Mapping with CartoDB

I’ve toyed with the idea of mapping before, but I thought mapping would involve lots of coding and headaches. Then I used CartoDB, and my life changed! (Sorry, this sounds like an infomercial.) Seriously, though, CartoDB is much, much more user-friendly than I expected. Although I had to follow instructions to create my multiple maps in CartoDB, I marveled at how easy it all was. I have to offer the caveat that I used a data set already provided to me, so I wasn’t manually entering any data laboriously. However, we’re talking about mapping, NOT metadata (thank goodness!), so let me begin.

The first type of map–the “dot map“–is fairly basic. There’s not much difference between this map and drawing dots on a physical map. However, you do get to select the background map, making it look slick and chic or going with an old-timey look. The background can convey a lot about what kind of data is being presented, so I liked this aspect of CartoDB. The other difference that makes this superior to a regular map and pen is the “hover” or “click” pop-ups, which, as the names suggest, allow information connected to each dot to appear whether you hover or click your cursor on it. I enjoyed the pop-ups because, when graphing in math class, I felt like legends were inadequate to convey all the information I wanted to. This solved that kind of problem perfectly.

The second type of map I tested out was the “animated map.” In this map, dots appeared and disappeared on the map to indicate when each interview was conducted. I really enjoyed this map, even if its information was very limited (i.e., the dates of the interviews). However, if this is the information you wanted, then you wouldn’t have to hover over dozens of dots to find out every date. Also, the animation provided a great insight into the frequency of the interviews across a period of almost a year, especially the months when the most interviews were conducted.

The third map I created was the “heat map,” which I definitely liked the least. I can imagine this kind of map would be useful if there are multiple data points in one town, say, as the dot map tends to let one data point cover up the others. However, since the interviews were relatively widespread, I don’t think this map was the best choice. I can see its uses, however, so don’t write it off. As always, you have to think about the information you want to convey, and the best medium for doing so.

We called the fourth map a “category map.” It’s a bit harder to describe this one, but basically this was a more interactive dot map. I was able to select widgets that allowed you to see the map through different categories: gender of the slave, name of the slave, where the slave was born, etc. True, this was all information available with the pop-ups on the dot map, but I enjoyed the idea of the visual presentation of certain information. Once again, it’s about accessibility of the information. It’s far easier to see dots of two colors and think, “Oh, there are the males and there are the females,” rather than clicking on every single dot. Plus, since I could only select a few widgets, I could focus the dots on the slaves, rather than on the interviewers. The animated map focused on when the interviews took place, which places emphasis on the project to document the slaves, not actually on the slaves themselves.

I suppose with the last map, the “layered map,” I was supposed to utilize all the information I previously learned about creating these maps. However, I couldn’t really use my two favorite types of map–animated and category–so I went the uncreative route and used two dot maps in different colors. The point of the layered map is to showcase multiple data sets on one map, so this map, for instance, shows where slave interviews were conducted and also where slaves were enslaved. However, I wished there were more of a relation between the two data sets. I did get to see that while the interviews were conducted in Alabama, the places people were enslaved were in Louisiana, Alabama, and Mississippi, to name a few. I suppose this might be a fault of mine for expecting too much of CartoDB and of the data sets (they might not have represented the same people, after all), but then I think that eliminates the spirit of a layered map. I wouldn’t put two unrelated data sets on the same map–that wouldn’t make sense. So I wanted to see more of a connection, and there wasn’t one.

Overall, CartoDB was very user-friendly, and it’s a great way to showcase data.

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