While working on the soon-to-be-released map widget for Piwik (heck, it’s been over two years since the first sketches!) I implemented two map symbol clustering algorithms into Kartograph.js. Last year I wrote about why this is a good idea, and now I turned that advice into re-usable code.
In this post I want to share my findings after experimenting with different clustering techniques.
Icons are widely used in infographics such as maps and pictographs. So as a visualization designer, you’ll get to the point where you must choose which icons or pictograms to use. But please, choose wisely.
The reason I got to this topic is a recent post by Naomi Robbins about two opinions on the usefulness of pictographs. She reminded my of a critical article by Stephen Few, who stated that unit charts (another term for pictographs) are for kids, but not for serious information displays. My biggest complaint about his article is that he picked some of the worst imaginable examples to back up his arguments.
read how to do it better..
A few weeks ago, while I was driving several hours towards our camping vacation, I suddenly noticed this beautiful piece of data visualization right in front of me. Actually, I found it that beautiful that I had to remake it in Illustrator:
I was completely stunned by the clean and simple layout of this gauge chart. It shows everything I, as the driver, need to know such as: How fast am I driving at the moment, how far have I’ve been driving at all, when is it time to get a new car.
But then I realized that this tiny chart, despite its useful, intelligent design, violates some of the common rules of data visualization, so I thought it’s a good idea to write about it.
Lately I joined Datawrapper, an open source project that aims to provide simple, embeddable charts for journalists. Really, no fancy stuff here, we’re just talking about line charts and bar charts. Limiting ourself to those types gave us a good opportunity to think about the best of doing them. So it came that this week I was thinking a bit about the perfect line chart.
A while ago I realized that I totally stopped using social bookmarking services since I started tweeting. Whenever I find an interesting link I share it on Twitter. If I find interesting links tweeted by the people I follow I’m most likely to favorite that tweet. I guess that’s the way most people use Twitter. How often did you check someone’s public links on delicious? I rarely did.
This is going to be a quick run-through the creation of the latest Kartograph showcase which is a high res vector map.
Over the last two years, cartography has drawn my attention from time to time. In 2009 I started my work in the field by porting the PROJ.4 library to ActionScript. My first notable interactive map application was a world map widget for the Piwik Analytics project, which is in use until today. It was born from the need to have a simple world map that is lightweight, easy to use and completely independent from external map services like Google Maps.
In his great blog The Daily Viz Matt Stiles recently posted this map of US crime rates. The map shows murder rates in different cities as bubble symbols and it strongly reminded me to write about the problem of overlapping map symbols.
So, what’s the problem here?
As some of you pointed out in the comments of my last post, taking equidistant colors in the HSV color space is no solution for finding a set of colors that are perceived as equidistant. This post describes what’s wrong with HSV and what we can do about this. Note that since this post contains interactive elements built on the latest web technologies, you might need a modern browser to get the most out of it.
click here for ultimate color geekyness
Over the last week I had some fun playing with choropleth maps. Thereby I analyzed the following US poverty map, which was recently published at the Guardian data blog:
To be honest, the first time I saw this map I didn’t thought much about it. Ok, poverty is highest in south central of the United States, especially near Mexican border. But recently I used the same data to demonstrate a choropleth map that I created from-scratch and I was really surprised to see a somewhat different picture:
click to dig into the world of choropleth maps..