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UI for Big Data Visualization | Jonathan Stray | UX Week 2012


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Visualization is great way to understand data, but it breaks down when the data gets big. Simply plotting everything to the screen won’t work, because there isn’t enough screen real estate, interactions slow to a crawl, and human working memory isn’t up to the task anyway. Big data requires specific interaction techniques for visual exploration, such as filtering, summarization, and context. We’ll go over some basic principles, and I’ll show examples of recent systems, including our work on the Overview Project, a system for visual exploration of huge unstructured document sets.

Published in: Design, Education

UI for Big Data Visualization | Jonathan Stray | UX Week 2012

  1. interfaces for big data visualization jonathan stray overview project associated press
  2. Ben Fry,Computational Information Design
  3. visualization extends perception
  4. “Visualization allows people to offloadcognition to the perceptual system, usingcarefully designed images as a form ofexternal memory.The human visual system is a very high-bandwidth channel to the brain, Tamara Munzner with asignificant amount of processing occurring inparallel and at the pre-conscious level.”
  5. a visualizationturns something you want to find into something you can see
  6. clusters outliersextents correlations
  7. work with human perception
  8. work with human senseswork with human memorywork with human cognition
  9. you have never seen a violin.perception involves interactively directing narrow attention
  10. don’t show it all.(you can’t anyway)
  11. filter
  12. summarize
  13. categories = “distance metric” + clustering algorithmd(x, y) ≥ 0d(x, x) = 0d(x, y) = d(y, x)d(x, z) ≤ d(x, y) + d(y, z) k-means single link hierachical
  14. annotate
  15. snapshots tags notes history
  16. demothe overview project
  17. the world does not spring magically into our heads. neither does big data.Interface extends perception. thanks @jonathanstray