Remember this the next time you see some statistics. Or a report. Or anything that appears on Wikipedia.
Starting today I will be visiting CERN, the Conseil Européen pour la Recherche Nucléaire with 11 other STEM social media advocates. What is CERN? It’s the location of the Large Hadron Collider and the birthplace of the World Wide Web. From the CERN Website:
At CERN, the European Organization for Nuclear Research, physicists and engineers are probing the fundamental structure of the universe. They use the world’s largest and most complex scientific instruments to study the basic constituents of matter – the fundamental particles. The particles are made to collide together at close to the speed of light. The process gives the physicists clues about how the particles interact, and provides insights into the fundamental laws of nature.
I will be sharing facts, images and videos via this blog and other social media.
I will be tweeting about this event a lot using the hashtag #CERNTweetup. If you aren’t interested in this sharing, you can use the filtering mechanism of your Twitter client to avoid those tweets.
…or your can use the search feature of your client to follow the tweets of all the invitees. Isn’t metadata great that way?
Today’s SQL Server 2012 Anniversary question is:
I thought the image I created above might inspire you.
Follow @SQLServer on Twitter and answer their daily questions to win fame and prizes.
I’m no expert in graphic design or data visualizations. I do know that pie charts are evil, as are most gauges and uses of 3D in dashboards. However, when I saw this bar chart from the fine folks at Klout, I knew it was a winner. Even the name of this category is wrong: Top Influential companies? No, from their description, this is a list of companies that were most talked about the most often. That doesn’t make a person or an organization influential. Otherwise, I’d be dressing like Kim Kardashian and collecting Justin Bieber dolls with weird "try me" portals.
At best, these companies influenced people to say things about them by doing something well…or in the case of Netflix, doing a lot of things poorly. But they didn’t do the influencing. People on the social networks did.
This data visualization is a list of companies who were most talked about…so they’ve used a bar chart. Bar charts are supposed to be used to show quantities, usually over time or some other measure. But this ranking is not a quantity. In fact, the bar chart is emphasizing the wrong thing, too. Notice how 11th place Facebook has more bar? But it’s in the worst place in the list. Or is it? We don’t know because the bar chart is showing us conflicting information. It could be that the top 11 companies are being ranked 11-1 in descending order based on their
influence mentions. From the list, I’d think think that the influence was descending, but I don’t know. If someone doesn’t know and the visualization adds no more insight than just a list of the companies, don’t add a chart.
Jen Stirrup, BI expert and Microsoft MVP, has some more to say about bad bar charts.
Don’t use bar charts to show rankings. Put down your data viz tool and take a walk. Notice the real world around you, then come back and think about using visualizations to help a reader understand the data better. That’s how to love your data.
One of the more fun types of data is image data, both meta data and actual images. So I turned to Google Maps and Bing Maps to see what various sites at the Kennedy Space Center looked like. Here’s a launch pad from Google Maps. You can see the boosters there.
Then there’s this image of the Vehicle Assembly Building (VAB). At first I was confused why part of this area was blackened out, until I realized the dark area is the shadow from the VAB.
You would probably recognize this building better from these NASA Photos:
And Bing’s Birdseye view of the launch pad, VAB, and viewing area:
The first visualization I saw of the VAB area caused my brain to jump to: "wow, they’ve blacked out some of the Space Center" when all that was going on was a perfectly natural occurrence of sunlight and shadow. I find it interesting that that different views of the same locations (via two different data services, Google and Bing) gives me a different understanding of the same places. There seems to be a lesson there in displaying the same data in many different ways.
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