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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 $9000 8875 8750 8625 8500 1995 1996 1997 1998 1999 2000 Show entire scale Market $10,000 7500 5000 2500 0 1995 1996 1997 1998 1999 2000 Show in context Market $10,000 7500 5000 2500 0 1950 1960 1970 1980 1990 2000 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 0.5? 13 Changing Scale …with linear time scale Down = Bad ? Make it explicit 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 = value2 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 1 Width Area Volume 2 3 4 5 6 7 Width & height encoding 1 Width Width & Height 2 3 4 5 6 7 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 Life is a a highway Paris in the the spring 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! • Visualization in the periphery - evaluation » David, Christa, Ali, Jon Projects • Visualizing Multi-D functions » Reenal, Priya, Mrinmayee • Visualization of data structures – evaluation Dec 4 » Kunal, Vikrant, Anuj • Snap-together visualization » Rohit, Varun, Jeevak, Atul • Visual Break-down analysis with Financial data » Ganesh, Anusha, Muthukumar, Sandeep • Human-eye view Dec 6 » 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 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 •…