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Extending human perception with data visualisation notes
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. Visualisations of big data are often beautiful but useless.
This is art, not insight.
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
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. This can be done by using a variety of “visual search” techniques to make data “Pop out”.
Colour, size, orientation, shape, grouping, motion,
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. This can be done by using a variety of “visual search” techniques to make data “Pop out”.
Colour, size, orientation, shape, grouping, motion,
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. This can be done by using a variety of “visual search” techniques to make data “Pop out”.
Colour, size, orientation, shape, grouping, motion,
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. This can be done by using a variety of “visual search” techniques to make data “Pop out”.
Colour, size, orientation, shape, grouping, motion,
15. Don’t show it all at once.
Filter, Animate, Summarise,
16. Don’t show it all at once.
Filter, Animate, Summarise,
17. Don’t show it all at once.
Filter, Animate, Summarise,
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. 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. 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. 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