In this chapter, Drucker continues her investigation into the historical origins of various graphical forms. She does so in order to provide the reader with a greater understanding of the context in which forms arose and the ways in which they may have implicit biases or allegorical meanings embedded within them. By recognizing these forms as not inherently neutral or empirical, the reader (and by extension, practitioners in the field of data visualization) may be able to “break the literalism of representational strategies and engage with innovations… that augment human cognition” (p.71) — Drucker’s ultimate rhetorical goal in producing the book.
Early in the chapter, Drucker defines two basic divisions in the functions that data visualizations can serve for their creators and audiences. First, there are representations of information that is already known, which she posits as having a static relationship to what they show. Secondly, “knowledge generators,” which create new information through their use, and thus have dynamic and open-ended qualities. Drucker seems to have a clear affinity for the second type, as they more closely serve the needs of her theorized “humanistic” practice.
After running through a historical deep dive into the uses which visualizations have served (timekeeping, space-making, administration and record keeping, trees of knowledge, and knowledge generators) and elaborating on the forms that evolved to suit these particular needs, Drucker ventures back into more theoretical territory. Under the heading of “visualizing uncertainty and interpretive cartography,” she questions the very assumption of empirical observation and data collection. In her words, data are “capta”— taken rather than given, with parameters that are decided by the observer as they are recorded. Thus, the biases (and historical/social context) of the observer are embedded in the very nature of what is recorded, and the presentation of data for comparison erases the original ambiguity of the phenomena (human existence?) that were observed.
In order to restore the ambiguity of human existence and the natural world to the field of data visualization, Drucker suggests a few strategies that break significantly from the standards of the field. The use of unequal measurements or standards, disjointed plotting, and “fuzzy” or geometrically undefined forms could serve as visual markers of complexity and uncertainty. She fails, however, to provide much in the way of concrete visual examples of these practices for the reader to gauge the effectiveness of these posited strategies. In this way, it seems that Drucker’s project could be better served by the inclusion of practitioners in the field who are also interested in “humanist” representation. Where she now seems content to remain in the realm of theory and art-historical analysis, she could instead move further into the realm of experimental practice.