To the Editor—The review by Salinas et al ^{Reference Salinas, Kritzman and Kobayashi1} introduces many important aspects concerning the science of data visualization. However, the references cited in support of an assertion that the best ways to visualize data remain unclear overlooks several important resources that provide insightful practical advice on optimal choices. In particular, the work of William Cleveland, whose career was devoted to scientific study of visual encoding and decoding of scientific data, and the work of various cognitive psychologists are noteworthy. Cleveland’s findings are distilled into 2 very useful books that have been reviewed in this journal. ^{Reference Birnbaum2,Reference Birnbaum3} Important findings from cognitive psychology articles are distilled into various comprehensive review publications, like that of Gigerenzer et al. ^{Reference Gigerenzer, Gaissmaier, Kurz-Milcke, Schwartz and Woloshin4} The graph examples illustrated by Salinas et al should be viewed with key concepts from Cleveland and Gigerenzer in mind. Exploratory data analysis methodology based on data visualization principles and techniques established in the 1970s–1990s “… add an exciting and useful tool to the epidemiologist’s repertoire.” ^{Reference Shelly5} The works of Cleveland, Gigerenzer, and others were paramount in informing many of the choices I had to make (and defend against those who initially found them unfamiliar) throughout my career in hospital and public health agency projects related to recognizing the onset of adverse trends efficiently and informing a wide range of audiences about comparisons of healthcare-associated infection rates. ^{Reference Birnbaum, Cummings, Guyton, Schlotter and Kushniruk6–Reference Birnbaum and Jarvis9}