Purpose: The bedrock of an effective visualization.

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Guest post by Noah Iliinsky, IBM visualization luminary.

This is a continuation of a series of posts covering the Four Pillars of Visualization. Please read my previous article , which describes these pillars as: purpose, content, structure and formatting. This post focuses on the first of these.

What is your purpose? Why are you here? And what do you want to accomplish with this visualization? These are the sorts of questions you must ask yourself before you begin drawing your visualization*. In fact, defining the purpose and selecting the content are critical, and often overlooked, steps in the visualization design process. We must understand what we’re visualizing before we figure out how to visualize it. Defining your purpose helps you figure out what that what is.

*This posts addresses creating visualizations for presentation. If you’re in the exploration phase, you should just try a bunch of things,
see what works, and not worry about process yet.

There’s a reason the purpose phase comes before the other three phases. A well-defined purpose not only gives you a target to aim for, it gives you guidance to start you in the right direction and keep you on track along the way. It will tell you what data is important to include and what doesn’t matter. It will tell you which relationships to emphasize, and which aren’t as relevant. It will tell you which data points to highlight and which aren’t as interesting.

A useful purpose must take into account questions like:

The more you know about your customer and how they will consume your visualization, the more clear and accurate your can make your purpose, and the greater your odds of success.

So what does a good purpose look like? It’s specific and detailed; think of it as a specification document for your visualization. A graph that is intended to “show the sales figures” presents a much broader (and, therefore, less useful) target than “show the sales figures for our flagship product, for the top three and bottom three regions, for the last eight quarters, in a format we can use online and in print.” Note how the second example specifies boundaries, key data and usage considerations? That will not only help you get past the dreaded blank page, it will give you a standard to test against as you make design choices.

To be most successful, different uses (purposes!) will probably require different implementations. For example, if I’m driving from Seattle, the map to get me to New York and the map to get me to Baltimore look almost identical. However, the purpose is different enough that I really do need a different set of directions to get me there. Note also that a more general purpose of “drive to the east coast,” while accurate and concise, is highly unlikely to be sufficiently specific as to be useful.

Keahey_vis_route1

The route from Seattle to Baltimore (above) is very similar to the route from Seattle to New York City (below), except at the critical point — the arrival.

Keahey_vis_route2

Luckily for us, there are a few very common general purposes, when it comes to graphing data. Check out the headings (below) fromIBM’s Many Eyes graphing tool.

Keahey_Vis_ManyEyesThese headings, about seeing relationships, comparing values, etc., are fantastic statements of purpose. It’s likely (but not quite guaranteed) that your purpose falls under one of those headings. If you’re having trouble defining your purpose, consult this page and think about how one of these purposes may fit your needs and data. Not all needs will be met by one of these purposes, but they do encompass the most common graphing scenarios.

Finally, remember that your purpose will probably change as you proceed with your design process. You may discover new needs, or see something unexpected that should be revealed. That’s a good thing; your purpose will evolve with your understanding. Once you have figured out your purpose you can begin selecting the content of your visualization; that’s the topic of my next post.

For further discussion on this topic, download my recent whitepaper, “Choosing visual properties for effective visualizations.” It describes the huge number of design decisions you need to make upfront before creating your visualization that will impact the ability of the visualization to communicate knowledge accurately and efficiently. This paper addresses one key aspect of the design process: how to choose an appropriate visual property (position, shape, size, color and others) to encode the different types of data that will be presented in the visualization.

Why stop the insight with this article? Visit IBM’s visualization hub, IBM Many Eyes and join more than 100,000 like-minded visualization enthusiasts from the realms of business, government and academia, including additional insights from Noah Iliinsky and other IBM visualization luminaries.

Noah Iliinsky strongly believes in the power of intentionally crafted communication. He has spent the last several years thinking, writing, and speaking about best practices for designing visualizations, informed by his graduate work in user experience and interaction design. Noah Iliinsky is the co-author of Designing Data Visualizations, and technical editor of, and a contributor to, Beautiful Visualization.

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