Visual design of quantitative data
The concept of a quantitative data visual design is quite unknown for many and most of us unfortunately don’t even realise that something like visual data design even exists. We commonly accept data in its graphic form without being aware how much it influences our behaviour. We encounter charts and tables daily, whether in newspapers or magazines, or directly in the workplace as a source of information for decision making.
Data visualization is a skill for which it is necessary to have at least basic knowledge of some disciplines that originally developed as stand alone fields of human knowledge:
- cognitive psychology and visual neuroscience
- descriptive statistical data analysis
- graphic design
The foundation for creating visual data presentations is adhering to the principles of human visual perception. Our visual perception registers certain external stimuli on the retina very quickly even prior we focus our attention in them; similarly quick is also their preattentive processing in our brain in parallel running processes. Human cognitive processes, however, require our focused attention to process the visual stimuli without pre attentive features over slow sequential processes. Creating visual design must therefore primarily take advantage of those preattentive features of target objects, and at the same time eliminate the amount of analytical work performed by our brain to process the visual stimuli without preattentive features – and leave this work to our eyes, which carry it out quickly, effectively and automatically.
The more effectively we are able to use pre attentive features, and the more effectively we are able to tailor visual design to the characteristics of human perception, the more effective we are in creating meaningful graphical data representations.
Graphic vs. visual design
Visual and graphic design are part of data visualization but differ in the function they perform. Graphic design deals with appearance, i.e. how the chart looks. Visual design deals with the graphic representation, i.e. which type of chart and which elements (lines, columns, bars, etc.) will represent data. Both design categories are irreplaceable and in the absence of either it isn’t possible to create an effective visual presentation of data.
How to create a good visual presentation of data
The preparation of any visual presentation of quantitative information must start with the question:
What message do I want to convey?
The visual presentation of data is the graphic display of a story, which provides a visual answer to the question. The main parts of the story must be mutually connected into a meaningful context. Good visualization includes careful wording of the name, which outlines its overall concept and indicates:
- which data we are actually looking at
- which time period does the data concern
- which important facts are we displaying through the data
Identifying the content of the message is just the beginning. Before we can move on to creating the visualization we should find answers to the following questions:
Why am I creating a visual presentation and what message am I to convey ?
If we aren’t able to answer, then we’ll create a presentation without any thought and concept. In such case we should stop working and think about the purpose of the intended visualization.
Who will I present the visualization to and what is its purpose?
It is important to determine which audience and what purpose we are presenting data for. An explanatory presentation intended for corporate executives will look very different to an exploratory one intended for researchers. Precise identification of the intended audience is important for correct conception of a presentation because it is precisely the target group that is decisive for the selection of the type of presentation and the method we use to present the data.
Which type of presentation should I choose?
For certain data types only certain chart types are suitable. The majority of data can be graphically represented in many ways, but only certain of them can ensure a meaningful and effective data representation. Time series are visualized through line or column chart, while for categorical data column charts suit, line charts have to be avoided, while for data hierarchy and structure of a whole bar charts make it best. It’s true that more types of charts can be suited to one type of data, and conversely, but there are always those tiny details that are vital to picking up the most appropriate one. Individual chart types communicate better about trends, others about categorical data, etc.
Creating a visual data presentation therefore contains four steps:
- In the first step we define the exact content of the story.
- In the second step we sort and order data into the structure required for its graphic presentation.
- In the third step we pick up the most suitable type of chart and create its basic format through a spreadsheet.
- In the fourth step we format the chart to create its final graphic design.