14.1Vis_04

Data VisualizationData Visualization

Lecture 14Information Visualization :

Part 2

14.2Vis_04

Glyph Techniques – Star Plots

Glyph Techniques – Star Plots

Star plots– Each observation

represented as a ‘star’

– Each spike represents a variable

– Length of spike indicates the value

Crime inDetroit

14.3Vis_04

Chernoff FacesChernoff 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

14.4Vis_04

Chernoff FacesChernoff Faces

Here are some of the facial features you can use

http://www.bradandkathy.com/software/faces.html

14.5Vis_04

Chernoff FacesChernoff Faces

Demonstration applet at:– http://www.hesketh.com/

schampeo/projects/Faces/

14.6Vis_04

Chernoff’s FaceChernoff’s Face

.. And here is Chernoff’s face

http://www.fas.harvard.edu/~stats/People/Faculty/Herman_Chernoff/Herman_Chernoff_Index.html

14.7Vis_04

Daisy ChartsDaisy Charts

Dry

Wet

Showery

Saturday

Sunday

Leeds

Sahara

Amazon

variables andtheir valuesplaced aroundcircle

lines connectthe values forone observation

This item is { wet, Saturday, Amazon }

http://www.daisy.co.uk

14.8Vis_04

Daisy Charts - Underground Problems

Daisy Charts - Underground Problems

14.9Vis_04

Networks of InformationNetworks of Information

In many applications of InfoVis, the observations are linked in a graph structure

– Directory trees– Web sites

We can still represent as a data table

– The link(s) appear as column(s) in the data table

1

2 3

Graph may bedirected orundirected

14.10Vis_04

Examples of Networks of Information

Examples of Networks of Information

My Windows2000filestore

Automobile web site- visualizing links

14.11Vis_04

Graph Drawing AlgorithmsGraph Drawing Algorithms

There are various general graph layout software packages

Example is dotty from AT&T suite called GraphViz

Nodes of graph laid out automatically

– here an undirected graph

– applications?

http://www.graphviz.org

14.12Vis_04

DottyDotty

Directed graph for softwareengineering application

14.13Vis_04

Hierarchical InformationHierarchical Information

Important special case is where information is hierarchical

– Graph structure can be laid out as a tree

http://www.cwi.nl/InfoVisu/Examples

14.14Vis_04

Tree MapsTree Maps

Screen filling method which uses a hierarchical partitioning of the screen into regions depending on attribute values

Alternate partitioning parallel to X and Y axes

Suitable for hierarchical type data– size of files in a user directory

14.15Vis_04

Tree Map of FilestoreTree Map of Filestore

Suppose user hasthree subdirectories:A, B and C

First partition in Xaccording to totalsize of each sub-directory

A B C

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Tree Map of FilestoreTree Map of Filestore

A B C

Then within eachsubdirectory, wecan partition in Yby the size ofindividual files,or furthersubdirectories

14.17Vis_04

Treemap ExampleTreemap Example

Usenet newsgroups

For history oftreemaps see:www.cs.umd.edu/hcil/treemap-history

Developed over many years by Ben Schneiderman and colleagues

14.18Vis_04

Hyperbolic TreesHyperbolic Trees

This is popular method of displaying hierarchical structures such as Web sites

Place home page in centre– with linked pages connected by

hyperbolic arcs– further arcs link to further links– see:

www.acm.org/sigchi/chi95/proceedings/papers/jl_bdy.htm

14.19Vis_04

Hyperbolic TreesHyperbolic Trees

Automobilesweb site

Home pagein centre

Click on linkyou want ...

14.20Vis_04

Hyperbolic TreesHyperbolic Trees

Auto Historymoves to centre of screen

Click on nextlink...

14.21Vis_04

Hyperbolic TreesHyperbolic Trees

Henry Fordis now at the centreand so on...

14.22Vis_04

Hyperbolic TreesHyperbolic Trees

www.inxight.com

Also worksfor familytrees...

14.23Vis_04

Document VisualizationDocument Visualization

Large collections of electronic text– the Web is prime example!

Powerful search and retrieval engines– return documents based on some

sort of keyword search How do we visualize the results of

a query? http://zing.ncsl.nist.gov/~cugini/uicd/

viz.html

14.24Vis_04

Document RetrievalDocument Retrieval

Suppose search returns a keyword strength– ie user enters a number of

keywords– engine returns list of documents– each document has a score for each

keyword specified (eg number of occurrences)

– most relevant document has largest total score

14.25Vis_04

Document SpiralDocument Spiral

Arrange docsin spiral, mostrelevant at centre

14.26Vis_04

Document Three-Keyword Axes Display

Document Three-Keyword Axes Display

One keywordper axis

Plot docs ina scatter plotusing keywordstrengths toposition alongaxes

Same keywordon all axes linesdocs up on X=Y=Z line

14.27Vis_04

Nearest Neighbour Sequence

Nearest Neighbour Sequence

Choose one docand place on circle

Find the closest in‘keyword strength’space and placeadjacent to it.... and so on