Over the last week or so, we have revisited visualization as a technique for interpretation. In our production of networks using Gephi, the process of creating data, preparing it for input into the software, manipulating it once in the software and then interpreting it once entered has been foremost. As we move on to mapping, we will find parallel processes at work: preparing data, entering it, manipulating it, interpreting it. And as we do so, it behooves us to think critically about what we are doing, and what we are not doing.
Johanna Drucker’s intelligent, broad view of visualization as a form of knowledge production offers us many pointers for taking each step on our path to visualization and interpretation with deliberation. The long chapter “Interpreting Visualization–Visualization Interpretation” from her book, Graphesis: Visual Forms of Knowledge Production (Harvard, 2014) presents us with an overview of forms of visualization primarily since the Renaissance, and it also issues a plea for the development of a greater understanding of the force of visual rhetoric; a plea that is directed especially at humanists, as they enter into a realm of spatialized representation that might appear to belong to the realm of the quantitative over the qualitative.
Visualizations can be either representations or knowledge generators in which the spatialization or arrangement of elements is meaningful. When reading a visualization, Drucker encourages us to use language carefully, employing terms such as “juxtapose”, “hierarchy”, “proximity”. Drucker claims that visualization exploded onto the intellectual scene at the edge of the late Renaissance and beginning of the early Enlightenment, when engraving technologies were able to produce epistemologically stunning diagrams that both described and also produced knowledge. Now with the advent of digital means to manipulate and produce data we can all produce timelines (!) without giving a thought to the revolution in the conceptualization of time and history that (our near neighbor) Joseph Priestley occasioned. So, as we play with Timemapper or Timeglider, Drucker cautions us to become aware of the visual force of such digital generations. “The challenge is to break the literalism of representational strategies and engage with innovations in interpretive and inferential modes that augment human cognition.” (p. 71)
How do we do this? Drucker argues for us to recognize three basic principles of visualization, both as producers and as interpreters: a) the rationalization of a surface; b) the distinction of figure and ground; c) the delimitation of the domain of visual elements so that they function as a relational system.
In her sections on the most prevalent forms of visualization, I find most pertinent to the coming module on mapping her insight that a graphical scheme through which we relate to the phenomenal world structures our experience of it (p. 74). In other words, the mapping of the earth, sky, sea or the measurement of time, that are in themselves complex reifications of schematic knowledge, actually become the way in which we experience that thing. The week is seven days long and the month is 28-31 days long (because of lunar cycles) and thus astronomical tables become the way we structure time. But time isn’t like that; it isn’t linear, especially in the humanities! It contains flashbacks, memories, foreshadowings, relativities (it speeds up when we are nervous, and slows down when we are scared). So we are imposing structures from social and natural sciences onto human experience. Drucker argues that the shape of temporality is a reflection of beliefs and not standard metrics, and therefore asks how do we find a graphical means to inscribe the subjective experience of temporality or the spatial?
For example, digital mapping may give us the ability to georectify a manuscript map onto a coordinate system, but what does this give us? It might show us how accurate a mapmaker was, or was not; it might help us to locate an archaeological site with more probability, but it is ignoring the fact that the manuscript map, drawn perhaps on buckskin, or stone, or vellum is a representation (and a thin one at that) of a traveler’s or observer’s experience that we are then translating into a system of coordinates. What is absent is the story; way-finding depends upon narratives, travel accounts, diaries. We must be aware that maps produce the illusion of isomorphism, but this illusion is based on an elaborate system of abstract schema and concrete reality.
I am most captivated by the section of her chapter that focuses on visualizing uncertainty and interpretive cartography, as this is an area I have thought a lot about in the last five years during which I have been working with GIS. As a software, GIS gives us enormous power to produce knowledge as a generator; through the combinatory power of layers, and base maps, and points, and embedded data tables, GIS has often seduced me with its “deceptive naturalism of maps and bar charts” generated from spreadsheets that I and my students have spent months creating. It strengthens the fiction of observer-independence; the objectivity of the “bird’s eye view”, and, as Drucker so aptly states, “we rush to suspend critical judgment in visualization.” For me, however, and for the students I have worked with, the question of how to represent ambiguity has consumed us; as has also how to make ambiguity the ground of representation. I think here of the brilliant visualizations of Steffany Meredyk, ’14 as she created her interpretive map of the main stem of the Susquehanna River.
Using the work of Margaret Pearce, Steffany and I talked for long hours about the importance of reinserting the positionality of the observer into the visualizations of the river. Taking her “data” from accounts of massacres in the 1760-80s that occurred on the Susquehanna River, and using graphical means of Adobe Illustrator to represent ambiguity, uncertainty and emotion, I consider Steffany’s work to act as a model for the way in which we can use digital media and methods as humanists. We can, as Drucker observes, “model phenomenological experience; model discourse fields; model narratives and model interpretation.”