April 15, 2013
The Insanely Illustrated Guide To Your First TileMill Map | Data For Radicals

11:05pm  |   URL: http://tmblr.co/ZjZlBwiogBC9
  
Filed under: maps mapping tilemill 
April 8, 2013
kqedscience:

The Big Squeeze: Can Cities Save The Earth?
“Tim de Chant has a wonderfully creative blog called Per Square Mile, where he thinks about population density. Last summer, he decided to a little experiment. He asked himself: Suppose I could move everybody on Earth into a single city. How much space would that city occupy?
Would it cover half a continent? Or could we fit all humanity into New Jersey?”

kqedscience:

The Big Squeeze: Can Cities Save The Earth?

“Tim de Chant has a wonderfully creative blog called Per Square Mile, where he thinks about population density. Last summer, he decided to a little experiment. He asked himself: Suppose I could move everybody on Earth into a single city. How much space would that city occupy?

Would it cover half a continent? Or could we fit all humanity into New Jersey?”

March 21, 2013
Speed Cameras

Possibly also Gothamist’s first dataviz.

8:52pm  |   URL: http://tmblr.co/ZjZlBwgp6XkR
Filed under: maps mapping speeding roads 
March 19, 2013
CartoDB | Blog: New publishing template for comparing maps.

cartodb:

A couple of weeks ago we launched two HTML templates for publishing your maps to the web to help you create custom content and provide more context for your maps. The templates are focused on two different use cases, one is targeting the editorial world by allowing content above and below…

11:06am  |   URL: http://tmblr.co/ZjZlBwgdM_tB
  
Filed under: Maps Mapping Tools 
March 17, 2013
kthread:

fourthsectorconsulting:

Mapping Food Deserts
The USDA has released their Food Access Research Atlas—a tool that lets policymakers, advocates, and community members see where food deserts are located throughout the U.S. Food deserts are areas where people have difficulty accessing fresh, healthy food. 

I feel like this would be more compelling if we could see population in the food deserts, maybe by gradient. What needs be obvious is not only how large the food desert is, but how many people are affected, right?

kthread filled in the gap: where are the people? There are a lot of people in Brooklyn and the Bronx who don’t live anywhere near a source of fresh food but you wouldn’t know it from this map. There are not a whole lot of people in eastern Oregon, period. So knowing what your map shows (in this case, rural poverty) and what it doesn’t is vital.

kthread:

fourthsectorconsulting:

Mapping Food Deserts

The USDA has released their Food Access Research Atlas—a tool that lets policymakers, advocates, and community members see where food deserts are located throughout the U.S. Food deserts are areas where people have difficulty accessing fresh, healthy food. 

I feel like this would be more compelling if we could see population in the food deserts, maybe by gradient. What needs be obvious is not only how large the food desert is, but how many people are affected, right?

kthread filled in the gap: where are the people? There are a lot of people in Brooklyn and the Bronx who don’t live anywhere near a source of fresh food but you wouldn’t know it from this map. There are not a whole lot of people in eastern Oregon, period. So knowing what your map shows (in this case, rural poverty) and what it doesn’t is vital.

March 4, 2013
kenyatta:

Mapping Data-Dense Cities as if They Were Mountains

This gave Herwig another idea for how to visualize data points that essentially pile up on a given place. “Why don’t I treat them like elevation?” he says. Dense information has a topology in the same way that physical terrain does.

sunlightcities:

Making more sense of dense data visualizations. 
-Source: Atlantic Cities 

Deleuze and Guattari would be proud.

John Keefe included another great example of topo mapping in his NICAR maps talk.

kenyatta:

Mapping Data-Dense Cities as if They Were Mountains

This gave Herwig another idea for how to visualize data points that essentially pile up on a given place. “Why don’t I treat them like elevation?” he says. Dense information has a topology in the same way that physical terrain does.

sunlightcities:

Making more sense of dense data visualizations. 

-Source: Atlantic Cities 

Deleuze and Guattari would be proud.

John Keefe included another great example of topo mapping in his NICAR maps talk.

(via notational)

12:13pm  |   URL: http://tmblr.co/ZjZlBwfVH8zW
  
Filed under: maps mapping topography 
March 4, 2013
Clay Shirky on Homicide Watch and Homicides in the District

We should/could have a whole separate discussion about dashboards and showing your work and Homicide Watch, but this is a great story that looks at two closely related projects side by side.

12:10pm  |   URL: http://tmblr.co/ZjZlBwfVGZWI
  
Filed under: mapping ethics maps 
March 3, 2013
John Keefe, Dave Cole, Matt Stiles on maps and mapping

Well annotated slides from their 2013 NICAR talk.

March 3, 2013
I believe this came up in class last week.

I believe this came up in class last week.

(Source: xkcd.com)

February 23, 2013
journo-geekery:

fastcodesign:

Infographic: An Amazing, Invisible Truth About Wikipedia
Every Wikipedia entry has an optional feature we take for granted—geotagging. An entry on the Lincoln Memorial will be linked to its specific latitude and longitude in Washington D.C. On any individual post, this may or may not be a useful thing. But what about looking at these locations en masse?
That was a question asked by data viz specialist and programmer Olivier Beauchesne. To find out, he downloaded all of Wikipedia (it’s open-source, after all) then used an algorithm that would assemble 300 topical clusters from popular, related keywords. Then he placed the location of each article in these topical clusters on a map. What he found was astounding.
“Eventually, Beauchesne’s maps evolve to something more than the locations of everything in the world. They become the locations of, quite simply, everything we know.”

