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Information Design and Visualization
Chris North
CS 3724: HCI
To do
• Hall of Fame/Shame Presentations
• Project: Requirements Analysis
Problem scenarios
summativeevaluation
Information scenarios
claims about current practice
analysis ofstakeholders,field studies
Usability specifications
Activityscenarios
Interaction scenarios
iterativeanalysis ofusability claims andre-design
metaphors,informationtechnology,HCI theory,guidelines
formativeevaluation
DESIGN
ANALYZE
PROTOTYPE & EVALUATE
Functionality
Look and feel
The Problem
Data
Human
Goal: Insight How?
Data Transfer
Human Vision
• Highest bandwidth sense
• Fast, parallel
• Pattern recognition
• Pre-attentive
• Extends memory and cognitive capacity• (Multiplication test)
• People think visually
Impressive. Lets use it!
Find the Red Square:
• Which state has highest Income?• Relationship between Income and Education?• Outliers?
Per Capita Income
Col
lege
Deg
ree
%
Scenarios = Data + Tasks
• Data categories:– Spatial (1,2,3D)– Tabular (Multi-dimensional) – Network, Tree– Text, documents
• Combinations of categories
User Tasks
• Easy stuff: (1 or few items)
• Min, max, average, %
• Exact queries, known item search
• Hard stuff:• Patterns, trends, distributions, changes over time,
• outliers, exceptions,
• relationships, correlations, multi-way,
• combined min/max, tradeoffs,
• clusters, groups, comparisons, context,
• anomalies, data errors,
• Paths, …
Excel can do this
Visualization can do this!
Examples of Tabular data visualization
• DataMaps
• Spotfire
• TableLens
DataMaps
• demo
Spotfire
• Mapping data to graphics (x, y, size, color, shape…)
• Multiple views: brushing and linking
• Dynamic Queries
• Details window
Cars data
Visual Mapping: Step 1
1. Map: data items visual marks
Visual marks:• Points
• Lines
• Areas
• Volumes
• Glyphs
Visual Mapping: Step 2
1. Map: data items visual marks
2. Map: data attributes visual properties of marks
Visual properties of marks:• Position, x, y, z
• Size, length, area, volume
• Orientation, angle, slope
• Color, gray scale, texture
• Shape
• Animation, time, blink, motion
Mapping Example in Spotfire
• Film database
• Film dot
• Year x
• Length y
• Popularity size
• Subject color
• Award? shape
TableLens (Eureka by Inxight)
• Visual encoding of cell values
• Details expand within context (fisheye)
• Sorting
Cars data
Examples of Tree data visualization
• Windows Explorer
• Star Tree
• TreeMaps
Star Tree (Hyperbolic Tree)
• Focus+Context
• Radial; shrink with distance to center
• Drag to navigate
• Scalability?
• Xerox PARC, Inxight• http://startree.inxight.com/
Treemaps• Parent/child containment
• Size & color encoding
• Map of the Market: http://www.smartmoney.com/marketmap/
• People Map: http://www.truepeers.com/
• Coffee Map: http://www.peets.com/tast/11/coffee_selector.asp
• U. Maryland
• “Squarified” TreeMap• http://www.research.microsoft.com/~masmith/all_map.jpg
Context is Important!
Information Visualization Mantra• Overview first, zoom and filter, then details on demand• Overview first, zoom and filter, then details on demand• Overview first, zoom and filter, then details on demand• Overview first, zoom and filter, then details on demand• Overview first, zoom and filter, then details on demand• Overview first, zoom and filter, then details on demand
- Ben Shneiderman
What is Information Visualization?
The use of computer-supported,
interactive, visual representations
of abstract data to amplify cognition
Keys points
• Power of visual system
• scenario = data + tasks
• Mapping data to graphics & visual properties• 2 steps
• Interaction for what doesn’t fit in visual rep.• Dynamic queries, brushing, …
• Examples: tabular data, trees
• Mantra: Overview first…
• Choice of visual representation matters
What’s the Big Deal?
Presentation is everything!
- Edward Tufte
Project Step 3 – Design
• Due 3 weeks: get started early!
• Design space• Dimensions of the design space
• Alternative designs
• Claims analysis
• Formative evaluation• Wizard of Oz
• Refinements
• Final design:• Scenarios
• Representations