Hi Greg,
I don't think anyone's claiming there should be the same amount of
OSMers *per square kilometer*, but *per capita* instead.
Rory
On 09/07/18 02:21, Greg Morgan wrote:
On Mon, Oct 9, 2017 at 2:10 PM, Frederik Ramm <frede...@remote.org
<mailto:frede...@remote.org>> wrote:
Hi,
today I was pointed to a recent, open-access scientific paper called
"Information Seeding and Knowledge Production in Online Communities:
Evidence from OpenStreetMap". This open-access paper is available here
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3044581
<https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3044581>
In the context of armchair mapping, but especially of data imports (and
recently, machine-generated OSM data) there's always been the discussion
between those who say "careful, too much importing will hurt the growth
of a local community", and others who say "this import is going to
kick-start a local community, let's do it!"
Honestly Frederik, you point to a study and say that it is all
scientific. Furthermore, you act like you just came across the study
when in fact you have already pushed to the mailing lists on two other
occasions.[1][2] This also shows that you have failed to properly check
the research before pushing the link once again. The study is all
scientific sounding yet the very heart of the study is based on the
Modifiable Areal Unit Problem.[3] Quoting the author "Note that TIGER
information was incorporated for 3,093 counties within the US; the state
of Massachusetts was excluded because better quality information
was available from the state government.12 I will restrict my analysis
to these 3,093 counties." The author picked any data, ignoring the size
of the population or other social and economic factors to make his
point. Thankfully the US Census Bureau uses "Block Groups (BGs) are
statistical divisions of census tracts, are generally defined to contain
between 600 and 3,000 people, and are used to present data and control
block numbering."[4] The whole foundation of the "INFORMATION SEEDING
AND KNOWLEDGE PRODUCTION IN ONLINE COMMUNITIES: EVIDENCE FROM
OPENSTREETMAP" study is based on a geographic division that the
_Census_department_would_not_use_. The Census Bureau uses their block
and tract configuration for a number of federal programs.
Based on local knowledge you shouldn't even be pushing this study. This
appears to be what happened. A smart person takes a plane trip to the
east coast of the US. That person obtains a degree at MIT and is a
Post-Doctoral Fellow--egg head kind-of smart. That same person that
authored this study now takes a plane trip to UC Berkeley in California
for a job that the person landed. These two plane trips have led to his
fatal analysis that all counties and the rest of the US must look like
MIT and UC Berkeley and have the same high density as those two cities.
Let's take the Arizona county I map out of, Maricopa County[5], the
Arizona county just north of me, Yavapai County [6], and Switzerland[7]
to see the basic flaws in this research. 5/8th of Switzerland fits in
my county alone. Adding Yavapai County's size to Maricopa County's size
we now have all of Switzerland covered and the combined population of
Maricopa County and Yavapai County adds only a 228,168 increase to
Maricopa County's population. The study says that both Maricopa and
Yavapai county should perform the same. Following this I have always
heard from European's that the American's should perform the same just
like how Europe mapped. The size of two counties that are part of
Arizona swallows up the size of Switzerland begins to show why the US
has a lower mapper density than Europe does.
Let's compare Germany[8], the state of Montana[9] and the United
States[10]. We see that the size of Montana matches the size of
Germany. Yet, we see the population density is roughly 82 million
people in Germany to 1 million people in Montana.z You see there is
nothing special to the vaunted Germany Pub Meetup as a way to map. You
have the natural density to make it happen. Moreover, now you feel the
German experience should be the same for the rest of the world and that
Montana can have the same mapping success as Germany. In Germany
mappers are a dime a dozen. Oh but wait! Let's take Germany's
population density and see what the US population would have to be to
have the same mapping success.
US Square Milles 3,796,742 / Germany Square Milles 137,903 = It takes
27.53197537399476 Germany's to fit into the US.
This means that to match the German population the US would need
27.5319753739947 * 82,800,000 = 62,279,647,560.966766 people where the
current population is 325,719,178.
