Missing Planets

In science news, we turn to graphics about planets and things. Specifically we are talking about exoplanets, i.e. planets that exist outside our solar system. Keep in mind that we have only been able to detect exoplanets since the 1990s. Prior to then, how rare was our system with all our planets? It could have been very rare. Now we know, probably not so much.

But, in all of that discovery, we are missing entire types of planets. This article published by Forbes does a nice job explaining why. But one of the key types of planets that we have been unable to discover heretofore have been: intermediately distant, giant planets. Think the Jupiters and Saturns of our system. Prior to now we could detect massive Jupiter-like planets orbiting super near to their distant stars. Or, we could detect super massive planets orbiting very far away. The in-betweeners? Not so much.

There's still a pretty wide gap out there…
There’s still a pretty wide gap out there…

The above screenshot does a good job of showing where new detection methods have allowed scientists to begin to fill in the gaps. It shows how there is an enormous gap between what we have discovered and how they have been discovered. And the article does a nice job explaining how the science works in that only now with our longer periods of observation will help resolve certain issues.

From a design standpoint, this isn’t a super complicated graphic. It does rely upon a logarithmic scale, which isn’t common in non-scientific or academic papers. But this graphic comes from that environment, so it makes a lot of sense. The article is full of graphics from third-party sources, but I found this the most informative because of that very gap it highlights and how the new work (the stars) begin to fill it in.

Credit for the screenshotted piece goes to E. L. Rickman et al.

Much Improved Mapping of American Migration

Forbes released Jon Bruner’s latest map of migration in the United States. It uses IRS figures to show inbound and outbound movement from counties across the United States. The work itself is an improvement from his map from last year, which was a bit more difficult to read. Beneath is the new version, and at the end, for comparison, the old.

This year's migration map
This year's migration map

Firstly, the colour palette is far more sophisticated. Secondly, and most crucially, the user can hide the lines on the map, which obscures a key part of the story of migration in urban areas—higher income people moving out of the city and into the suburbs. Thirdly, the map data now includes additional years, which are available by clicking the small chart in the upper right—a welcome addition that allows the data from last year’s map to become accessible this year. Fourthly, and to be fair this may have existed previously but not that I can recall, the new map is accompanied by essays.

These essays use the map and its data to tell stories and explain what one sees going on with the data. It is (relatively) easy for one to put together a piece of data visualisation from a data set. But, without knowing where to look, users may not actually find anything valuable in the visualisation. By pointing to these essays, the map—already much improved from a design perspective—takes on a much more rounded and mature character and becomes more about generating information and knowledge than simply figures and statistics.

Last year's migration map
Last year's migration map