This week I was helped to discover that my interest is in data visualization. So with this post I want to give my readers and interesting insight of the topic of data visualization. Of course not the topic as in general, but more like something that caught my interest during this week.
I tipped over a quote of Grace Dobush, who said:
“What’s the big deal? Everybody’s doing it, right? If you put [Infographic] in a blog post title, people are going to click on it, because they straight up can’t get enough of that crap. Flowcharts for determining what recipe you should make for dinner tonight! Venn diagrams for nerdy jokes! Pie charts for statistics that don’t actually make any sense! I have just one question—are you trying to make Edward Tufte cry?”
For me personally data visualization has always been a tool that enables us as humans to get an better understanding of complexity by just simply visualizing it.
So where is the problem here?
According to the “Gurdian UK” data visualization tools like “Wordle” had been designed as an academic exercise that had turned into a common way of showing word frequencies over the past years.
Furthermore, it claims that during the past years the supply of data visualization tools that were free has not been that much as it is now. And compared to what we are being offered nowadays is more “fancier” and also more diverse. As a result of this people have been tending to make data visualization look less and less nicer.
But we still want to keep on using data visualization tools. Ian Lurie is on the opinion that more people want to easily follow a story that is being told visually then being told verbally. And it is nothing wrong with that. But it is important to not get excited and overzealous about what data visualization tools offer to us.
So here are some advises for everybody they should consider when working with data visualization:
In recent times 3D animations and pictures have become more and more popular. They are associated with a high degree of fanciness and we love to use them. But we have to be careful when using them. Fanciness does not always lead to fancy story telling. 3D data visualization can create more work, because more data or information is needed, since you now have another axis that has to be filled up with the right information.
Colors and Data Visualization
Some of us might feel, the more colors the better. Well when it comes do basic data stick with a basic amount of colors. Too many colors for the certain data set will only lead to confusion and nobody wants that. Keep it simple and stupid actually fits in here perfectly.
And here I have another example:
The information based in this picture is based on the data given at this website.
1. The term destiny is here not clearly defined.
2. The circles represent the amount of fatal accidents. Using the USA as an example this picture states a number of 2613 fatal accidents. But do we know how many flights were flying to the USA? In fact do we know how many flights were operating in general? This picture might lead to misjudgment for example thinking the USA is a dangerous place to fly to.
3. Do the dots stand for the certain city or the country itself? (see Europe)
After this week I have learnt some more on data visualization and I hope you have, too. It is always good to put yourself in the position of a listener who does not want to be shocked with a chart that contains all colors of a beautiful rainbow.