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

ENV Glyph Techniques

ENV Glyph Techniques 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

ENV Glyph Layouts 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

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

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

ENV Star Glyphs – Iris Data Set

ENV 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 Chernoff Faces

ENV Chernoff Faces Here are some of the facial features you can use

ENV Chernoff Faces Demonstration applet at: –

ENV Chernoffs Face.. And here is Chernoffs face

ENV Stick Figures 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 - different angles that may be varied are shown

ENV D image data from Great Lakes region Stick Figures

ENV 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 Shape Coding

ENV Time series of NASA earth observation data Shape Coding

ENV Dry Wet Showery Saturday Sunday Leeds Sahara Amazon * variables and their values placed around circle * lines connect the values for one observation This item is { wet, Saturday, Amazon } Daisy Charts

ENV Daisy Charts - Underground Problems

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

ENV Reducing Complexity in Multivariate Data Exploration

ENV Clustering as a Solution Success has been achieved through clustering of observations Hierarchical parallel co- ordinates –Cluster by similarity –Display using translucency and proximity-based colour

ENV Comparison One of 3 clusters

ENV Hierarchical Parallel Co-ordinates

ENV Reduction of Dimensionality of Variable Space 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