Lovely work.

journo-geekery:

fastcodesign:

Infographic: An Amazing, Invisible Truth About Wikipedia

Every Wikipedia entry has an optional feature we take for granted—geotagging. An entry on the Lincoln Memorial will be linked to its specific latitude and longitude in Washington D.C. On any individual post, this may or may not be a useful thing. But what about looking at these locations en masse?

That was a question asked by data viz specialist and programmer Olivier Beauchesne. To find out, he downloaded all of Wikipedia (it’s open-source, after all) then used an algorithm that would assemble 300 topical clusters from popular, related keywords. Then he placed the location of each article in these topical clusters on a map. What he found was astounding.

“Eventually, Beauchesne’s maps evolve to something more than the locations of everything in the world. They become the locations of, quite simply, everything we know.”

Lovely work.

(via lifeandcode)

February 14, 2013
Scape Toad (for reshaping maps)

4:16pm  |   URL: http://tmblr.co/ZjZlBwe8nO3Q
  
Filed under: tools maps mapping distortion 
February 10, 2013
I forget now who brought up a Sourcemap-like idea in class this week, but if you’re interested in mapping supply chains, check them out. The map above traces Chicken of the Sea: Light Meat Tuna from sea to sandwich.

I forget now who brought up a Sourcemap-like idea in class this week, but if you’re interested in mapping supply chains, check them out. The map above traces Chicken of the Sea: Light Meat Tuna from sea to sandwich.

January 27, 2013
How to make a map with Google Fusion tables

babydatajournalism:

From Simon Rogers, data editor/news editor at The Guardian newspaper. 

2:48pm  |   URL: http://tmblr.co/ZjZlBwcnRoDy
  
Filed under: tutorial maps mapping 
November 14, 2012
officialssay:

“Where does it end? Is HUD going to call for a breakup of Vermont and Maine because they are 95 percent white?” Westchester County Executive Rob Astorino, in a New York Daily News op-ed last year, arguing that residents’ income, not race, determines where they live.
But our map suggests otherwise.
Here, the darker the blue, the more African-American households there are in a certain area. One shows Westchester as it is today. The other shows what Westchester would look like if African-American households were located near white households of the same income.
For the full interactive map, click here: http://propub.ca/STCvTO

officialssay:

“Where does it end? Is HUD going to call for a breakup of Vermont and Maine because they are 95 percent white?” Westchester County Executive Rob Astorino, in a New York Daily News op-ed last year, arguing that residents’ income, not race, determines where they live.

But our map suggests otherwise.

Here, the darker the blue, the more African-American households there are in a certain area. One shows Westchester as it is today. The other shows what Westchester would look like if African-American households were located near white households of the same income.

For the full interactive map, click here: http://propub.ca/STCvTO

November 14, 2012
kenyatta:

skepticalavenger:


Chris Howard:  America really looks like this - I was looking at the amazing 2012 election maps created by Mark Newman (Department of Physics and Center for the Study of Complex Systems, University of Michigan, http://www-personal.umich.edu/~mejn/election/2012 ), and although there is a very interesting blended voting map (Most of the country is some shade of purple, a varied blend of Democrat blue and Republican red) what I really wanted was this blended map with a population density overlay. Because what really stands out is how red the nation seems to be when you do not take the voting population into account; when you do so many of those vast red mid-west blocks fade into pale pink and lavender (very low population).
So I created a new map using Mark’s blended voting map based on the actual numbers of votes for each party overlaid with population maps from Texas Tech University and other sources. 
Here’s the result—what the American political voting distribution really looks like.

Now THIS is the most accurate map that I’ve seen, and it is fascinating.

It’s a shame ‘purple’ doesn’t suit the simple narrative of left vs right, good vs evil, spy vs spy, electoral college vs the person you voted for that makes for a dramatic, easy to understand story. Otherwise, we’d see more of this during actual coverage on election night.

You see so much more in a map like this.

kenyatta:

skepticalavenger:

Chris Howard:  America really looks like this - I was looking at the amazing 2012 election maps created by Mark Newman (Department of Physics and Center for the Study of Complex Systems, University of Michigan, http://www-personal.umich.edu/~mejn/election/2012 ), and although there is a very interesting blended voting map (Most of the country is some shade of purple, a varied blend of Democrat blue and Republican red) what I really wanted was this blended map with a population density overlay. Because what really stands out is how red the nation seems to be when you do not take the voting population into account; when you do so many of those vast red mid-west blocks fade into pale pink and lavender (very low population).

So I created a new map using Mark’s blended voting map based on the actual numbers of votes for each party overlaid with population maps from Texas Tech University and other sources. 

Here’s the result—what the American political voting distribution really looks like.

Now THIS is the most accurate map that I’ve seen, and it is fascinating.

It’s a shame ‘purple’ doesn’t suit the simple narrative of left vs right, good vs evil, spy vs spy, electoral college vs the person you voted for that makes for a dramatic, easy to understand story. Otherwise, we’d see more of this during actual coverage on election night.

You see so much more in a map like this.