A Typical Day in Iraq

Open the newspaper or turn on the news, and nearly every day there are reports of terror-inspired violence in Iraq. Just today, a deadly car bomb took the lives of 11 and wounded 45 others in an area near the northern city of Kirkuk. Sixty badly decomposed bodies were found on August 6 in a secluded area of the turbulant Diyala Province. A brief moment of normalcy for some Iraqis was violently disrupted when a car bomb hit a bustling ice cream parlor on August 1, killing 60 people. On July 30, six were killed and several wounded in a car bomb that abruptly interrupted the fesitivies following Iraq’s win in the Asian Soccer Cup. These are just a few examples of what a typical day in Iraq looks like.

The statistics on violence in Iraq are bleak. MSNBC reports :

The number U.S. casualties per day in Iraq is around 25.

The average number of Iraqis who are wounded or killed each day is 100.

There are roughly 1000 attacks per week on people of all nationalities.

This is up from 600 just a year ago.

U.S. citizens are the target of more than 75% of the attacks that occur in Iraq.

Terror Hotspots in Iraq

The National Counter Terrorism Center maintains a database, called the World Wide Incidents Tracking System, that provides a record of observed terror incidents across the globe going back to 2004. According to the center, “Terrorism occurs when groups or individuals acting on political motivation deliberately or recklessly attack civilians/non-combatants or their property and the attack does not fall into another special category of political violence, such as crime, rioting, or tribal violence.”

Included in the dataset is detailed information on each incident – e.g., nationality of perpetrator, nationality of victim, weapon of choice, event type and faciltiy targeted. The number of fatalities, wounded and hostages taken per incident are also on record.

So, which areas of Iraq have been most prone to terrorism? To answer this question, all of the records for Iraq were extracted from the database, and for most incidents geocoded to the city level and mapped according to fatalites. The map below shows where there are “concentrations” of incidents with high impacts. Other lower impact events are scattered all over Iraq and you can see this in geocommons by selecting Show Points and Shapes when viewing the “Violence in Iraq (2004 through March 2007) data set in MyMaps.

Gaining a Richer Understanding of the Problem

In the upcoming weeks, I will be taking a more fine-grained look at the World Wide Incidents Tracking data for Iraq. The data that was extracted for today’s blog includes unique identification codes that can be joined to subsets of the incident data based on any of the criteria present in the records. Future blogs wll examine how the spatial pattern of terror attacks in Iraq has changed over time, whether the location of hotspots differ by weapon of choice or nationality of the victim and any other interesting tidbits that surface from the datamining exercise.

Popularity: 3% [?]

The political blogs have been stirring over last weekend’s passage of a bill that expands the government’s authority to eavesdrop on Americans. The administration began pushing for the new legislation in order to better gather information on foreign terrorists. But opponents of the bill say it goes beyond the small fixes that were initially sought.

By changing the definition of “electronic surveillance,” the new law allows the government to eavesdrop on international phone calls coming or going from the United States without a warrant. However, this is only permitted when the government’s target is a foreigner.

Tony Fratto, a White House spokesman, stressed this point by saying that the objective of the new law is to give the government greater flexibility in focusing on foreign suspects overseas, not to go after Americans. “It’s foreign, that’s the point,” Mr. Fratto said. “What you want to make sure is that you are getting the foreign target.”

But the left isn’t satisfied with that rationale. And they’re expressing their frustrations with the Democrats.

Kevin Drum, a Washington Monthly blogger, feels the “Democrats pretty clearly got steamrolled on this.” He writes that negotiations were going smoothly until the language was changed in the final hours. “Democrats weren’t ready for it, and with Congress about to adjourn and no backup strategy in place, they broke ranks and caved in. The only concession they got was a six-month sunset in the bill.”

Jack M. Balkin, a constitutional law professor at Yale, who writes for The Balkinazation blog, places more direct blame on the Democrats. “The passage of the new FISA bill by the Senate and now the House demonstrates that the Democrats stand neither for defending civil liberties nor for checking executive power. They stand for nothing at all.”

If those frustrated with the Democrats want to focus their displeasure, they should take a look at the following map. It displays the locations of the 41 Democrats who voted in favor of the bill.

Popularity: 3% [?]

Today we are exactly one year out from the start of the 2008 Olympics in Beijing. Besides being general fans of the Olympics we have several employees training to hopefully participate in Beijing in the rowing events. They made a good showing a few weeks back at the Pan Am games bringing back medals – including frequent blog contributor Jen Reck with a bronze in the women’s pair.

With the large company interest in the Olympic games we thought we’d bring in some Olympic data to map as well as a perspective on recent controversy surrounding the games. Everyone is familiar with the recent medal power houses – USA, China, Russia – but which countries get the most medals for their population size. Bang for the buck, pound for pound, these countries standout for 1996-2004 games:

The Bahamas dominate with 5.04 medals per million people, followed by Cuba with 2.4, then sports loving Australia at 2.35 and Jamaica with 2.35.