The value of travel and education is that a person's understanding of
world is expanded. That person's view is expanded to understand other
human beings live and work in diverse places. The failure here is that
instead of understanding that the world is different; instead of
understanding that not every one has high speed internet; instead of
understanding that not every one has the same leisure time available to
map; the same tired rhetoric is repeated over and over again that
everyone should be able to craft map their local space has overshadowed
the obvious need to change our outreach to draw more people into
mapping. The rhetoric also fails to address how does OSM keep mappers
once an area is imported or craft mapped. That is the real problem not
imports.
Finally, I provide two more items to think about. Ben Discoe[11] keeps
an interesting metric. Thinking about Ben's data, if the US were to try
and survey every node without an import, then it would take 31.7 years
to generate the same number of nodes created by the TIGER import. 31.7
years is not a very useful map. In addition, even though I am out
Mapillary[12] surveying most days, I have not covered the entire state
of Arizona. I haven't even covered every major road. That would still
not be a very useful map. However, I can eat my own tasty dog food and
use maps.me <http://maps.me> for all my map needs. It is not perfect.
The map does not have to be in order to be useful.
Another approach is needed to generate more interest in OpenStreetMap.
It is not the imports dude.
Regards,
Greg
[1]
https://lists.openstreetmap.org/pipermail/talk/2017-October/079116.html
<https://lists.openstreetmap.org/pipermail/talk/2017-October/079116.html>
[2]
https://lists.openstreetmap.org/pipermail/talk-us/2017-October/018002.html
<https://lists.openstreetmap.org/pipermail/talk-us/2017-October/018002.html>
[3] https://en.wikipedia.org/wiki/Modifiable_areal_unit_problem
<https://en.wikipedia.org/wiki/Modifiable_areal_unit_problem>
[4] https://www.census.gov/geo/reference/gtc/gtc_bg.html
<https://www.census.gov/geo/reference/gtc/gtc_bg.html>
[5] https://en.wikipedia.org/wiki/Maricopa_County,_Arizona
<https://en.wikipedia.org/wiki/Maricopa_County,_Arizona>
9,224 square miles
4,307,033 population
[6] https://en.wikipedia.org/wiki/Yavapai_County,_Arizona
<https://en.wikipedia.org/wiki/Yavapai_County,_Arizona>
8,128 square miles
228,168 population
[7] https://en.wikipedia.org/wiki/Switzerland
<https://en.wikipedia.org/wiki/Switzerland>
15,940 square miles
8,401,120 population
[8] https://en.wikipedia.org/wiki/Germany
<https://en.wikipedia.org/wiki/Germany>
137,903 square miles
82,800,000 population
[9] https://en.wikipedia.org/wiki/Montana
<https://en.wikipedia.org/wiki/Montana>
147,040 square miles
1,050,493 population
[10] https://en.wikipedia.org/wiki/United_States
<https://en.wikipedia.org/wiki/United_States>
3,796,742 square miles
325,719,178 population
[11] _https://www.openstreetmap.org/user/bdiscoe/diary/44192
<https://www.openstreetmap.org/user/bdiscoe/diary/44192>_
_https://docs.google.com/spreadsheets/d/1HiC1-ixx30tbwgI27RJt1SvvK80BBRkLOg98Qcb0SD0/edit#gid=1034182050
<https://docs.google.com/spreadsheets/d/1HiC1-ixx30tbwgI27RJt1SvvK80BBRkLOg98Qcb0SD0/edit#gid=1034182050>
_
_
_
What's remarkable to me, as you can see from the trendlines, is how
steady the rates are. At this rate, all of TIGER won't be cleaned up (or
at least touched) for another 31.7 years (for nodes) or 9.9 years (for
ways).
[12]
https://www.mapillary.com/app/?lat=33.63299223685526&lng=-110.89833796896335&z=6.748498419952923
<https://www.mapillary.com/app/?lat=33.63299223685526&lng=-110.89833796896335&z=6.748498419952923>
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