During a late night epiphany we decided the blog had gotten a bit stale. So, to encourage a regular flow of content we figured a new look and pithy title would be just the trick. Welcome to the shiny-new, rebranded, USGS approved “Off the Map”. Now fortified with vitamins, minerals, insight, and elegant prose.

Why change the title to “Off the Map”? Well push pins seemed so 2005 and we needed another reason for an office contest. The winner you’ve now seen, but there were lots of other great entries such as:

1. Geo Me This
2. Plain to the Simple
3. MapRap (bling your map ????)
4. Map This (including middle finger to the man* graphic)
5. Libre la Data
6. The Lat and Long of It
7. Atlas Maximus
8. Adept and Disheveled

Why did we end up picking “Off the Map”. Well speaking for myself I just wanted to be able to use Kyle’s graphic with the dead push pin.

The next reason? As we’ve been developing the second generation of GeoCommons we found the big areas we were having to innovate had nothing to do with the map. The new ideas that were going to change the way people use maps - were literally “off the map”. Whether it was handling large datasets ridiculously quickly in a browser or structuring taxonomies and semantic relationships we were increasingly putting lots of resources into data management. Just so happened that data could be shown on a map.

Don’t get me wrong the map is still the single interface that ties all the data together, but increasingly I think what will make the GeoWeb matter has less to do with maps (including all sorts of crazy 3-D worlds) and more to do with delivering useful data to help people make better decisions. Which happens to be done through a map.

We should be getting a couple of posts up a week explaining this line of thought in more detail. Most likely with several side trips of randomness and entertainment. So, please stay tuned and we promise to keep a regular flurry of GeoWeb bits o’ knowledge.

* “The man” of course being all those evil cabals preventing easy public access to open data

Popularity: 17% [?]

Yesterday we posted a blog about the international fiber cuts a few weeks ago. While I am interested in the geography of fiber and failures in general, we thought it would be a good opportunity to put Google MyMaps through its paces for creating a substantive data driven map. After 25 or so hours of collective labor I thought it would be useful to give the postmortem on our experience.

While there are many positive qualities to Google MyMaps the biggest complaint is that we spent 40 hours mucking about with it. The goal for the last blog post was to create a map that had 1) the fiber routes and landings for impacted carriers, 2) the location of the fiber failures, and 3) the countries that lost connectivity because of the failure. Seemed like a straight forward set of goals and I naively thought we could bang it out in a few hours. So, what ate up our time? Could we just be cartographically challenged?

1) Creating country boundaries - tracing all the countries with outlines so we could make polygons for the failed states was a big sink hole of time. The worst part was when we were not quite complete we hit the limit for the number of points a MyMap could support. Thus it was unfinished and did not make it to the blog post. If you are curious at what point MyMaps bonked here is the map:

View Larger Map

I’m trying to convince someone to count all the points so we have a numeric threshold but I think I need to offer more beer to get the bribe to work. The limit I’ve seen for number of points a My Map can support is 150, but it looks as if we exceeded that for drawing polygons.

2) Dealing with multiple layers - since there were three distinct layers to our MyMap we thought it would be useful to separate them out so the map would be easier to understand. The issue is that you can’t embed a Google MyMap with multiple distinct layers, they have to created as one continuous set. This was almost a deal breaker since we had broken up the work between three people (Bill Emily and myself). Fortunately we found a work around where we saved each of our maps/layers as kml then imported all three onto a new map (except Emily’s countries since it was the limit busting bonking layer).

3) Little bit of cartographic love - while push pins and drawing tools are great for posting pictures of my summer vacation some basic cartographic tools would have made life far easier. Dealing with the lack of a legend is challenging for conveying the story the map is telling. In MyMaps you get a list of every point on the map running down the right pain and with the embed you get nothing.

The conclusion at the end of it is MyMaps is a phenomenal drawing tool for maps - simple and intuitive. On the other hand if you want to create a data intensive map be prepared to run up against some technological limits, but more importantly be prepared to invest a good chunk of time. A large number of these limitations (need for enhancement) have been suggested in the MyMaps Google Group and it will be interesting to see if any are picked up in future releases.

* When I searched for other blog posts that have talked about the pros and cons for MyMaps I came up with zilch - making cross linking pretty tough. Interestingly the only comparison I found was for mapping service, but no one has compared the newer map creation tools. Maybe a topic for next time.

Popularity: 21% [?]

