What are the principles of good visualization design?

Good visualization design principles include clarity, accuracy, simplicity, relevance, and consistency.

Clarity is the first principle of good visualization design. The main purpose of a visualization is to communicate information clearly and effectively. This can be achieved by using appropriate visual encodings for the data, such as position, length, angle, colour, and shape. The choice of visual encoding should be guided by the nature of the data and the questions that the visualization is intended to answer. For example, position and length are good for representing quantitative data, while colour and shape are good for categorical data.

Accuracy is another important principle. The visualization should accurately represent the data without distorting or misleading the viewer. This means that the scales, proportions, and relationships in the visualization should be true to the data. For example, in a bar chart, the lengths of the bars should be proportional to the data values they represent. In a map, the distances and areas should be accurately portrayed.

Simplicity is a key principle in visualization design. The visualization should be as simple as possible, but no simpler. It should not include unnecessary details or embellishments that can distract from the data. The focus should be on the data and the insights it provides, not on the design itself. This principle is often referred to as the principle of 'less is more'.

Relevance is another principle to consider. The visualization should be relevant to the audience and the context in which it is used. It should present the data in a way that is meaningful and useful to the viewer. This may involve selecting and highlighting the most important data, or tailoring the visualization to the viewer's knowledge and interests.

Consistency is the final principle. The design elements of the visualization should be consistent in their use and interpretation. This includes the use of colours, shapes, sizes, and other visual encodings. Consistency makes the visualization easier to understand and interpret, as the viewer can apply the same interpretation across different parts of the visualization. For example, if a certain colour is used to represent a certain category in one part of the visualization, the same colour should be used for the same category in other parts of the visualization.