One definition of visual perception according to the article "The Role Of Visual Perception in Data Visualization" is the ability to process and interpret our surrounding environment contained in visible light or within our eyesight. Also, according to the same article, images are perceived by our brains not our eyes. What is meant by that is that our visual perception is selective meaning that we only pay attention to some details within our vision and not to the entire image. And according to Idriss Aberkane, knowledge equals attention multiplied by time. Therefore if we pay only attention to some details and omit other details, we deliberately to choose to omit some factors from our grasb. Second, our vision is drawn to familiar patterns, meaning that we see what we expect to see. Finally, our memory is limited. When looking at a visual, we can only hold to a limited amount of information at a time. Therefore, all those factors should be taken into consideration when creating and looking at a visual.
To Create good visuals, one should understand first how our brains works to process and store information. Basically, there is 3 types of memories in charge of processing data in our brain. The iconic memory in which we process first the information. The process last than less second and is called preattentive processing. That process happen automatically when we see a visual and often happens before we even start paying attention to details. In that stage our brain detect some attributes. The second type of memory is the working memory which is our short term memory. Usually when we are working with a visual meaning when we start paying attention to details detect patterns, focusing on the information of interest, we use our short term memory. According to Miller's law our working memory has a capacity of 5 to 9 minutes. Finally the long term memory is where the information we learnt, analyzed is stored.
Also, according to the article "Graphical Perception and Data Visualization" by Nina Zumel, there are some principals to consider when creating visuals. First, we should make sure that the important differences are large enough to perceive. For instance, if we are not using the right scale in a bar chart. Even though, the differences are quite important, while using a large scale, it will be perceived as small which might be misleading for the reader. That often happens when combining different metrics within the same visualization. Second, shape changes should be large enough to perceive. A simple example would when tracking a stock price over a large period of time versus in one day. Over one day, we can see that the price fluctuate over the day and sloping differently, while we change the view of the same visual over 1 year we can see a general trend, one slope for the entire day. Again we just want to make sure and emphasize important differences for the readers of our visuals.
To conclude, in order to create an effective visual one should understand and focus on the information we want to pass to our audience. It is also very important to understand the way we capture, process and store information. During the class session, we discussed how pie chart can be inaccurate and readers made more mistakes interpreting pie charts than bar charts. In fact, humans are relatively bad at judging the angles versus surface for bar charts, which might lead to misinterpretation. Also, some readers might focus on different aspects such as the perimeter of the cone, which make a pie chart even more prone to errors. On the other hand, I think we should focus on the information we want to transfer. Basically if we want to analyze the difference between x amount of variables, instead of graphing those variables we should graph the only the difference between those variables. All the aspects discussed above makes visualizing data a challenging task and therefore should be taken into account while creating a visual.Sources:
The Role of Visual Perception in Data Visualization. (2017, January 11). Retrieved September 28, 2017, from http://daydreamingnumbers.com/blog/visual-perception-data-visualization/ Zumel, A. N. (2012, September 11). Good Graphs: Graphical Perception and Data Visualization. Retrieved September 28, 2017, from http://www.win-vector.com/blog/2009/08/good-graphs-graphical-perception-and-data-visualization/