Assorted Links

1. Taking Data Visualization From Eye Candy to Efficiency
   
   
2. Fuck Nuance, a manifesto for more bold social theories, by Kieran Healy (via Analise Real)
   
   
3. Machine Learning Classes at Oxford (videos, presentation and code)
   
   
4. 2015 Ig Nobel prizes: a study shows that nearly all mammals take the same amount of time to urinate (about 21 seconds)
   
   
5. There is a Space Syntax Toolkit for QGIS (ht Renato Saboya, who runs a great blog about urbanism written in Portuguese: Urbanidades)
   
   
6. 10 things you need to know about the Magna Carta
   
   
7. Slum tourism and its discontents. Not exactly a new article but a good summary of arguments (ht Fabiana Freitas, my lovely partner)
   
   
8. The Value of Democracy: Evidence from Road Building in Kenya [unagated paper]
   
   
9. The Human Mortality Explorer. Visualizing Death across Time and Space via (Bernardo Queiroz)
   
   

How much do Americans drive compared to other countries?

This comes from a new report published by LSE Cities. Commentary  by Richard Florida and Aria Bendix here.

Annual vehicle kilometres per person against wealth levels: 1970-2008

click on the image to enlarge it

Urban Picture

Delirious New York, by Ezra Stoller.

Headquarters of the United Nations, NYC

soundtrack: one of my favourites from Kermit

The Human Hemisphere

We have seen Bill Rankin's inventive map of the World Population Distribution by lat long. More recently Bill has come with other ways of thinking our hemispheres. Here is my favourite one.

ps. On a related topic, here is map showing how geographically unbalanced the distribution of the world population is.

[image credit: Bill Rankin, 2015]

Redefining Urban Futures

Nice presentation by Kent Larson summarizing some of the projects they have been developing at MIT Media Lab and that are contributing to redefine the future of our cities, in some way.

I wouldn't say these ideas are new, revolutionary or even disruptive in a way that will solve the most pressing issues in most cities for every one. However, the work of Kent and his team make an enormous difference in bringing these ideas closer to reality.

Before there was ggplot

Before Hadley Wickham was born, when there was no ggplot, this is how people used to create maps using small multiples (nice example here).

Results of the US Presidential Election from 1789 to 1876, published in 1877

Transport disruptions, big data and travel behavior

A new discussion paper shows how a strike in the underground system of London could actually improve general welfare and make individuals' travel behavior more efficient. (via Tyler Cowen).

Larcomy, S., Rauch, F., Willems, T. The benefits of forced experimentation: striking evidence from the London underground network. University of Oxford. Department of Economics Discussion Paper Series (Ref: 755 )

Abstract: We estimate that a significant fraction of commuters on the London underground do not travel their optimal route. Consequently, a tube strike (which forced many commuters to experiment with new routes) taught commuters about the existence of superior journeys -- bringing about lasting changes in behaviour. This effect is stronger for commuters who live in areas where the tube map is more distorted, thereby pointing towards the importance of informational imperfections. We argue that the information produced by the strike improved network-efficiency. Search costs are unlikely to explain the suboptimal behaviour. Instead, individuals seem to under-experiment in normal times, as a result of which constraints can be welfare-improving.

The researchers examined 20 days' worth of anonymised Oyster card data, containing more than 200 million data points, in order to see how individual tube journeys changed during the London tube strike in February 2014.

Here is a very interesting point to emphasize and that I'm sure cartographers will like: "The London tube map itself may have been a reason why many commuters did not find their optimal journey before the strike. In many parts of London, the actual distances between stations are distorted on the iconic map. ... the researchers found that those commuters living in, or travelling to, parts of London where distortion is greatest were more likely to have learned from the strike and found a more efficient route."

Soundtrack:

The shifting patterns of how Londoners live and work

Here is an interesting piece about passenger trends in London’s Underground system since 2001 and how this piece of information helps us better understand how the city's economy is changing (I saw this via Iain Docherty).

One obvious change in passenger patterns captured by this chart shows the notion of 'peak time' has widened over the past fifteen years or so. As the article suggest, this is likely a reflex of some of the changes observed both in the labor market (with the increase in the number of workers that are self-employed and have more flexible time shifts) and in the housing market, where the prohibitive housings costs of London are pushing people farther from the city.

Assorted Links

1. The changing gap between male and female life expectancy in the UK
   
   
2. Till Nagel is starting a collection of bike visualizations (maps, flows, timelines…)
   
   
3. Great piece at The Economist on the role of land in modern economies and the role of housing wealth in rising inequality ht Leo Monasterio
   
   
4. A real-time map of cyber attacks via @flowingdata
   
   
5.  Nice interactive version of Schelling's Segregation Model in JavaScript
   
   
6. London's historic road network from Roman Times to today
   
   
7. Other things I'd rather be doing
   
   
8. A new tool from Google can estimate the total sunlight a rooftop receives throughout the year
   
   
9. Visualizing usage patterns of the bike sharing scheme in Philadelphia, by Randal Olson

Returners and explorers dichotomy in human mobility

Pappalardo, L., Simini, F., Pedreschi, D., Barabasi, L. et al. (2015). Returners and explorers dichotomy in human mobility. Nature Communications, 6. doi:10.1038/ncomms9166

Abstract:

The availability of massive digital traces of human whereabouts has offered a series of novel insights on the quantitative patterns characterizing human mobility. In particular, numerous recent studies have lead to an unexpected consensus: the considerable variability in the characteristic travelled distance of individuals coexists with a high degree of predictability of their future locations. Here we shed light on this surprising coexistence by systematically investigating the impact of recurrent mobility on the characteristic distance travelled by individuals. Using both mobile phone and GPS data, we discover the existence of two distinct classes of individuals: returners and explorers. As existing models of human mobility cannot explain the existence of these two classes, we develop more realistic models able to capture the empirical findings. Finally, we show that returners and explorers play a distinct quantifiable role in spreading phenomena and that a correlation exists between their mobility patterns and social interactions.

[image credit: Pappalardo et al. 2015]

The recent story of my life

I saw this via Arthur Charpentier, who has remarkably good twitter and blog you might like.

[image credit: the unmistakable xkcd]

How I feel trying to learn Python

Some useful sources:

• Digital Geography
• Geoff Boeing
• Yhat, Inc.
• Datapolitan
• Daniel Forsyth
• MITx: Introduction to Computer Science and Programming Using Python

Where Are the Syrian Refugees Today?

Hans Rosling (aka the Mick Jagger of statistics) in an informative three-minute video about the Syrian Refugees.