Pill Bugs, Potato Bugs or Doodlebugs? | Data and the Web

Data and the Web

Pill Bugs, Potato Bugs or Doodlebugs?

Image - Pill BugIf you haven't checked out what the fine folks at Many Eyes are doing with “community” data visualization, it is well worth a peek. I took a look at one of their recent blog posts today regarding the new map visualizations they are offering. Very nice stuff indeed.

However, the thing that really caught my [many] eye[s] was the mention of a data set denoting “the regional slang for those odd little bugs that curl into balls.” This is definitely not something that keeps me up at night, but I've always wondered about the monikers of these benign little creatures. I grew up calling them “pill bugs.” However, probably due to some deep psychological desire to be accepted in elementary school, I eventually started referring to them as roly-polies, since that is what my friends called them.

I dug up the visualization in question and was pleased to see that I probably wasn't the only kid in Chicagoland that may have struggled with these entomological naming conventions — in fact, there are a bunch of other names given to these li'l guys across the US. For posterity, Illinoisans call this thing a Pill Bug, Roly-Poly, Potato Bug, Sow Bug and Doodlebug 15%, 41% 7%, 6%, and 3% percent of the time, respectively.

The one downside that I've encountered with Many Eyes is they only seem to provide the underlying data set in a .txt file (albeit in tab delimited format). Kirix Strata™ doesn't yet recognize the tsv-in-txt's-clothing just yet, so you need to save the file to the desktop and then open it up in Strata (selecting a text-delimited file type with a tab delimiter). But, once you get it in there, fire up your analytical skills and manipulate away.

Also, please report any bugs while you're at it. ;)

Edit: Per Wikipedia, there are a bunch of other common names associated with these insects, including my favorite, “cheeselog.”

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Data and the Web is a blog by Kirix about accessing and working with data, wherever it is located. We have a particular fondness for data usability, ad hoc analysis, mashups, web APIs and, of course, playing around with our data browser.