How (not) to lie with visualization cs5984: Information Visualization Chris North

Final Quiz 7 information types: 1d 2d 3d Multi-d Trees Graphs Doc collections

Where are we? Information Types: Multi-D 1D 2D Hierarchies/Trees Networks/Graphs Document collections 3D Topics: Design Principles Empirical Evaluation Java Development Visual Overviews Multiple Views Peripheral Views Workspaces Debates Vis. Lies

How (not) to lie with visualization Show and tell “USA Today” graphs…

Stock Market Crash?! $ Market

Show entire scale $10, Market

Show in context $10, Market

Another example

Percentages: 0% – 100% Employment rate = 100 – unemployment rate

Tufte’s Rule Visual attribute value should be directly proportional to data attribute value Lie factor = (visual effect) / (data effect) truth = 1.0

Company financial status

The hidden 0-points Lie factor = ?

Changing Scale ?

Changing Scale

…with linear time scale

Down = Bad ?

Make it explicit  Better Other examples: user performance, questionnaire results

Logarithmic data  log scale

Size Coding

Size Coding: width or area? =?

Size Coding

Width or Area Width = value Height = value Area = value 2 or Area = value width*height = value width = height = value 0.5 Problem: Using 2 dimensions to represent 1 dimension.

Volume coding? Height? Diameter? Surface area? Volume? 73 – 79 data difference = 5.5x 73 – 79 volume difference = 270x

Problem with area encoding Width Area Volume

Width & height encoding Width Width & Height

Solution: just use width (or height)

A Propaganda Classic

Hmmm… Low rank = good! Different time scales Not really tuition Artistic mood

How not to lie Show entire scale Show data in context Consistent, linear scale Log scale for log data Up vs. down: indicate direction of improvement Avoid size coding Use width OR height Don’t use both for same data attribute Avoid area coding

Visualization = Communication Communication is person dependent People have a lot of “baggage”

Expectations Paris in the the spring Life is a a highway Now is the the time

Re-training Red spades, black hearts Poor user performance even after being told

Orientation Who are they?

Orientation

Homework 3 Results Hinite bites. Too much hypertexty stuff Not enough zooming, infovisy stuff Keep trying to break out of the box!

Projects Visualization in the periphery - evaluation »David, Christa, Ali, Jon Visualizing Multi-D functions »Reenal, Priya, Mrinmayee Visualization of data structures – evaluation »Kunal, Vikrant, Anuj Snap-together visualization »Rohit, Varun, Jeevak, Atul Visual Break-down analysis with Financial data »Ganesh, Anusha, Muthukumar, Sandeep Human-eye view »Alex, Qiang, Ming, Vishal, Ahmed Bioinformatics »Quoc, Mudita, Dhananjay Online chat/video-conference visualization (virtual school) »Mahesh, Ben, Samal, Kuljeet, Harsha, Parool Digital libraries »Jun, Supriya, Abhishek, Anil Maps and in-vehicle interfaces »Ying, Xueqi, Zhiping, Rui Dec 4 Dec 6 Dec 11

Your Last InfoVis Assignment! Dec 18: Project Final Paper due Dec 7: ACM CHI short papers due Other destinations: March?: IEEE InfoVis papers due …