WHY DATA VISUALISATION
Data visualization is the presentation of analytical results in a pictorial or graphical format. This is beneficial to people of all professions, as it conforms to the way the human brain processes information.
When information is presented textually, the brain has to neurologically “piece together” the information in order to understand or recognize its importance. This is a slow, lengthy process which can often cause confusion among people who aren’t familiar with the subject.
Data visualization transcends this issue. It presents the data in a visual format to therefore allow the brain to process and understand the given information at a faster rate.
There are plenty of statistics that support this. For example, studies have shown that:
- Visual information is transmitted to the brain 60,000 times faster than textual.
- 40% of people respond better to visual information than plain text..
- Infographics increase online traffic by 12%.
- Visual content drives user engagement.
Visualizations also help people see things that were not previously obvious to them – especially pattern, which can be hard to spot in large data volumes.
“A wad of numbers in a paragraph will rarely resonate with readers. In contrast, a graph, more complex graphic, or perhaps a simple interactive widget (such as was used during the budget to help people determine how it would impact them directly) will often be clearly understood, and therefore determined the best avenue to the reader,” says Brisbane Times’ Editor in Chief, Simon Holt.
HOW TO MAKE GOOD VISUALISATIONS
When it comes to large data volumes, everyone loves data visualization. It’s more exciting than an image and can generally create a new level of depth for your story. But just because the data has been presented visually, doesn’t mean it is easy to grasp or interpret.
We’re all been victims of a data-packed infographic, chart or pictorial that has had an obscure message. And while the creator may have had the intention to convince you their message matters, you’ve instead been unimpressed, confused or indifferent of the cause, due to one poorly presented data visual.
So how can we, as journalists, prevent this from happening?
“Data visualization is more art than science; knowing your intended audience and how they like to consume data is key,” says George Wright, leader of the Intelligent Systems at Fairfax Media . “You always want to aim to make the visualization as interesting and easy to comprehend without dumbing the data down to the point of irrelevance.”
Other key points that make a good visualization are:
- Information. This includes the accuracy, consistency, integrity and honesty of the visualization. Mr Wright says, “The biggest danger in data journalism is misrepresenting the statistics in order to make a story angle more sensational. Ultimately, someone will call you out on it.”
- Story. This creates the interestingness of the visualization. It makes it relevant, meaningful and new; factors that are crucial in hooking the reader. Without a story, the visualization can be “boring” to the reader, as it can lack interest.
- Goal. This determines the usefulness of the visualization – is its aim to be usable or to add emphasis to the story? Without a goal, the visualization can become useless.
- Visual form. This includes the structure, appearance and harmony of the visualization. Visual forms are what make the visualization look “appealing” to mass audiences. They’re often the first point of interest – if a reader likes the visuals, then they’ll be more likely to view the visualization.