CS 5764Information Visualization
Dr. Chris North
Today
1. What is Information Visualization?
2. Who cares?
3. What will I learn?
4. How will I learn it?
1. What is Information Visualization?
• The use of computer-supported, interactive, visual representations of abstract data to amplify cognition– Card, Mackinlay, Shneiderman
The Big Problem
Data
Human
How?
Data Transfer
•
•
The Big Problem
Data
Human
How?
Data Transfer
Vision:Aural:Smell:HapticsTasteesp
Human Vision
• Highest bandwidth sense
• Fast, parallel
• Pattern recognition
• Pre-attentive
• Extends memory and cognitive capacity• (Multiplication test)
• People think visually
• Brain = 8 lbs, vision = 3 lbs
Impressive. Lets use it!
Find the Red Square:
Find the Red Square:
Pre-attentive
• Which state has highest Income? Avg? Distribution?• Relationship between Income and Education?• Outliers?
Per Capita Income
Col
lege
Deg
ree
%
%
Visual Representation Matters!
• Text vs. Graphics
• What if you could only see 1 state’s data at a time? (e.g. Census Bureau’s website)
• What if I read the data to you?
• Graphics vs. Graphics• depends on user tasks, data, …
History: Static Graphics
Minard, 1869
The Big Problem
Data
Human
visualization
Data Transfer
The Bigger Problem
Data
Human
interactivevisualization
Data Transfer
Interactive Graphics
• Homefinder
Search Forms
• Avoid the temptation to design only a form-based search engine
• More tasks than just “search”• How do I know what to “search” for?
• What if there’s something better that I don’t know to search for?
• Hides the data• Only supports Q&A
• How can search be integrating with visualization?
User Tasks
• Easy stuff:• Min, max, average, %• These only involve 1 data item or value
• 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!
More than just “data transfer”
• Glean higher level knowledge from the data
Learn = data insight
• Reveals data• Reveals knowledge that is not necessarily “stored” in the data• Insight!
• Hides data• Hampers knowledge• Nothing learned• No insight
Some Philosophy…
• bigger picture: Insight• Vs. statistics, data mining, …
• Formal vs informal
• even bigger: Visual Analytics• Interaction as central
• Perception -> cognition
• Visualization in context
Class Motto
Show me the data!
2. Who Cares?
Presentation is everything
My Philosophy: Optimization
Visualization = the best of both
Impressive computation + impressive cognition
Computer•Serial•Symbolic•Static•Deterministic•Exact •Binary, 0/1•Computation•Programmed •Follow instructions•Amoral
Human•Parallel •Visual •Dynamic •Non-deterministic •Fuzzy•Gestalt, whole, patterns •Understanding •Free will•Creative •Moral
3. What Will I Learn?
• Design interactive visualizations
• Critique existing designs and tools
• Develop visualization software
• Empirically evaluate designs
• Understand current state-of-art
An HCI focus• A visualization = a user interface for data
*
Topics
Information Types: • Multi-D• 1D, 2D, 3D spatial• Hierarchies/Trees• Networks/Graphs• Document collections
Analytics:• Analytic theories• Analytic methods
Strategies:• Design Principles• Interaction strategies• Navigation strategies• Visual Overviews• Multiple Views• Empirical Evaluation• Development• Theory• High-Resolution Displays