Data Visualization: 2013 Week #1

For the first week of the New Year, Data Community DC is expanding into a natural extension of its current outlook: Data Visualization.  As has been our style, we leverage our network to bring you the most practical and interesting news and points of view.  In this article, we focus on two important aspects of Data Visualization: gathering data and effective visualization techniques.

A Simple Mashup

As Data Scientists we often want to use every tool in our arsenal, possibly because we believe it will help or we want to live on the cutting edge, but we forget that people are the best pattern matchers and all we need to tease out useful insights is data juxtoposition.  Here the Trauma Professional's Blog creates a mashup of the Fatal Accident Reporting System (FARS), the Census of Fatal Occupational Injuries (CFOI), and other hidden government databases, allowing our natural pattern recognition to find what's most relevant to us.

Mapping our Thoughts

On the other hand, it is simply fun to go off the deep end and use every tool in the box!  This Fall Berkley researchers measured blood flow in video watchers' brains combined with PCA analysis to create a "continuous semantic map" of how we organize the world we see around us.  The stunning interactive map relates position in the brain with its influence in the organizational process, and much more.  While the raw data is all available in one place, as opposed to hidden government databases, its inter-relationships are not self evident.  This is a fun visualization because we can explore the raw data versus the analysis results, allowing us to reconcile our own understandings of brain function.

UI Design Evolution

If you've ever wandered to the cockpit of an airplane, you may have gotten that intimidating feeling as you imagined how to synthesize all that information in real-time.  This intimidating feeling is exactly what F22 Raptor engineers aimed to eliminate.  This article by AssertTrue() breaks down the thinking behind cockpit design over time; but, as data scientists, we know that there is a crucial relationship between automation (algorithms, AI, etc.) and action (pilot/user input).  Too much automation and vital information is unavailable for critical decisions, while information overload may force attention to non-critical issues.  We can abstract these concepts for our own UI challenges.  In organizations, people are pilots, and what information is presented to them from around the organization greatly affects what decisions they make on its behalf.  Action = f(Awareness)

Written by: Sean M. Gonzalez