Today I got the following email from Ragaar, one of my readers: “Congratulations! Your blog is in the big six, according to eagereyes.” I checked the link and found that Robert kindly included me in his Six Niche Visualization Blogs and said nice words about FILWD.
That’s fine and great of course, but the event also made me realize that new readers might not easily get a full picture of what FILWD is all about and what it has to offer. Plus I have the feeling many of the regular readers too might not know what’s the idea behind it, so I thought I could indulge, for one time, on a self-referential posts. But before I move on to the post, let me send two important messages.
@Robert: EagerEyes is the only blog that convinced me it was possible to write a successful blog about visualization without necessarily showing pictures all the time. Thanks!
@Ragaar: I cannot express with words what it means to me to receive such an enthusiastic email from a reader because MY blog was mentioned in a more famous one. That’s well beyond my expectations. You made my day.
Why should you read FILWD?
I know, I know … this looks like a message coming from the marketing department. But there’s no marketing department here, only me behind a screen.
- The world is flooded by data.
- People love visualization because it turns (boring) numbers into flashy images.
- Thus they take data, throw colored pixels on the screen, and call it visualization.
- But visualization is much more than eye-candy and few people know it or realize it.
- Many are jumping on the wagon but don’t know where or how to start, so they just start and throw pixels.
- If they type “visualization” in Google or anything similar they are redirected to famous blogs with thousands of flashy images but almost no guidance.
- Academics have been studying visualization for a long time but people jumping on the wagon don’t know what they have to offer and how to access it.
- Visualization users have specific needs that academics ignore. Plus academics have a deep faith on their knowledge but visualization theory is really really limited.
- People need more guidance.
- People need to be told that visualization is much much more than flashy images.
- Visualization users and academics need a bridge.
FILWD aims at addressing these consequences, based on the aforementioned facts. If you like this plan jump on the wagon and let’s do this journey together.
Most popular posts
Now that you know what FILWD is all about let me guide you through the most popular posts I have had since I started 7 months ago. These might not be my favorites but I have a religious respect for the crowd and if people liked them so much there might be a reason. So here we go.
- 7 Classic Foundational Vis Papers You Might not Want to Publicly Confess you Don’t Know – When I saw how people reacted to this post I was blown away, I could not believe it. This is still by far the most successful post I have ever written and it continues to attract people every day. Currently it has 168 tweets and 22 comments. I cannot tell why it is so popular but I can tell that this is the prototype of the kind of contribution FILWD wants to give. From day one my focus has been on bridging the divide between what people do in academia and what people out there need in terms of visualization. If more people read this stuff, everyone will profit from it.
- How to become a data visualization ninja with 3 free tools for non-programmers – This is a very practical post. I think part of its popularity is due to the sexy name. Nonetheless, the main message of the post, regardless the fact that it point to some real, useful, and free tools, is that data visualization is a lot about data manipulation before anything could be visualized. The post just gives you an entry point to make the whole thing less cumbersome.
- How to Become a Data Visualization Expert: A Recipe – I am sure there are lots of people who are interested in becoming visualization experts today. That is really great! But there is also so much noise that I think it is really really hard to trace your own path in such a mess. This post is intended to help a novice take the right path in this amazing world.
- How do you visualize too much data? – This is a technical/academic post. A very large number of visualizations we see on the web have very low data density. But people is confronted every day with tens of thousands or even millions of data records. How do you visualize them? The post gives some initial suggestions on which tactics can be used.
- Demystifying Cargo Cult Visualization: You Cannot Visualize 3 Variables by Mixing 3 Colors – This is a “rant” kind of post, but supported by some hard visualization theory. I must admit I was a bit afraid when I pushed the “publish” button of this one. The whole post is an open criticism to a visualization published by the SEED magazine (and it was pretty tough!) but it really was meant to be used as a concrete example to convey a deeper message: in order to design innovative visualizations you have to know the science behind it before.
- Can visualization influence people? I mean can we prove it? – This is a recent one. A very candid one admittedly. The question was originally posed by a guy attending an invited talk I gave at the IDRC in Canada and to whom I could not give a satisfactory answer. So I thought I could just “crowdsource” it and see what the answer would be. Luckily, I received lot of comments. And these comments are the real wealth of the whole post.
- Why Visualization Cannot Afford Ignoring Data Mining and Vice Versa – I think there are a lot of data mining guys out there who are increasingly looking into visualization as a way to solve some of the problems machines cannot solve. On the other hand visualization cannot really handle problems with very complex data without the use of automatic techniques. The post summarizes the main issues and suggests ways and reasons for a tighter integration.
Few reflections on the popular posts lists
- You guys seem to like when I posts things starting with “How to …”. This is not new. It’s a very well known fact that how-to posts tend to attract people. Nonetheless, it also demonstrates that many of you are in need to learn the basics of visualization, and this is another fundamental premise of FILWD.
- The fact that the most popular post is one with a long list of research papers is a big revelation for me. I always suspected that people interested in visualization need to better know what research has to offer, but I could never imagine such an interest. This is a big call for those who, like me, write about visualization: there are people out there that are interested in more than flashy graphics and animated bubbles!
Most underrated posts
There are a couple of posts I think deserved more than the attention they received.
- InfoVis Makes Us Cyborgs – In this post I was trying to explain how visualization is a natural development of the way the world is changing and that it can bee seen, as well as other technologies, an extension of our mind. My guess is that the article was too hard to digest and far from the needs of the readers. But, if you would like to give it another try I think it could be worth it.
- When will we decide to provide lots of value? – This one is a call to action to all my fellow bloggers or the aspiring ones. As I said above, people are desperately in need of good quality sources and it’s our responsibility to make them available and easily accessible.
Why do I write FILWD?
There are a number of selfish and narcissistic reasons for having a blog of course, and I am not immune to that. But let me tell you that the biggest satisfactions I had from writing this stuff so far is the number of enthusiastic messages I received and keep receiving from people saying that they desperately needed some of the things written here. There is nothing better for me than knowing I am useful. In the end this is what FILWD is for me: doing something useful for other people.
What do you want from FILWD? Speak up!
Now it’s your turn to speak. What do you want to see in FILWD? Is there something special you would like to see here? Is there anything you did not like? Do you have suggestions on how to make FILWD more useful to you? I am happy to hear. You can write a comment below or send me a message on twitter.