It’ll Be Too Warm for the Winter Olympics

The Winter Olympics are creeping ever closer and so this piece from the New York Times caught my eye. It examines the impact of climate change on host cities for the Winter Olympics. Startlingly, a handful of cities from the past almost century are no longer reliable enough, i.e. cold and snow-covered, to host winter games.

This screenshot is of a bar chart that looks at temperatures, because snow and ice obviously require freezing temperatures. The reliability is colour-coded and at first I was not a fan—it seemed unnecessary to me.

At first I did not care for the colours in the bars
At first I did not care for the colours in the bars

But then further down the piece, those same colours are used to reference reliability on a polar projection map.

But then this map changed my mind
But then this map changed my mind

That was a subtle, but well appreciated design choice. My initial aversion to the graphic and piece was changed by the end of it. That is always great when designers can pull that off.

Credit for the piece goes to Kendra Pierre-Louis and Nadja Popovich

The Internationalism in Sport

Whilst away, I came upon this piece in the following of my offseason baseball news. The New York Times published it between Christmas and New Years and the piece looks at the origins of sports persons in European football leagues compared to several American sports leagues, including American football, baseball, and basketball.

I was most confused by US women's football, which I had not realised has not been a single continuous organisation
I was most confused by US women’s football, which I had not realised has not been a single continuous organisation

The piece features an opening set of small multiples comparing all the leagues. Maddeningly, I wanted details and mouseovers and annotations at the start. Fortunately, as the reader continues through the article, each small multiple becomes big and the reader can explore the details of the league.

Credit for the piece goes to Gregor Aisch, Kevin Quealy, and Rory Smith.

Jones–Moore Election Results

Apologies for the lack of posts over the last week or so, I have alternately been on holiday or sick while spending other time on my annual Christmas card. This will also be the last post for 2017 as I am on holiday until the new year. But before I go, I want to take a look at the election night graphics for the Alabama US Senate special election yesterday.

I am going to start with the New York Times, which was where I went first last night after returning from work. What was really nice was there graphic on their homepage. It provided a snapshot fo the results before I even got to the results page.

The homepage of the New York Times last night
The homepage of the New York Times last night

The results page then had the standard map and table, but also this little dashboard element.

I'm spinning my wheels…
I’m spinning my wheels…

We all know how I feel about dashboard things. To put it tersely: not a fan. But what I did enjoy about the experience was its progression. The bars below filled in as the night progressed, and the range in the vote-ometers narrowed. But that same sort of design could be applied to other graphics representing the narrowing of likely outcomes.

The second site I visited was the Washington Post. Like the Times, their homepage also featured an interactive graphic, another choropleth map.

A different page, a different map
A different page, a different map

There are two key differences between the maps. The Times map uses four bins for each party whereas the Post simplifies the page to two: leading and won. The second difference is the placement of the map. The Post’s map is a cropping of a larger national map versus the Times that uses a sole map of the state.

For a small homepage graphic, bits of both work rather well. The Times cuts away the unnecessary map controls and neighbouring states. But the space is small and maybe not the best for an eight-binned choropleth. In the smaller space, the Post’s simplified leading/won tells the story more effectively. But on a larger space that is dedicated to the results/story, the more granular results are far more insightful.

On a quick side note, the Post’s page included some context in addition to the standard results graphics. This map of the Black Belt and how it correlates to regions of Democratic votes in 2016 provides an additional bit of background as to how the votes played out.

Note, the Black Belt was named for the black soil, not the slaves.
Note, the Black Belt was named for the black soil, not the slaves.

Credit for the piece goes to the design teams of the New York Times and the Washington Post.

Flying for Thanksgiving

This is a piece from a few years ago, but the New York Times cleverly brought it to the front of their Upshot page. And it seemed just so appropriate. Many of you are likely travelling today—I’m not, I’m headed to work—and many of you will be driving or taking the train. But some will be flying. But to and from where?

If only it captured other travel data
If only it captured other travel data

The map has some nice features that allow you to selectively few particular cities. Philadelphia has relatively few travellers by air, but that’s probably because places in the Northeast are more easily accessible by road or rail.

Chicago also has relatively few travellers, though more than Philadelphia. I would posit that is because most people are not flying to visit their relatives, but rather driving to places in Wisconsin, Iowa, and Indiana.

No post tomorrow, because I intend on sleeping in. But you can expect something on Friday.

Credit for the piece goes to Josh Katz and Quoctrung Bui.

The Importance of Cartography

Today I wanted to share with you a piece from the BBC that explores the importance of cartography, or mapmaking, in relief efforts particularly in Malawi, a country located in southeastern Africa.

My favourite still, perhaps, was an image of a hand-drawn map
My favourite still, perhaps, was an image of a hand-drawn map

This is a still from a short video—it clocks in at just a tad under three minutes—that you can watch to see how volunteers are identifying and mapping villages that do not appear on today’s maps. The importance, as they explain, is that if the village does not appear, it is as if the village does not exist. Consequently it can be quite difficult for aid to reach these villages during disasters like the 2015 floods.

Credit for the piece goes to Ruth Evans.