Visualization and Interpretation by Johanna Drucker

Author:Johanna Drucker
Language: eng
Format: epub, pdf
Publisher: MIT Press

Rationale for nonrepresentational approaches

This section presents an epistemological rationale, intellectual justification, and design outline for a nonrepresentational approach to modeling interpretation in a graphical environment.7 It begins with a critical discussion of the representational approaches that are the common form of information visualizations and suggests that the less familiar nonrepresentational approach could be used to augment these existing visualizations by supporting interpretative work that is closer to the practice of humanistic hermeneutic traditions. Representational display, based on large-scale processing, surrogates, and conventional visualizations, and nonrepresentational modeling at the level of the individual interpretative act operate at very different scales and support distinct intellectual work. In a representational approach, data precede display. Display is a surrogate produced according to automated protocols and algorithms. These cannot be altered or intervened except through rewriting their code, and the display, though interpretative and subject to interpretation, cannot be used as a means by which interpretation is actually modeled. While all visualizations express a model, they do not all provide a modeling environment. In the nonrepresentational approach proposed here, graphical input serves as a primary means of interpretative work. More significantly, a graphical environment that supports direct modeling of interpretation allows traditional humanistic approaches, close reading and marking of texts, documents, artifacts, or images to be integrated with computationally produced visualizations.

While information visualization has become ubiquitous in digital humanities, common tools for graphic expressions of data have limited value as primary modes of creating interpretation. They do not provide an environment in which interpretation is actually done directly. The traditional work of scholarly interpretation, at the level of individual artifact or text, often seems at odds with the computational processing that produces data visualizations. An alternative, grounded in a nonrepresentational approach to modeling interpretation in a graphical environment, could add essential capacity to the existing methods and platforms by providing a space for direct creation and inscription of interpretative work.

User-authored interpretation is premised on the distinction between display and modeling and signals a crucial difference between the two approaches. The modeling approach uses graphical means to produce interpretative work using visual argument structures such as contradiction, ambiguity, parallax, and point of view that are fundamentally interpretative in character. It engages conventions and dimensions of graphicality not used in standard chart, graph, timeline, and mapping software with their entities and attributes. The system I developed in the context of the 3DH project at the University of Hamburg is meant to be a radically innovative addition to existing visualizations and to add new dimensions in the service of interpretation and modeling alongside representation and display. The term modeling is being used here to refer to the process of creating a generalized intellectual schema or structure and should not be confused with the way the word is used to refer to three-dimensional rendering software.8

As noted here repeatedly, the visualizations adopted by digital humanists (charts, graphs, diagrams, maps, and timelines) were mainly developed in the natural sciences, social sciences, statistics, business applications, and other fields. These bear the hallmarks

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