The goal of the Vibrant Data Project (#vdat) is to enable a massive democratization in our collective ability to convert data into personal and social good. How can we enrich a Vibrant Data Ecosystem that increases access to economic opportunity, protects civil and political rights, improves environmental sustainability, increases human health and wellness, and sparks radical advances in science and education?

Automating the Creation of Infographics

Over the past few years I’ve had a few of my infographics spread around the web in interesting ways.  Some have gone viral on social media channels, others have been picked up by people for use in their slides, while others have been published or referenced by journalists. That has lead to a great deal of interest in the subject matter, but by far, the most common thread I’ve observed is from people who want to create visualizations of their own data.  

Usually they have little to no budget, but are so sick of looking at the hieroglyphics that only their PhDs can understand that they are willing to try something else.  Don’t get me wrong, there is absolutely a need for the intricate designs that appeal to experts and academics, but sometimes relating that information to people outside of that domain of expertise is not as easy as it could be.

However, developing infographics is at the same time nuanced and slow, as it is complex and meticulous.  And there I’m only talking about static work – the path to learning R or Flex and creating heatmaps like the image below is even steeper! 

Over at my company metaLayer our dashboard product includes a visualization suite. Some of you may be wondering just what will be available in that suite.  Well, here are a some sneak peeks of the type of visualizations we’re working on. 

These are just different ways of visualizing the incredibly difficult contextualization features we’ve developed for our platform, but they’re necessary if our goal is to make such complicated information collection more consumable. 

Anyways, here is a sneak peak of some things I’m working on.  You’ll have to visit blog.metalayer.com for more details about how and when these will be integrated. (Hint: Soon.)

The stacked area graph is a common chart in many programs.  The concept is simple, the columns represent periods of time, while the colors represent one measure of value, and the area of the stacked shapes represents another.

One that harkens back to my days as an audio engineer (it looks like a sine wave visualization). Using the same concepts illustrated above, this densely packed visualization can allow you to look at a set of information, a subset of that information and comparate it to a completely disparate type of information (the line in the background). It’s best when used with excessive datasets to spot trends over time.

There are quite a few more that we’re working on, and you’ll find news about their release here.

A Tale of Two Infographics

Over the past few days I’ve received a few emails asking me if we produced this infographic which has been republished and referenced by Microsoft Social Media Manager Rob Wolf on The Next Microsoft Blog, by Steve Clayton of PSFK and others:

No we didn’t.  Actually this was created by someone named Jonathan Good at a different startup called 1000Memories whom we have no affiliation with.  

The confusion is with this infographic we published about two weeks before Jonathan’s on a number of sites including Quora, Flickr, and Visual.ly:

I suppose the section that people are finding similar is this section:

Needless to say, we’re flattered by the similarities and the enthusiasm you’ve had for reaching out to us.  However, we wanted to clarify that the graphics aren’t from the same source or research. 

1000Memories’ research is great and goes way farther than we did to estimate all the photos ever taken, where we were only concerned with the size of the photosharing market. They even emphasize the need for the findability of images, a problem that we’re attempting to solve at metaLayer.  There’s other differences in the two images as well: from the math used to scale the size of the rectangles in their graphic, to their inclusion of the number of photos taken each year, including analogue photos.

 

Anyways, we find the work of 1000Memories equally interesting as it’s made for some nice conversations about our technologies which aim to solve the problem of making photos more easy to mine for meaning.