Multiperspectivality and Experimental Data Visualization

Multiple Perspectives

  • Lines of sight: What knowledge might be available to one person but not another person (e.g., who spoke to whom)?
  • Emphases: What features of data might be very important to one person but wouldn’t occur to someone else (e.g., building accessibility, gender-neutral restrooms)?
  • Emotion: Are there ways to visualize data that reflect emotional states (e.g., calm vs. impassioned; for reference)? Dataset: Albuquerque pollen counts. Example question: How does this data look to someone who isn’t allergic to pollen? Someone who is?
  • Perception: What do “traditional” data visualizations assume about what we value and how we absorb information? Would it be possible to build a dataviz from another viewpoint about how to take in information or interact with the world? Dataset: Property lost on NYC subway. Example question: Visualize the dataset “conventionally.” Now visualize it from the POV of someone encountering the lost property on a moving subway train.
  • Power and authority: How does the world look different to someone who assumes they have control over their environment? Someone who can’t take that power for granted? Dataset: Title 9 Cases. Example question: How would a college administrator view this dataset? How about a potential victim?Dataset: Traffic stops in Washington, DC. Example question: How would a police officer use this data? What about a person concerned about racial profiling?



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