Archived entries for Mapping

Meter Beaters

Meter Beaters is an app to find free parking spots in Chicago. With so much freely available civic data you would imagine that there would be plenty of apps like this, but the city keeps it’s parking data close to the chest. I know because I tried to build something like this 6 years ago.

Meter Beaters

I wanted an app to show me where residential parking zones were so I could spot the non-zoned streets and find free parking. This is particularly difficult in neighborhoods such as Lincoln Park. I tried filing a FOIA request to get the data, but they were only willing to provide it as 100s of pages of printouts. I build a web scraper in Processing to walk through a GIS database and query each street section through their parking zone look-up form, but then they installed a CAPTHA on the form. I asked the Chief Data Officer of the city in the nicest way I could, but nothing. After a while, I just gave up.

All I can assume is that the city does not want to provide easily accessible access to this data, so I’m glad to see that someone has taken up the challenge. The app isn’t perfect, I have critiques of the interaction model and I’ve found flaws in the data. They have a way to submit corrections though, so hopefully it will improve over time.

Lost to progress

I ran across an interesting tidbit about modern cartography while reading a New Yorker article profiling Paul Krugman today (emphasis mine):

Krugman began to realize that in the previous few decades economic knowledge that had not been translated into models had been effectively lost, because economists didn’t know what to do with it. His friend Craig Murphy, a political scientist at Wellesley, had a collection of antique maps of Africa, and he told Krugman that a similar thing had happened in cartography. Sixteenth-century maps of Africa were misleading in all kinds of ways, but they contained quite a bit of information about the continent’s interior—the River Niger, Timbuktu. Two centuries later, mapmaking had become much more accurate, but the interior of Africa had become a blank. As standards for what counted as a mappable fact rose, knowledge that didn’t meet those standards—secondhand travellers’ reports, guesses hazarded without compasses or sextants—was discarded and lost. Eventually, the higher standards paid off—by the nineteenth century the maps were filled in again—but for a while the sharpening of technique caused loss as well as gain.

It makes me wonder how this phenomena shows up in other disciplines like education, public policy, and healthcare. If the new standard for accuracy includes an idealogical or methodological bias it could forever exclude the re-inclusion of previously held beliefs. As our world becomes more standardized, quantifiable, and testable it will be important to look back to our archives to see what didn’t fit in so nicely and why.

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