An analysis of visual epistemology in the digital humanities, with attention to the need for interpretive digital tools within humanities contexts.In the several decades since humanists have taken up computational tools, they have borrowed many techniques from other fields, including visualization methods to create charts, graphs, diagrams, maps, and other graphic displays of information. But are these visualizations actually adequate for the interpretive approach that distinguishes much of the work in the humanities? Information visualization, as practiced today, lacks the interpretive frameworks required for humanities-oriented methodologies. In this book, Johanna Drucker continues her interrogation of visual epistemology in the digital humanities, reorienting the creation of digital tools within humanities contexts.
Drucker examines various theoretical understandings of visual images and their relation to knowledge and how the specifics of the graphical are to be engaged directly as a primary means of knowledge production for digital humanities. She draws on work from aesthetics, critical theory, and formal study of graphical systems, addressing them within the specific framework of computational and digital activity as they apply to digital humanities. Finally, she presents a series of standard problems in visualization for the humanities (including time/temporality, space/spatial relations, and data analysis), posing the investigation in terms of innovative graphical systems informed by probabilistic critical hermeneutics. She concludes with a final brief sketch of discovery tools as an additional interface into which modeling can be worked.
Author(s): Johanna Drucker
Publisher: The MIT Press
Year: 2020
Language: English
Pages: 203
City: Cambridge
Cover
Acknowledgments
Framework: Creating the Right Tools and Platforms
Outline of this book
Intellectual foundations
1. Visual Knowledge (or Graphesis): Is Drawing as Powerful as Computation?
Visual epistemology
Visual and digital
Visuality, perception, and cognition
Images of nonvisible phenomena
Aesthetic images as knowledge arguments
and
Graphical specificity
Notation and inscription
Philosophical issues of imitation, mimesis, and simulation
Visualization methods used in computing
Summary
Next
2. Interpretation as Probabilistic: Showing How a Text Is Made by Reading
Interpretation: A probabilistic approach
Digital humanities and probability
Constructedness: Visuality and probability
Distinguishing data and capta
Discourse fields
Ivanhoe: Designing a game of interpretation
Modeling interpretation: Implications and work ahead
Probabilistic aspects—design challenges
Ambiguity and uncertainty
Implications
3. Graphic Arguments: Nonrepresentational Approaches to Modeling Interpretation
Graphical input
Rationale for nonrepresentational approaches
Justification
Design of the concept modeling environment
Design brief
Graphical features
Activators and inflectors
Dimensions of interpretation
The idea of graphical enunciation
4. Interface and Enunciation, or, Who Is Speaking?
Defining interface
Interface theory
Frame analysis
Constructed subjects
Enunciation
Critical interventions
5. The Projects in Modeling Interpretation, or, Can We Make Arguments Visually?
General principles
The projects
Temporal modeling
a. Interpretative timelines
b. Heterochronologies
Spatial modeling
Network inflection
Modeling interpretation in a rich research (discourse) field
Comparative ontologies
Enunciative interfaces
Summary
Appendix: Design Concepts and Prototypes
Demonstration of principles Graphic argument
Affective metrics
Inflection
Point-ofview systems
Direct input (two-way screen)
Projects
A. Temporal modeling
B. Heterochronologies (a version of the comparative ontologies)
Spatial modeling
Network inflection
Comparative ontologies
Argument creation and a rich research field
Enunciative interface
Other images and features
Conclusion
Notes
Framework
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Appendix
Index
