Finding Meaning in my Data Visualisations
By: Kork Ling Hui
Tags: Data, Infographics, Data Visualisation

After I had posted my mini venture onto slack, Makarios, one of my classmates had suggested that I try this out with the 2x2 and 4x4 rubik’s cube. So I decided to try out his suggestion as an adaptation to my previous experiment, and made similar infographics for all three, and ended up with the final data visualisation here:

I represented the different cubes visually, the size of the pink bubble depicted how satisfied I was with myself after conquering the cube, amount of clocks showing the amount of time I devoted to figuring the cube out, and the red and yellow lines depicting whether I felt satisfied or not with the time I took to complete the cube.

It’s not much, but a lot of thought went into deciding what should go into the visualisation, how should I represent my data, how should I represent and clean my data to produce the best visualisation etc. Although the project seems simple, I really think it has taught me the importance of meaningful data visualisations. You can think of data visualisations like creating a new food item to sell to the public. If your product is similar to those already in the market, it is unlikely that consumers will deviate from their go-to brand just to try out a new brand that pretty much is trying to sell the same thing. Instead, a touch must be added: maybe a different texture, or a new flavour, with the consumers’ wants in mind. Likewise, a data visualisation should always aim to tell the audience a story. I’ll be sure to think twice before screen-shotting any visualisation on tableau in which I had mindlessly dragged and dropped the variables just to churn it out.

Apart from this mini project, I was also intrigued by the use of emojis after my project on perceptions of happiness. So I decided to do more experimentation with the project idea and managed to collect some data here:

I decided to produce my own data visualisation again, but this time not hand-drawn but using an infographic editor instead, and came up with this infographic:

I was looking for a new software to help me represent the data I had collected, and was excited when I came across Venngage. To my surprise, this software required me to label all my axis on my own, compared to excel and tableau, so I had to see if my chart made any sense to me before I could even start labelling. This was a new challenge for me, slightly different from the previous one as this time I did not curate the data but only cleaned it myself. But I eventually decided on the chart above and received rather satisfactory responses! Dr Charles suggested I post this on r/dataisbeautiful on reddit, and I was a little nervous because this would mean my visualisation would be open for the world to see and provide feedback on. My post is here:

What I did not expect was to get 22.7k upvotes on reddit! They were a lot of feedback, some nasty but mostly constructive criticism and positive responses to my post. This really taught me a few things: 1) for a visualisation to be well received, I had to understand it in its entirety, and 2) the impact a meaningful visualisation can have, especially on social media! A visualisation on social media has the power to spread and reach to so many people. However, it is important to take note that with great power, comes great responsibility. It is pertinent to be able to discern false information, or else the consequences would be dire.