Gold Nobels, no degrees
Giorgia Lupi, Simone Quadri, Gabriele Rossi, Davide Ciuffi, Federica Fragapane, Francesco Majno
We are flattered about the recent gold medal we won at the Kantar Information Is Beautiful Awards 2013 with our “Nobels, no degrees” data-visualization originally published for La Lettura and part of our data-visualization gallery.
I take the chance to explain it a little bit more.
It is a rich narrative that explores Nobel Prizes and Laureates from 1901 to 2012.
We visualized the prize category along a timeline, with these parallel “scores”, within these 6 main rows highlighted by colors,
(red for chemistry, blu for economic sciences, green for physics, yellow for literature, purple for medicine
and orange for peace)
Each dot represents a Nobel laureate, and each guy is positioned according to:
– the year the prize was awarded
– and his or her age at the time of the award,
…so highlighting how old you should be to win the prize, eventually!
Per each category we also draw a line indicating the average age for the category and the average age for the total of the Laureates.
We then used the main axes of the visualisation (i.e. the spatial layout) to provide some aggregated information.
Arcs here represents principal universities of Affiliations of Nobel per each category and the distribution.
Interesting is that Chemistry (red) Physics (green) and Medicine (purple) are spread among the 7 main universities,
while Literature and Peace’s nobel laureates (yellow and orange) quite didn’t attend the Top Universities.
Other aggregated information: bar charts here within these two “parenthesis” represent their average grade level per categories
(if Phd or not even degreed), and you can learn that if you want a Nobel in Medicine or Economic or Phisics, well you should seriously think about aPhd, while you can try without that for literature and peace.
double rounded dots represent women (actually not so many out of the total)
This charts below represent the most frequent hometowns out of the total, coloured per category, and aggregated per 30 years.
Interesting is that, lately, if you are born in the US you are more likely to catch the prize, while at the beginning of last century, the most of the scene was European.
We also have some curiosities highlighted, some primates and particularly relevant information we found, some “personal stories”: like Marie Curie winning two nobel prizes, Or the oldest winner was 90, while the youngest was 24, and so on.
And, finally this is the “how to read it part”, when we used the visualisation main shape as a base to give readers information about how to play around.
Coming to the visual inspiration that we had, I always try to encourage to take inspirations not necessarily from existing data-visualization (as I explained in my Eyeo Speech) (and as I pursue with my Pinterest references’ boards)
Moreover, I’ve been always so fascinated from musical scores and their elegant aesthetics. Many many times I would find myself simply replicating shapes / lines and connections / referring to the musical panorama, with no real idea what I am doing or with no purposes at all.
I also really visually love all of the so called “graphic music notation“, That uses non-traditional symbols and colors to convey information about the performance of a piece of music, to express what should be played / when and how.
And John Cage, a famous contemporary composer and its visual explorations on contemporary scores.
I guess I don’t need to say more, maybe. Can you spot some similarities with the visualisation I was showing before?
Above is just a quick overview of the first sketches, when I tried to simply follow this idea of building parallel scores helping highlighting some differences we noticed within the data; and then the visualization was already pretty clear to us.
Above are some intermediate stages, when we started doing it digitally. Lots of people asked us why we “rotated” the visualisation. To be honest, the lack of space played its role on that choice, but this rotation we tried while fitting everything into the art board, isn’t it just incredibly more elegant and beautiful? We then took this bold choice to present it this way.
If you want to learn more about our process, take a look at the Non-linear Storytelling: Journalism through “Info-spatial” Compositions article I wrote for the Parsons Journal of Information mapping, and send me your notes and comments!