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Extending human perception with data visualisation notes

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Extending human perception
with
Data visualisation
This is taken from a talk on Big Data.
About visual tools and technique...
Visualisations of big data are often beautiful but useless.
This is art, not insight.
Communicating insights are not just about pretty graphics, that’s just design porn.
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Extending human perception with data visualisation notes

  1. 1. Extending human perception with Data visualisation This is taken from a talk on Big Data. About visual tools and techniques for communicating data. That’s a visualisation of Facebook connections.
  2. 2. Visualisations of big data are often beautiful but useless. This is art, not insight.
  3. 3. Communicating insights are not just about pretty graphics, that’s just design porn.
  4. 4. “Visualization allows people to offload cognition to the perceptual system, using carefully designed images as a form of external memory.” Tamara Munzner Department of Computer Science University of British Columbia Visualisation extends perception & memory. http://www.cs.ubc.ca/labs/imager/tr/2009/VisChapter/akp-vischapter.pdf
  5. 5. A visualisation turns something you want to find into something you can see.
  6. 6. 0" 5" 10" 15" 20" 25" 30" 35" 40" 45" 50" 6/01/08" 6/03/08" 6/05/08" 6/07/08" 6/09/08" 6/11/08" 6/01/09" 6/03/09" 6/05/09" 6/07/09" 6/09/09" 6/11/09" 6/01/10" 6/03/10" 6/05/10" 6/07/10" 6/09/10" 6/11/10" 6/01/11" 6/03/11" 6/05/11" 6/07/11" 6/09/11" 6/11/11" 6/01/12" 6/03/12" 6/05/12" 6/07/12" 6/09/12" 6/11/12" Late%&mesheets% A visualisation turns something you want to find into something you can see.
  7. 7. How do we extend the human ability to perceive data? We make it possible for our eyes to see trends and identify differences. Work with human perception: Senses, memory, cognition.
  8. 8. This can be done by using a variety of “visual search” techniques to make data “Pop out”. Colour, size, orientation, shape, grouping, motion,
  9. 9. This can be done by using a variety of “visual search” techniques to make data “Pop out”. Colour, size, orientation, shape, grouping, motion,
  10. 10. This can be done by using a variety of “visual search” techniques to make data “Pop out”. Colour, size, orientation, shape, grouping, motion,
  11. 11. This can be done by using a variety of “visual search” techniques to make data “Pop out”. Colour, size, orientation, shape, grouping, motion,
  12. 12. This can be done by using a variety of “visual search” techniques to make data “Pop out”. Colour, size, orientation, shape, grouping, motion,
  13. 13. This can be done by using a variety of “visual search” techniques to make data “Pop out”. Colour, size, orientation, shape, grouping, motion,
  14. 14. This can be done by using a variety of “visual search” techniques to make data “Pop out”. Colour, size, orientation, shape, grouping, motion,
  15. 15. Don’t show it all at once. Filter, Animate, Summarise,
  16. 16. Don’t show it all at once. Filter, Animate, Summarise,
  17. 17. Don’t show it all at once. Filter, Animate, Summarise,
  18. 18. x 133 Don’t show it all at once. Filter, Animate, Summarise,
  19. 19. Look at me! Annotate and label – help people not get lost.
  20. 20. Text Clusters Outliers Correlations Patterns to look for: Clusters, outliers, extents, correlations. http://www.google.com/publicdata/explore? ds=d5bncppjof8f9_&ctype=b&strail=false&nselm=s&met_x=sp_dyn_le00_in&scale_x=lin&ind_x=false&met_y=sp_dyn_tfrt_in&sc ale_y=lin&ind_y=false&met_s=sp_pop_totl&scale_s=lin&ind_s=false&dimp_c=country:region&ifdim=country&hl=en&dl=en&icon Size=0.5&uniSize=0.035#! ctype=b&strail=false&bcs=d&nselm=s&met_x=sp_dyn_le00_in&scale_x=lin&ind_x=false&met_y=sp_dyn_tfrt_in&scale_y=lin&ind _y=false&met_s=sp_pop_totl&scale_s=lin&ind_s=false&dimp_c=country:region&ifdim=country&pit=-153914400000&hl=en_US &dl=en&ind=false
  21. 21. Look at me! Look at me! Look at me! Minimum necessary difference. Reduce visual noise. Tufte: What is the minimum number of pixels required to highlight the difference between data.
  22. 22. Look at me! Look at me! Look at me! Minimum necessary difference. Reduce visual noise. Tufte: What is the minimum number of pixels required to highlight the difference between data.
  23. 23. You are here You can’t look at big data sets all at once, you can look at 2 parts of it at once to try to make sense of them together in your mind. Interface extends perception, allowing us to understand what it is telling us. Total Perspective Vortex - Zaphod Bebblebrox

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