Earlier
in November, I mentioned that I wanted to do a post on MOOCS, Massive Online
Open courses. I still want to do that
post, but once again, another topic has pushed a discussion about MOOCs further
into the calendar year.
Data
Visualization, or Data Viz, is an emerging technology field that combines skills
connected with three fields: communications, design and programming. My guess is that if you’re reading this,
you’ve seen many examples of Data Viz, especially after this recent election
cycle. Data Viz takes a data set and
portrays it visually. These infographics
are often eye-catching. Additionally,
many are interactive, allowing the viewer to control the data that is viewed or
create an opportunity to see a relationship between sets of data.
It
may sound a bit complicated, so it might be helpful to think of Data Viz as
graphs and charts on steroids. In the
Data Viz world, programmers attempt to give viewers new and useful ways to
examine data. The premise is that a well-crafted visualization may allow a
viewer to understand a data-driven topic in a new and useful way.
Here’s an example that
portrays relative incidences of a number of diseases as they are found around
the world.
 | ||
| For a full look at this visualization, click here. |
Mike Bostock works for the
NY Times and is responsible for many of their notable data visualizations. Bostock's map of Hurricane Sandy’s wind speeds as the
hurricane came ashore might be of interest, given recent events. Click on the
“Next” button towards the top of the map to see the information change over
time.
 | |
| For a full look at this visualization, click here. Click on the “Next” button towards the top of the map to see the information change over time. |
Treemaps are one fairly
familiar data visualization type. Here,
a finite amount of data is first divided into component parts. Then, these
parts are represented by different sized sections proportionally to the total
data set. In the following example, the US stock market is divided into
categories of stocks (health care, financials, consumer goods, etc.) and these
sections are further divided. Scrolling over this treemap yields deeper market data.
See for yourself right here.
This
outstanding example pops up now again as someone’s emailed favorite: http://www.gapminder.org/world/ It is really beautifully done and shows how,
with the right representation of data, new understanding is created. In this case, the relative wealth of nations as
it connects to life expectancy is portrayed over the last two centuries.
It’s
worth considering that Data Viz (also known as DV to insiders) is a growing
field of academic study. Course work, and even concentrations within majors,
has become part of computer science programs and design programs. Journalists, social scientists, graphic designers
and scientists increasingly find DV part of their field. My guess is that it won’t be long before data
visualization finds its way into high school curricula.
Interested in exploring the topic further? There are many sites to check. Here are a few to get you started.
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