This is the third post in our series ‘Principles of Data Visualization’ #PoDV
We started off this series discussing the importance of data visualization in business, and then moved to the two goals in data visualization – explanation, and exploration. Now that we’re aware of how data visualization functions in business scenarios, let’s dive into the mechanics of how we process visual information. We’ll understand the role of memory in perceiving visual information, and how to apply that understanding as we work with visualizations.
The eyes and the brain are partners in the visual process. To put it in traditional BI terms, the ETL is done by the eyes, and the information processing by the brain. The optic nerve that connects the eyes to the brain is an information highway. Studies show that the eyes transmit information to the brain at ethernet speeds. Due to this close relationship between the two, mental health experts have observed that poor eyesight also affects memory, and likewise, mental health issues tell on a person’s eyesight. When discussing data visualization, we give a lot of attention to what looks good, and often neglect the importance of memory in the visual process. However, memory is equally, if not more important, than eyesight.
Eyesight and Memory Working in Parallel
If you’re familiar with big data terminology you would have come across the term ‘massively parallel processing’ (MPP), as most commonly seen in MapReduce technology that powers Hadoop. It breaks data down into small units, and processes each of the units in parallel. A similar process has always been used by us to process information with our vision as well. When we look at a visual, our eyes and our brain work in parallel to take in new information, and break it into small chunks. Then, the eyes and the brain process the chunks in parallel to find meaning. Let’s look at an example to better understand this.
Let’s say we walk into a supermarket to buy oranges. Our eyes first scan the layout of the supermarket. At the same time, our brain processes the various sections of the layout, and instructs the eyes to zone in on the fruits section. It does this by sending signals about how fruits look from memory. The eyes then break the entire scanned area into parts, and scan each part to spot the fruits section. The same process is repeated till we zero in on the oranges in the fruits section. This process of visualizing information is performed by the eyes and memory working in parallel.
The Role of Memory in Vision
While that’s an overview of how we process visual information, let’s discuss the vital role of memory in our vision. There are two types of memory that come into play when we process visual information.
- Long-term memory
- Working memory
This type of memory is formed by past interactions and experiences, and is stored in our brains to be accessed whenever needed. This type of memory is what makes us always expect the units to be marked off on the X and Y axes of a chart, or the date range selector at the top of a dashboard.
It needs to be considered when designing the layout of a dashboard or visualization. There should be good reason to go contrary to long-term memory when deciding the basic structure of a dashboard. While a detailed discussionon this topic is out of the scope of this series, for an overview of concepts related to long-term memory, see our white paper ‘Designed to succeed—How design is playing a strategic role in today’s software products’. While long-term memory is vital in data visualization, the more important kind of memory when processing visual information is our working memory.
When we look at a line chart, or notice a number in a dashboard, we use our working memory to store just the information we need at the moment. This type of memory breaks the entire visual into small chunks of information, in a process appropriately called ‘chunking.’ Surprisingly, for all the complexity of our brain, our working memory can hold only about 3 chunks of information at any given time. When perceiving a complex visual, we’re constantly replacing the 3 available slots in our working memory. This is why when designing a visual or a dashboard, one of our goals is to remove distractions, and pack as much useful information as possible into each chunk. While we want to avoid information overload, this allows the designer to direct the attention of the viewer in a natural way. Let’s look at how to apply this learning when designing a chart.
Edward Tufte, a data visualization expert, termed the distractions in a chart as ‘chartjunk’. He defines chartjunk as the ‘elements in charts that are not necessary to comprehend the information represented on the graph’. In his book ‘The Visual Display of Quantitative Information’, he gives the following example of how to reduce chartjunk for better visual expression:
By reducing chartjunk as much as possible, we can make best use of a viewer’s working memory, and build more effective dashboards.
With that practical example, we end today’s post with a deeper understanding of how eyesight and memory are partners in the visual process. While we always want to build dashboards that look sexy, it pays to go deeper, and consider how our memory processes the visual information in a dashboard.
In the next post, we’ll discuss one of the most fundamental concepts in data visualization – preattentive attributes. If you find these posts insightful, and would like to get an overview of this entire series in a single read, view our white paper ‘Principles of Data Visualization.’