The winner-take-all Republican primary awarded McCain with 57 delegates. This was his second win over Romney in nearly as many weeks. A spatial distribution of the share of votes at the county level (see the map below) shows an interesting pattern where bright hues indicate higher share of votes for a candidate compared to all other candidates. McCain won more votes in 47 counties than any other candidate (counties shown in red), while Romney had plurality of votes in 17 counties (green) and Huckabee with an overall showing of 4th place, managed to claim Holmes county (blue), in Florida panhandle. On the other hand, Giuliani, who invested so heavily in just one state strategy, ignoring all the early primary/caucuses came in a distant third with not a single county to show for all his concentrated efforts/resources in Florida. Late today, Giuliani annouced that he was ending his presidential bid.

Color key: McCain counties = Red, Romney counties = Green and Huckabee counties = Blue

Vote counts by counties for McCain and Giuliani shows a very strong correlation coefficient of 0.999048, indicating that both were going after similar constituency within the Republican party and that McCain’s gain was Giuliani’s loss. Below are vote counts for the top five counties for each of the four candidates.

McCain’s top five counties by vote counts are Miami-Dade (~75,500), Pinnellas (~44,000), Broward (~40,660), Palm Beach (~38,480), Hillsborough (~37,800).
Giuliani’s top five counties by vote counts are: Miami-Dade (~ 40,250), Pinellas (~19,280), Broward (~18,660), Palm Beach (15,975), Hillsborough (~15,850).
Romney’s top five counties by vote counts are: Duval (~36,650), Pinellas (~34,970), Lee (~34,140), Hillsborough (~30,450), Palm Beach (~29,230).
Huckabee’s top five counties by vote counts are: Orange (~15,710), Duval (~13,830), Hillsborough (~12,840), Pinellas (~12,350), Brevard (~11,580).
Overall, out of 1.9 million votes cast in the closed primary, McCain won 36% (689,000) votes to Romneys’ 31% (~593,000), followed by Giuliani (~279,880) and Huckabee (~258,300).

For detailed datasets go to GeoCommons and search with keywords “Florida Republican Primary” and explore interactive thematic and heatmaps of vote counts for each of the top four republican candidates.

Popularity: 16% [?]

Economy was the number 1 issue for Michigan Republicans and they voted in large numbers for Mr. Romney. Michigan has one of the highest rates of unemployment in the U.S. Huge job losses in manufacturing sector, mainly due to down-turn in Michigan’s auto-industry has voters worried about the future. Romney’s “optimistic” message that he would fight to bring those jobs back to Michigan resonated with voters as opposed to McCain’s “straight talk” message that the lost jobs are never coming back!

Romney vis McCain: Michigan primary vote

Note: Brighter hues = Higher vote count, Darker hues = Lower vote count

This is Romney’s first win (not including his win in the Wyoming primary) and probably saved him from dropping out of the primaries after finishing 2nd, both in Iowa and New Hampshire. McCain and Huckabee finished 2nd and 3rd respectively. With Romney’s win in Michigan, the GOP has no clear cut front runner. Romney got nearly 38.9% votes (~337,700), to McCain’s 29.7% (257,400), followed by Huckabee at 16% (~139,600).

DNC (Democratic National Committee) decided to punish Michigan for violating primary rules by moving forward its primary date. They stripped Michigan of all its delegates for the National convention. As a result, both Obama and Edwards withdrew their names, while Clinton’s name remained on the ballot and she won the primary. According to some, Clinton would have won the primary anyway.

Clinton vis Mr. Uncommitted: Michigan primary vote

Note: Brighter hues = Higher vote count, Darker hues = Lower vote count

Interestingly many who wanted to support either Obama or Edwards voted “Uncommitted”. Clinton won more than 55% vote (~327,300) compared to 40% vote for Mr. “Uncommitted” (~236,900). And much of the “Uncommitted” vote came from African Americans and young voters according to the exit polls. This does not bode well for the Clinton camp, as the Democratic primaries move south where African-Americans are a major constituency. More on this in the future blogs.

In the meanwhile you may want to explore all of the maps shown above at Geocommons. Search with keywords “Michigan” or “Primary” to discover dynamic, interactive maps with zoom-in and pan.

Popularity: 17% [?]

Clinton’s come-from-behind stunning victory in the New Hampshire Primary makes her the New Comeback Kid. Below is a heatmap of spatial distribution of Clinton’s votes by cities/towns and places in the southern New Hampshire.

We at FortiusOne further analyzed voting patterns to find spatial distribution of where Obama, the New Kid on the block won more votes than Clinton in New Hampshire primary.

Explore the interactive heatmaps along with tons of data on Presidential politics on Geocommons.

Popularity: 16% [?]