The dark side of Olympic glory are the growing scandals surrounding drug doping for performance enhancement. There have many stories about the increase in drug testing for the Beijing Olympics. The United States Anti Doping Agency has said all Olympic candidates must be in the drug testing pool for the next year in order to participate. With all the attention on doping for the next Olympics many have focused on China’s history of doping transgressions and whether systematic doping has been eradicated from China for the 2008 games. To gain a perspective on the controversy I thought it would be interesting to map out which countries have the most doping transgressions. To do so we took the data from the Wikipedia page of sports people sanctioned for doping offenses. Bill geo-coded the data and did counts for each country. The results mapped out as such:

The map clearly shows that the USA dominates in athletes sanctioned for drug doping with 115 followed by Russia with 44, Italy with 24, and Germany with 22. China is well down the ladder with 12. So, is this a case of the pot calling the kettle black in the case of the US media pointing out Chinese transgression. The direct answer is yes – we have plenty of our own doping problems to worry about. There is though more to the story. The list points out athletes that were sanctioned not athletes that tested positive. According to a CBC article over 40 Chinese swimmers alone have tested positive for doping since 1990. There could likely be a difference between athletes that are reported as sanctioned to the public and athletes that test positive from a country. Since the Wikipedia data is based on public reporting of sanctioned athletes it could be skewed towards countries that openly reveal transgressions.

No matter how you slice it there is a doping problem across the globe and it has the potential to mar the Olympic games as it has the Tour de France. I’ll close with the question of how do we combat it. The recent announcements on increased drug testing illustrates the primary tactic of testing more people – increasing the pool of athletes. I spent 4 years myself in the USADA testing pool and I would argue that spending your resources on testing more people is not going to solve the problem. Simply because the doping occurs primarily with the top athletes not the bottom of the pile. Doping requires resources and money to fund it and mask it. The second and third tier of athletes rarely have the resource to successfully pull off doping so why spend your resources monitoring them. What always burned me when I had to deal with the hassles of testing – submitting your scheduled location for every day of the week and faxing updates whenever you deviate from that schedule for more than 48 hours – was that I was paying the price for the high end athletes that were cheating. The same athletes that had the money and resources to cheat system. I’d love to see more resources going after the top end of the sport, because lets face it if you are doping and coming in last place – who cares you have already received your punishment.

Popularity: 3% [?]

One of the natural questions to follow a tragic event like the I 35W Minneapolis bridge collapse is where are there other bridges that could suffer a similar fate. In our last post we talked about the National Bridge Inventory, the valuable information contained in it, and the difficulty working with it.

My original hope was to load up a dataset with lat longs for the dangerous bridges across the country, but after Raj spent many hours trying to sort out the geo-coding inaccuracies in the data set it became apparent that would not be possible. The latitude and longitude coordinates simply did not map to reality, the entire state of New Jersey was missing coordinates, and many time the last two digits of resolution were zeroed out. So, Raj aggregated the data to the next best level of resolution – counties. The bad news is you cannot tell where in that county the dangerous bridges are, but you can tell which counties have the riskiest bridges and if it is one you drive through. We are still working on trying to derive a finer grain picture and will definitely post those up if we can come up with something accurate.

Where are the the most dangerous bridges:

The top 5 most dangerous counties and the total number of dangerous bridges are:

Garfield Oklahoma 78

Attala Mississippi 45

Allegheny Pennsylvania 42

Washington Pennsylvania 37

Montgomery Pennsylvania 36

So, how was this all calculated? First we took the National Bridge Inventory and grabbed the safety ratings for all bridge’s superstructure, substructure, and decks (found here):

“The NBI database contains ratings on the three primary components of a bridge: the deck, superstructure, and substructure. A bridge deck is the primary surface used for transportation. The deck is supported by the superstructure. This transfers the load of the deck and the traffic carried to the supports. Within the superstructure are the girders, stringers, and other structural elements. The substructure is the foundation of the bridge and transfers the loads of the structure to the ground. The superstructure is supported by the substructure elements, such as the abutments and piers.”

For each of the key bridge components, decks, superstructure, and substructure we provided counts by county for the number of bridges by their safety ratings (ranging from “failed” to “excellent”). We also created three indexes: 1) dangerous bridges (the sum of the number of failed, imminent, critical, and serious bridges), 2) risky bridges (the sum of the number of poor, fair, and satisfactory bridges) and 3) safe bridges (the sum of the number of good, very good, and excellent bridges).

The embedded map show the number of dangerous bridges rated by their superstructure. In the Minneapolis bridge collapse the superstructure was rated “poor” and all the bridges mapped are bridges in worse condition by safety rating. This is just one slice of the data. The best way to see how your location rates is to head to GeoCommons and create a map by clicking the “mymaps” tab and adding one of the three datasets. Just search “bridges” or by type “superstructure”, “substructure”, “decks”. Once you’ve made the map you can also click on the “about this dataset” link and create top ten lists for whatever data attribute you think is most critical. We hope this allows a mechanism for the public to discover if there are dangerous bridges in their backyard.

Popularity: 17% [?]