1. Information Visualization Chris North cs3724: HCI

2. What is Information Visualization? The use of computer-supported, interactive, visual representations of abstract data to amplify cognition

3. The Big Problem Data Human How? Data Transfer contacts, dict/thes, music, news, email, web Books, papers, scientific data, VB ref vision: 90Mb/sec Hear: 10/s, 44k/s Smell: 1 Touch: Taste Neural link: huge esp

4. 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!

5. Find the Red Square: The pop-out effect

6. Which state has highest Income? Relationship between Income and Education? Outliers?

7. Per Capita Income College Degree %

8. 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?

9. The Big Problem Data Human How? Data Transfer

10. Information Integration

11. The Bigger Problem Data Human How? Data Transfer

12. Interactive Graphics Homefinder

13. forms Avoid the temptation to design 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

14. 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!

15. More than just “data transfer” Glean higher level knowledge from the data Reveals data Reveals information about data that is not necessarily “stored” in the data Learn = data  information Insight! Hides data Hides “information” Nothing learned Zero insight

16. More than just “data transfer” Glean higher level knowledge from the data Reveals data Reveals information about data that is not necessarily “stored” in the data Learn = data  information Insight! Hides data Hides “information” Nothing learned Zero insight The Insight Factor

17. Class Motto Show me the data!

18. What’s the Big Deal?

19. Presentation is everything!

20. 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

21. Visualization Design Principles

22. Increase Data Density Calculate data/pixel “A pixel is a terrible thing to waste.”

23. Eliminate “Chart Junk” How much “ink” is used for non-data? Reclaim empty space (% screen empty) Attempt simplicity (e.g. am I using 3d just for coolness?)

24. Information Visualization Mantra Overview first, zoom and filter, then details on demand

25. InfoVis Design Principles Increase data density Eliminate “chart junk” Mantra: Overview first, zoom&filter, details on demand Insight factor Does the design reveal the data? Does the design help me explore, learn, understand? Show me the data!