Alex Reid

Last week, Jesper Andersen was talking at the Strata Data Conference about how to build a “data narrative” using social media and online information to tell a story about a neighbourhood.

He focused on San Francisco’s Haight Street and with the public information from government open data, mapping data, real estate, rental listings data with data from social services like Foursquare, Yelp and Instagram.

He looked at the safety element by finding the crime statistics from DataSF.org, and looked at an analysis of Tweets and found that, by distribution, people were more negative on the lower half of Haight. He was also able to see what people found interesting on Haight by mapping pictures from Instagram to the street as well to offer a creative Google Street View.

Story of Haight

It’s not the next Google Street View but it does offer hope inspiration to mobile application developers to use open data and social media data to tell a story.

Car accidents are a leading cause of death, especially for younger people.

In 2005, the UN said that the number of road traffic deaths and injuries would exceed the damage wrought by HIV by the year 2020. The World Health Organization (WHO) predicted that that road traffic injuries will rise to become the fifth leading cause of death by 2030.

Most of all, it’s human error that often causes accidents.

Nevada became the first jurisdiction in the world to allow autonomus vehicles on public roads last month. For the past few years, DARPA has been driving (no pun intended) towards driverless vehicles (think robot soldiers), and Google was behind the lobbying so that they could test their driverless project, which won the 2005 DARPA Grand Challenge.

Sebastian Thrun on Google’s driverless car (Youtube).

Google wouldn’t say why they choose Nevada, and while it could be that the Google founders like Burning Man, the state is known for its testing grounds – nuclear weapons and rocket cars.

Google has ben testing a fleet of seven vehicles, consisting of six Toyota Prii and an Audi TT. Their software drives the vehicles at the speed limit it has stored on its maps and maintains its distance from other vehicles using its system of sensors. The system provides an override that allows a human driver to take control of the car by stepping on the brake or turning the wheel, similar to cruise control systems already in cars. (source)

Most auto technology already uses sensors and cameras, but most of the advances available have simply been corrective or assisting technologies like the “Lane Keep Assist” ability of the 2010 Toyota Prius that uses a camera to detect lane markers and automatically steers the car toward the center of the lane.

Google says they’re just playing around with the idea, and no matter the commercial value of such an idea, the social benefits alone in preventing car accidents, by drunk or other human error, is an idea beyond worth merit.  I see this as a positive alternative for drunk drivers, but chauffeurs might be out of work soon.

Safety is the sell here, and it may still be simply an assisting program, but even with the risk of computer error, I see huge potential for this to revolutionise the auto market and save lives.

Somehow I suspect the built in GPS sytem will be Google Earth.

Here’s a good web site that I’m suggesting to my West Coast friends:

http://72hours.org/

Eric Fischer created two series of major world city maps showing where people take photos, using geocoding information from Flickr and Picasa. In his first series hosted on Flickr, titled The Geotaggers’ World Atlas, he used geo tagged photos over a nine day period in late May 2010 to show a heatmap of where most photos were snapped.

A week later, he created a second series over a five day period in early June 2010, titled Locals and Tourists giving the city maps more depth by comparing “tourists” to “locals”.

He explained:

Blue points on the map are pictures taken by locals (people who have taken pictures in this city dated over a range of a month or more).

Red points are pictures taken by tourists (people who seem to be a local of a different city and who took pictures in this city for less than a month).

Yellow points are pictures where it can’t be determined whether or not the photographer was a tourist (because they haven’t taken pictures anywhere for over a month). They are probably tourists but might just not post many pictures at all.

Purple would obviously be the merging of both tourists and locals.

Of course, these only count those photos that were geo-tagged and posted on Picasa and Flickr publicly. But the series gives you a great idea of where to go on vacation, where the locals go and if you’re thinking of opening a camera supply store, where to setup shop.

For me, this is a big help as I have a planned trip to San Francisco in a couple months and it’s also quite inspiring; data visualization made art!