Nuclear tests: a story

This project started over the course of the summer when reading about the 60 year anniversary of the Hiroshima bombing. A few infographics had been published presenting the tests that had preceded and followed this event.Screen Shot 2015-11-11 at 11.26.13

I started wondering about the data behind those infographics. Where they easy to collect (Nuclear testing could be classified for certain obvious reasons), which information would be available.

It turned out that Nuclear testing is a quite well documented subject. Quite quickly I have found some sources describing in details the tests that have occurred with dates, names, and various other metrics such as the power or the height at which the event happened, allowing me to have more insights on the topic.

At the same time, I was also taking benefits of the summer break to catch up on my blog reading list and was reading about the use of “scrolling” in data visualisation on Jim Vallandingham’s blog. Finding this format particularly useful for storytelling, I decided to try applying it to an example and what’s best than the data

I have gathered the information I needed to produce my story, focusing on the tests, the treaties and the number of nuclear weapons. Once I had a story line, I have produced the accompanying charts to go along the “story”.

The charts have been produced using mostly d3.js.

The scrolling format allows to go through the story in a natural way. The charts and texts evolve smoothly while you’re going down the page.

It is important to interact with the charts to get as much information as you can from them. Thus, the map (screenshot below) needs to be played in its entirety to realize how many test have happened, how often and where (you just need to play the yellow button).

The full story can be seen HERE (

The dark background has been picked intentionally in line with the topic treated. The first sentence in the text “Are humans really the only species willing to play with a technology they don’t fully comprehend and master?”, is a direct reference to a science-fiction comic that has marked me as a child:  Valérian, agent spatio-temporel and more specifically the Métro Châtelet direction Cassiopée and Brooklyn station terminus cosmos episodes.

I have also published each graphics individually. They can be seen at the following locations:

Let’s go to the countryside with cartoDB

I have wanted to start playing with cartodb for some time. This tool allows you to “quickly” make customised web-based maps.

I was thinking to map my daily commute to work, finding an application to register my geographic position at regular interval and then plotting the results with cartodb but I couldn’t help thinking it wasn’t the most the most interesting thing to display. So, I have opted to start searching data that could be of interest. From the commute idea, my mind has jumped to transportation and transportation in Paris mainly means subway. I have started searching geo data for the Paris station but early in my search, I have found data linked to the train network, if the data were not directly linked to what I had on my mind, the made me change my focus from Paris to France and from RATP to SNCF.

So I have started searching on the SNCF open data portal for data that could be of interest to me.
I quickly found the two following sets of data that cover most of the French train network:

The high speed train (TGV) data are missing but SNCF has announced they should be made available pretty soon. i’ll update my map once they are.

Once the data selected I have merged the data I needed thanks to the R dyplr package and have also merged the 2 datasets together (TER and intercité).

It was then just a matter of importing my data in cartodb, to georeference them properly and decide what to display and how.

Once thing I wasn’t satisfied with is the basemap offered by cartodb, but It didn’t really as it offers to customise your map by importing and adding layer elements to it or to import basemaps from other systems such as “Here, “Stamen” or “Mapbox”. I had already worked with the latest one so opted for it.

Buf if mapbox has offered me the flexibility to remove the information I didn’t need, I got frustrated by it as I couldn’t make the railway system appears before reaching zoom level 12. The only work around I can think of is to obtain the geographical information from the railway system and reimport them in Mapbox instead of using the default openstreetmap data. I’ll probably try it in a near future but if anyone has an idea, I am all ears.

Anyway the final map can be found below, the more intense the color the more trains are circulating this path. The purple color has been picked based on SNCF logo.

A last fact, SNCF operates on a railway network of about 29 901 km , which makes it the second most important national railway in Europe. (source wikipedia)

How was life? – Well-being across time

The OECD in cooperation with “clio infra” has just launched a new report measuring the quality of well-being over time (starting in 1820): “How Was Life?

To accompany the report, an interactive visualisation has been developed enabling you to compare the evolution of performances for  a set of 11 indicators and up to 160 countries. The indicators are GDP per capita, real wages, Education, Life Expectancy, height, homicide, polity, CO2, SO2 , Biodiversity and Income inequality.

The visualisation includes a “Play” function that transistions between the years. It enables you to notice some interesting trends such as the strong increase in GDP per capita in western economies starting in the fifties  or the constant increase in the number of average years of education.

If you would like to see the evolution for a given country you can select one. It is then displayed with a red dot to allow you to see its evolution more clearly.

Mouse over the bubbles to see a line chart of the country data.

All the data can be found at Clio Infra dataset.