Envisioning Information Lecture 4 – Multivariate Data Exploration Glyphs and other methods

1. Envisioning Information Lecture 4 – Multivariate Data Exploration Glyphs and other methods Hierarchical approaches Ken Brodlie ENV 2006

2. Glyph Techniques ENV 2006

3. Map data values to geometric and colour attributes of a glyph – or marker symbol Very many types of glyph have been suggested: Star glyphs Faces Arrows Sticks Shape coding Glyph Techniques ENV 2006

4. How do we place the glyphs on a chart? Sometimes there will be a natural location – for example? If not… two of the variates can be allocated to spatial position, and the remainder to the attrributes of the glyph Glyph Layouts ENV 2006

5. Each observation represented as a ‘star’ Each spike represents a variable Length of spike indicates the value Glyph Techniques – Star Plots ENV 2006

6. Each observation represented as a ‘star’ Each spike represents a variable Length of spike indicates the value Crime in Detroit Glyph Techniques – Star Plots ENV 2006

7. Star Glyphs – Iris Data Set ENV 2006

8. Chernoff Faces • Chernoff suggested use of faces to encode a variety of variables - can map to size, shape, colour of facial features - human brain rapidly recognises faces ENV 2006

9. Here are some of the facial features you can use Chernoff Faces http://www.bradandkathy.com/software/faces.html ENV 2006

10. Chernoff Faces • Demonstration applet at: • http://www.hesketh.com/schampeo/projects/Faces/ ENV 2006

11. .. And here is Chernoff’s face  Chernoff’s Face ENV 2006 http://www.fas.harvard.edu/~stats/People/Faculty/Herman_Chernoff/Herman_Chernoff_Index.html

12. Glyph is a matchstick figure, with variables mapped to angle and length of limbs As with Chernoff faces, two variables are mapped to display axes Stick figures useful for very large data sets Texture patterns emerge Idea due to RM Pickett & G Grinstein Stick Figures    - different angles that may be varied are shown   ENV 2006

13. Stick Figures 5D image data from Great Lakes region ENV 2006

14. 4 1 5 2 6 3 Shape Coding • Suitable where a variable has a Boolean value, ie on/off • A data item is represented as an array of elements, each element corresponding to a variable shade in box if value of corresponding variable is ‘on’ Arrays laid out in a line, or plane, as with other icon-based methods ENV 2006

15. Shape Coding Time series of NASA earth observation data ENV 2006

16. This item is { wet, Saturday, Amazon } Daisy Charts * variables and their values placed around circle Dry Wet * lines connect the values for one observation Leeds Showery Sahara Saturday Amazon Sunday http://www.daisy.co.uk ENV 2006

17. Daisy Charts - Underground Problems ENV 2006

18. Four variates: day, source, search terms, keywords Daisy Charts – News Analysis ENV 2006

19. Reducing Complexity in Multivariate Data Exploration ENV 2006

20. Success has been achieved through clustering of observations Hierarchical parallel co-ordinates Cluster by similarity Display using translucency and proximity-based colour Clustering as a Solution http://davis.wpi.edu/~xmdv/docs/vis99_HPC.pdf ENV 2006

21. Comparison One of 3 clusters ENV 2006

22. Hierarchical Parallel Co-ordinates ENV 2006

23. Reduce number of variables, preserve information Principal Component Analysis Transform to new co-ordinate system Hard to interpret Hierarchical reduction of variable space Cluster variables where distance between observations is typically small Choose representative for each cluster Subgroup has then been identified – showing what? 42 dimensions, 200 observations Reduction of Dimensionality of Variable Space http://davis.wpi.edu/%7Exmdv/docs/vhdr_vissym.pdf ENV 2006