I just received the new information design book from Taschen:
“Information Graphics” by Sandra Rendgen, edited by Julius Wiedemann.
I am happy to have 1 infographic included in it.
When I received it, my first reaction was, “This book is gigantic! :)”, it is, indeed, with it’s 480 A3 pages, and the huge amount of information in it – in the form of essays and of course, diagrams and infographics – which are very easy to be read because of the size of the pages, and some of them even expanding on 4 pages, folded within the book.
I definitely have a lot to learn from it!
The book launches Monday, April 16th at Taschen’s London store (12 Duke Of York Square in Chelsea), but it’s already a big success, as it is the #1 pre-orders at Graphic Books on Amazon.
Below I’ve added a link where you can buy it from Book Depository, as I prefer it, simply because they sell books with free shipping anywhere in the world.
How to play: drag the sliders. Go to the end of the sliders to exit and be able to explore another slider, or when you see the >> marks, go there and explore further.
It is also a work about data visualization in general, as I was exploring the relationships between different type of graphs, and how the information can flow, naturally, from one type of graph to another, in this case, from a flow diagram into 2 pie charts. To emphasize this, I chose to make it in traditional media (paint and paper); Then I had to bring it back into the digital world and program the interaction, so you can see it.
There is so much creativity in this book!!!
My entry for the Information is Beautiful Awards – First Challange, a visualization about the world’s non-renewable resources – how long might they last?
Switch the buttons “Grows” and “doesn’t grow” to view the estimates of years ramaining for these minerals and fuels, if the production continues to grow at the rate it grew in the past 10 years; and what difference would make if we were not going to increase the production.
My entry for the UN Global Pulse – Visualizing the voices of the vulnerable challenge on visualizing.org.
Optimized for HTML5 supporting browsers, specially Firefox. In Safari browser the arrows don’t work well, please scroll with your mouse instead.
View the visualization.
In the – Country’s Economy vs Meeting your Household Needs – graphs, I showed also the relationships between those answers. This might give us a clue of the relevance of the answers, because those who answered that the economy is much worse but they do better at their household might have a reason not related to the global crises for doing better, or were too subjective.
The part about – Relevant things that people talk about – tries to capture the pulse of the surveyed people about dealing with the household problems and about their quality of life (I chose to treat these to questions together as the answers completed each other in very many cases, the quality of life is also explored further in the graphs below this section). Many answers contained information about more than one issue, therefore they were included in many circles.
The whole graph is not a breakdown of what % of the population thinks or does, it’s actually more similar to a word cloud, it’s an issue cloud. Also, I have included some issues that appeared only few times but I believe some of them are relevant and may give important clues about what the majority talked about, but didn’t mentioned it.
A special case it’s Ukraine, where about 2 thirds mentioned the word “Change” with different attitudes, (from No change, to a change is highly needed, a change is visible) and many more talked about it with other words. Only few said “A change of power” or a “Change of government”, “Justice for the people”, although few, I believe they are very relevant and give “Change” a political meaning besides the economical one.
In order to make the wordclouds about the future, I had grouped together similar words (like change and changing), treated as an expression groups of few words that had a meaning like that, and regarding the answers that were phrases with many words, I had included them in the one word that summed up best the phrase (not necessary written in the phrase, but had the meaning of the phrase). For example, in India, many people told what profession they want to have in future, I grouped them as “profession” so that their plans about careers would show up in the cloud.
My data visualization for Visualizing.org‘s Visualizing Urban Water Challenge.
A view of almost each country’s available freshwater resources, compared to the freshwater withdrawal; water per capita, the percent of urban and rural population, and what percent of them have access to improved drinking water and improved sanitation, and an estimation for urban population growth in 2030 in this context. The data is arranged as a generated water drop, with mugs (representing the population with access to improved drinking water), or baths (for sanitation), which contain as much water as the percent of population who has access to them, for each country.
How to use it:
Select a country in the drop-down menu (they are ordered by continents and alphabetically).
Now the water-drop is generated.
The left side of the mug (or bath if Sanitation button is clicked) represents the rural population, the right side mug (or bath) is the urban population.
They are resized according to the urban/rural population percentage for 2010, and also the estimation for 2030 (click play button under Urban Population Growth).
How much of the mug (or bath) is in water – this represents the percentage of population who has access to improved drinking water (or sanitation), what is above, doesn’t.
The freshwater, withdrawal bars compare the quantity of water withdrawn against the total renewable freshwater resources for that country. It corresponds to the water level in the water drop, unless the difference is to big to be viewed well, when that happens the water drop has a bigger frame, indicating there is more water than shown.
The Water per Capita includes the water directly used by a person, and also indirectly used, in agriculture and industrial sectors.
When some data is missing, the indicators show 0, but the drop shows a default value instead.
A new data visualization I made. Life expectancy for people born in 1990, 2000 and 2006 in various countries over the world, each continent’s highest and lowest life expectancy. First graph is a view through the 1990s – 2090s timeline, while the second one shows the same data, viewed by age. And a graph showing the increase/ decrease life expectancy patterns for those countries.
The data comes from visualizing.org a new data viz online platform that launches today (1st Oct. 2010) at the Cooper Hewitt Design Conference in New York (live stream, the gallery of data visualizations is @2pm EST (9pm Romanian time)).
Here is a link to the Data set.
My entry for the The Brian Lehrer Show
– Map Your Moves: Data Visualization Challenge. The data comes from a Census survey in which nearly 1700 people responded, which asked when, why, and where each person has moved over the last 10 years.
I chose to deal with all the data between 2000-2009, and explore these entries, apart from the zip codes. For the Trends chart, on the right, I’ve interpreted the explanations for the initial reason “Other” and moved to the more apropriate reason, such as: those who said they moved from rent to owners -> Can afford a better place, or divorce -> Roomate or Relationship problems. Also I added the “Love or Marriage” reason, because it was a common explanation.