"The visible figures by which principles are illustrated should, so far as possible, have no accessories. They should be magnitudes pure and simple, so that the thought of the pupil may not be distracted, and that he may know what features of the thing represented he is to pay attention to." (National Education Association, 1894)
"First, color has identity value. In other words, it serves to distinguish one thing from another. In many cases it does this much better and much quicker than black and white coding by different types of shading or lines. […] Second, color has suggestion value. […] Red is usually taken to mean a danger signal or an unfavorable condition. But since it is one of the most visible of colors it is excellent for adding emphasis, regardless of connotation. […] Green has no such unfavorable implication, and is usually appropriate for suggesting a green light" condition. […] Similarly, every color carries its own connotations; and although they seldom make a vital difference one way or the other, it seems logical to try to make them work for you rather than against you."" (Kenneth W Haemer, "Color in Chart Presentation", The American Statistician Vol. 4" (2) , 1950)
"Seeing color isn't always as simple as it may seem. Some colors are not easy to see unless the conditions are just right; some are so easy to see that they overpower everything else; some are easy to see but difficult to distinguish. […] Large masses of color become too visible and easily overwhelm the entire chart. The more visible the color the easier it is to use too much of it." (Kenneth W Haemer, "Color in Chart Presentation", The American Statistician Vol. 4" (2) , 1950)
"The execution of any task involving information visualization will be motivated by the user's intention and influenced by many factors. One of these is the user's internal model. Another is the visible externalization of some data. A decision as to how - as well as whether - to proceed will depend upon an interpretation of these sources of information." (Robert Spence, "Information Visualization", 2001)
"System Thinking is a common concept for understanding how causal relationships and feedbacks work in an everyday problem. Understanding a cause and an effect enables us to analyse, sort out and explain how changes come about both temporarily and spatially in common problems. This is referred to as mental modelling, i.e. to explicitly map the understanding of the problem and making it transparent and visible for others through Causal Loop Diagrams" (CLD)." (Hördur V. Haraldsson, "Introduction to System Thinking and Causal Loop Diagrams", 2004)
"Cleverly drawn pictures can sometimes disguise or render invisible what is there. At other times, they can make you see things that are not really there. It is helpful to be aware of how these illusions are achieved, as some of the illusionist’s 'tricks of the trade' can also be found in distortions used in graphs and diagrams." (Alan Graham, "Developing Thinking in Statistics", 2006)
"[...] the production of data is an important aspect of critical practice precisely because of the lack of attention normally accorded to it by designers. What is made invisible, in this case, the production of data, is often one of the most important aspects for a critical thinker to focus on. What becomes standardized, routine and efficient has become naturalized, and therefore unquestioned. But it is there, in the unquestioned areas, that so many ideologically, politically, culturally framed decisions have been made." (Peter A Hall & Patricio Dávila, "Critical Visualization: Rethinking the Representation of Data", 2022)
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