Sunday, July 21, 2013

A Principle of Mapping Involving Precision and Accuracy

In the Coursera Map course that I am taking (https://www.coursera.org/course/maps), we were asked to place virtual pins on an interactive world map. Many students drilled down deeply to very specific locations in order to place their pins, some of these deliberately lying a bit so as not to reveal their exact location. Others placed their pins at coarse renderings on the map, without drilling down deeply at all, BUT NONETHELESS their pins appeared in rather arbitrary locations when the user drilled down and the map was viewed at a higher resolution. I wrote the following to the course discussion board, with a few revisions here to contextualize it. These maps represent digital tools that we may want to use in Vanderbilt MOOCs and we may want to improve on them.

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I was one of those who drilled down to the building level in placing my pin, and was quite exact (an exact location in the city of Nashville). I saw one posted pin that was in the middle of Vanderbilt stadium and other pins looked haphazardly placed. Some of these may have been placed intentionally in (modestly) wrong places, as many have outlined on the boards. But some of these may have been placed in the Nashville region at a COARSE grained (low resolution) map by people who did not drill down deeply at all.

                                    snippet from ESRI-generated map on PennState course site
My placement was precisely where the faculty apartment is at McGill Hall (top right yellow pin), but another person's pin in the middle of Vanderbilt stadium, Dudley Field -- mistake?


These latter pin placements were accurate at the grain level in which they were placed, but (unintentionally) wrong at finer grained renderings of the map.

Shouldn't there be a precision principle of interactive maps like that provided in the class (analogous to rules of precision for floating point numbers I suppose)? Shouldn't there be some functionality for interactive maps, perhaps a research topic, that I can identify data with a region in a low resolution rendering of a map without being wrong at higher resolution when a user drills down. I can think of strategies to do this, but given the ambiguities of regions that this course has already made us aware of, there must surely be some fleshing out of these ideas.

I had the same question a couple of years ago when I started placing pictures on Google maps, most very precise down to a few square feet, but I also wanted to place some pictures on a larger region (e.g., a museum, a park, a city) with NO implication that these pictures were intended to be accurate at a finer grained level. (I wrote about this very fun exercise as well -- see http://aicourses.blogspot.com/2013/07/playing-with-pictures.html; beyond being fun though, its also a story that is illustrative of a point that is central in the Coursera-hosted PennState Map course -- that maps and geospatial tools/concepts can be central in telling stories!!!)

To the geographers out there -- is anyone doing research on implementing methods that enforce a precision principle of interactive maps?

BTW -- I think that a significance of this precision principle relates to issues of privacy. I'm guessing that those people who do NOT want to precisely identify their location, or identify their demographics (e.g., age, gender) with their own location, are probably sensitive to misidentifying someone else's residence with them (or with their demographics) -- at least I think that many would be sensitive to that.

But if placing a pin (or picture or ...) on a low resolution rendering of a map "accidentally" places the pin on someone else's residence at a higher resolution, then this misrepresenting of the makeup of that residence is exactly what could happen!

1 comment:

  1. This quote and the followup discussion on representation from Brent Hecht and Emily Moxley (http://www.tandfonline.com/doi/pdf/10.1080/02693799108927841, pp. 5-6) is certainly relevant to the precision principle idea

    Stated simply, GSP arises because most Web 2.0 spatial data representation schemas only support point vector features. The “blame” for this limited representational expressiveness can probably be split between designers’ lack of education about geographic information as well as a dearth of popular tools that support vector features of greater than zero dimensions. For many geoweb applications, GSP does not restrict functionality a great deal, but in some cases, the points - only paradigm borders on ridiculous."

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