Breaking down a complex story into a simpler one


Presenting your Data and Telling a Story

In my opinion, the most significant thing that a designer can do is find a way to step into the shoes of the user.

Keeping this in mind, I have realized that the user’s main concern is the potency of the designer’s research on the user’s life. This is where the process of visualization can play a key role: presenting relevant information in an easy-to-understand form.

Visualization often goes hand-in-hand with user research. Although this particular experience did not allow me to conduct user research and create a visual for the user group I observed, considering a potential user group while figuring out my visualization has allowed me to gain enough knowledge to carry out the full process in a future opportunity.

Introduction and Background

For the purpose of creating visuals, I used the Tableau kit that was provided to me. Initially, the simplicity behind Tableau’s drag and drop system intrigued me, and I wondered how complex visuals could possibly be created from a drag and drop system. Both using Tableau and examining a large amount of Seattle 911 data I was given was overwhelming. Because of this, I decided that I would make visuals first, and the figure out how to make sense of them. I quickly realized that doing made the process harder instead of easier, and I reversed my steps.

After spending a couple of hours familiarizing myself with the data, I realized I wanted to create visuals about property crime in Seattle for a user group of home and business owners. Specifically, auto theft, shoplifting, burglary, robbery, missing and found property, and property damage.

My visuals can be seen below, and the questions they pertain to are in the captions.

I created my visuals using Tableau, and my dashboard can be found here

“What types of property-related crimes as most common?”
“Where do the most property-related crimes occur?”
“When do the most property-related crimes occur?”

Looking Back

I am used to communicating using words, but not using visuals. Consequently, I had a lot of trouble with organizing my thoughts to create visuals. Something that really helped me was creating a list of the key points I wanted to address in each visual, and then incorporating them using the most efficient method I could find.

In order to do this, I made sure to ask myself the 5 ‘W’ questions: Who would be concerned with the data, What would be the concern, When (what time) did the activity in the data occur, Where was the area of relevance, What was the idea I was trying to communicate and Why was I trying to communicate this idea.

What could I have done to have made the process of sorting and visualizing data easier?

The dataset was large, and the data points were widely spread out within it. Hence, it was very difficult to comb through the data and familiarize myself with it, and also, determine what user group I wanted my visuals to speak to.

In order to make this process easier in the future, it might be helpful to gather more background information on the types of data available. I would then have an informed opinion on who the data could be most relevant to and how it could effectively be presented. Information for the latter could be gathered by looking at example visualizations created by others on similar data.

Visualizing for the Future

Since I am interested in studying mental health, I started thinking about the applications visualization could have in this field. One example I thought of was using visualization to explain the consequences of casual drug use to college-age students.

Alcohol and drugs are often used at parties, and drinking with friends or occasionally smoking is viewed as a novelty experience. Because students may not be aware of the growing tolerance their bodies may have for certain drugs and the risk of possible addiction and dire health and social consequences, they may not be inclined to stop using drugs recreationally.

As a student myself, I know that looking up statistics about this topic might seem unnecessary. But, if visualization was used to communicate the consequences of reckless drug use, students might be more willing to consider the data and take precautions when using drugs.

Visualization is powerful to communicate data. Regardless of the user group in consideration, using graphics to tell a story can go a long way.

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