Data Visualization: Developing a Simple Black-and-White Mock-Up
After you’ve done the hard work of defining and outlining your storyboard, it’s time to develop your mock-up. Mock-ups are also referred to as wireframes or prototypes. Think of them as rough sketches that help you visualize what the final output will look like.
You may find it a little bit unexpected to start with a simple black-and-white sketch. After all, isn’t one of the main points of data visualization to use elements like color to tell the most effective stories from the data? The answer is yes, but not during the mock-up stage. By using mock-ups without color, you force users to focus on what you need them to focus on.
If you start the mock-up process with color, your users won’t focus on anything else — not on the data, on the layout, or even on whether the message is being conveyed correctly. The color discussion will become the focal point of the entire mock-up process, and your final data visualization will suffer.
Your only goal at this stage is to get participants’ sign-off on the layout of your mock-up. You don’t need to do anything fancy or artsy to get that approval.
Although this approach seems to be fairly logical, some of you may be nervous about taking it. You may fear that users may grow impatient with or be turned off by a plain black-and-white mock-up. To overcome this worry, you should make it a habit to reiterate and set expectations up front about what users should expect to happen next and in the final outcome.
The exception to this rule is mock-ups created for an executive audience. Your time with executives is likely to be limited, so it’s critical that you don’t approach them until you have a fully functional, well-branded visualization. Anything less, and you risk being axed!
Some other benefits of sticking to black and white for your initial mock-up include the following:
Saves time and money when making changes: It’s less expensive to make design modifications on a black-and-white sketch than it is to make changes on a system-ready visualization connected to live data.
Keeps the focus on the placement, position, and size of each element on the visualization: Laying things out in a flat, colorless space helps you figure out where to place each component to provide a nice, clear user interface that tells a compelling story. Color sometimes distorts your view of the overall layout and causes you to focus on the shiniest items in the model.