Recognizing the Human Components of Data Visualization

Adding a component such as easy-to-use navigation, or choosing and applying an effective color scheme to data visualization is referred to as the human side of data viz. Humanizing your data viz a critical component of any data visualization.

As compelling mobile apps continue to evolve, user expectations are at an all-time high. Gone are the days when apps could survive based simply on their usefulness. In the app world, having an attractive and intuitive user interface (UI) is a do-or-die proposition. In the data-viz world, a nice UI has typically been considered to be something that is nice to have, but that school of thought is changing. No matter how great the data is, if your data-viz UI is not user friendly then no one will use it.

Adding the human component to your data visualization is a must, though sadly, many people overlook this task. The following are some easy ways to humanize any data viz:

  • Use simple navigation. Imagine having a car with the lock/unlock door buttons hiding under the seat, or a car with the open/close window buttons located in the trunk. Is that a car that you would buy or want to use? Probably not. The same is true of a data viz with confusing menus. It not only frustrates users as they attempt to get to their data, but also causes them to stop using it.

  • Use colors effectively. When it comes to color, what is effective and ineffective is always subjective. There are always users who don’t like a particular color. It’s your job to ensure that your data visualization follows some best practices for effectively applying color regardless of the color scheme.

  • Use intuitive images and visual cues. One of the most overlooked humanization techniques is to apply easy-to-understand visual cues and images that appeal to the human mind. The emergence of social media sites such as Instagram and Flickr — which have hundreds of millions of users who gather online to share their images — demonstrate that human beings like to see images.

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