Time used a pair of area charts (a form of treemap) to illustrate the trend in Americans adopting babies of foreign origin. The data consist of the number of babies labeled by country of birth in 1999 and in 2013.
This type of chart fails the self-sufficiency test. The entire dataset is faithfully reproduced on the printed page, and that is because readers cannot figure out the relative sizes by their own eyes. (Try imagining the charts without the numbers.)
This need to present all of the data creates an additional design challenge: how to place country names where several boxes crowd onto one another. The designer here adopts an expand-from-the-middle approach, which might require getting used to.
In addition, the amount of distance placed between the pair of dates is vast, and that is not optimal for a graphic whose primary goal is to elicit a trend.
Here is the Bumps-style chart. These charts are great except where the data are tightly clustered. Recently I have been experimenting with small-multiples as a way to split up the data, which alleviates the labeling challenge.
In this version, the countries are shown as four groups. The countries that show up as significant enough in each year to merit individual labels are shown in the middle, themselves split into two groups: those that have seen its share of adoptions increase versus those that have seen a decrease. The remaining countries show up in only one of the two years. Presumably this means in the other year, there were zero adoptions from those countries. (However, it is also possible that in the missing year, the numbers were so tiny that they were included in the "Rest of the World" category.)
I also switched to graphing shares of adoptions rather than number of adoptions. The total number of adoptions dropped drastically during that period. It is often the share, not the absolute numbers, that is of interest.