The relationship between mapping and data visualization

The relationship between mapping and data visualization is somewhat ambiguous and generally ill-defined. In most cases, the two concepts are inextricably linked, and the terms mapping and visualizing are often used interchangeably. Yet, after some reflection it seems apparent that the two concepts are indeed distinct, that there are differences, and defining both in relation to each-other seems somehow imperative to understanding the territory.

The first incentive may be to think of mapping as a particular form of data visualization—tied to geography, and as such mapping data points in spatial proximity to one-another. Yet, when we speak of mapping, it is quickly apparent that geography is not the only possible organizing principle, and as such the use of the word ‘mapping’ suggests a larger concept.

In the introduction of Else/Where: Mapping, Janet Abrams and Peter Hall write that there are three types of space that can be conceivably mapped, from information space (finding patterns in large quantities of data), to physical space (orienting the body to the physical environment), to social space (representing relationships between people). Broadly speaking, therefore, mapping can be considered a process that determines how objects, or entities, are related to each-other by representing them on a (conceptual) field.

Lev Manovich considers visualization a subset of mapping. For Manovich, mapping is the translation from one form of representation to another. In The Anti-Sublime Ideal in Data Art, he uses the term data visualization for the mapping of abstract data that does not inherently have a visual representation. “By representing all data using the same numerical code, computers make it easy to map one representation into another: grayscale image into 3D surface, a sound wave into an image (think of visualizers in music players such as iTunes), and so on. Visualization then can be thought of as a particular subset of mapping in which a data set is mapped into an image.” (Manovich, The Anti-Sublime Ideal in Data Art). He describes data visualization as the “mapping of data into the visual domain.” In other words, if mapping typically translates physical entities into an image, data visualization translates (or maps) abstract data into an image.

James Corner presents another definition of mapping in The Agency of Mapping. Quoting Deleuze and Guattari, Corner suggests that one must separate a map from a tracing. A tracing is simply a reflection of a real situation or process, and as such does not present a point of view. A map, on the other hand, has agency: it is the product of a creative activity that suggests new narratives and conceptual constructs by which to better understand the topic under consideration. “Mappings have agency because of the double-sided characteristic of all maps. First, their surfaces are directly analogous to actual ground conditions; as horizontal planes, they record the surface of the earth as direct impressions. […] By contrast, the other side of this analogous characteristic is the inevitable abstractness of maps, the result of selection, omission, isolation, distance and codification.” (Corner, The Agency of Mapping).

This idea is reiterated in episode 110 of This American Life, Mapping, which states that maps focus on a single topic at a time—ignoring all other information that is not relevant. This is precisely the omission or selection that Corner is referring to, that gives mapping its agency. The next question, however, becomes whether tracings—in the way that they are defined by Corner and Deleuze—can in fact exist, as they are necessarily the product of human agency of some kind. But this is perhaps the critical distinction: mapping involves a particular agenda, a political motive, whereas tracings are created without a particular motive in mind. It is a subtle yet powerful distinction. This quote from J. B. Harley seems relevant: “‘Far from holding up a simple mirror of nature that is true of false, maps redescribe the world—like any other document—in terms of relations of power and of cultural practices, preferences, and priorities’” (Janet Abrams and Peter Hall, Else/Where: Mapping).

Conclusively, to follow Corner’s argumentation, it seems that the distinction between mapping and data visualization may hinge on the understanding of mapping as a process with agency. Visualization, on the other hand, is a neutral term, expressing neither agency nor its antonym, structure. And while its purpose is defined as generating insight and drawing conclusions, it does not imply a particular political motive. As such, visualization could be considered the superordinate concept, contradicting Manovich’s idea of it being a subset of mapping. While ultimately it might be considered a question of semantics, regarding mapping as a process with agency offers a more nuanced approach to understanding the relationship between the two concepts.

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