1. Lecture 05: Animated Transition and Animation
October 10, 2017
COMP 177 Visualization

2. Admin Assignment 2 was due last night Sign up for grading this Friday!
Grading on Thursday – first come first serve
Assignment 3 – Animated Transition

3. Set Theory (from Lecture 2)
Bijection (one visual attribute, one data attribute)
Surjection (multiple visual attribute to one data attribute)
Every element in Y has 1 or more corresponding element in X
Injection (One to one mapping, but not all data elements are mapped)
Every element in X has a mapping in Y, but not true in reverse
Other scenarios?

4. Card, Mackinlay (1997) Symbol Meaning D Data Type ::= N (Nominal),
F : Function for recoding data ::=
f (unspecified)
> (filter)
s (sorting)
mds (multidimensional scaling)
↑ (interactive input to a function)
D’ : Recoded Data Type (see D)
CP : Control Processing tx (text)
M : Mark types ::= P (Point), L (Line),
S (Surface), A (Area), V (Volume)
R : Retinal (mark) properties ::=
C (Color), S (Size),
— (Connection), [] (Enclosure)
XYZT : Position in space time ::= N, O, Q, * (non-semantic use of space-time)
V : View transformation ::=hb(hyperbolic mapping)
W : Widget ::= sl(slider) rb(radio buttons)
Symbol Meaning
D Data Type ::=
N (Nominal),
O (Ordinal),
Q (Quantitative).
QX (Intrinsically spatial),
Qlon (Geographical)
NxN (Set mapped to itself - graphs)

5. Example 1: Ozone Mapping
Card and Mackinlay, The Structure of the Information Visualization Design Space

6. Example 1: Ozone Mapping
The rows of the table describe the variables with the case variable (“Samples”) at the top and the value variables below. The nominal (N) set of Samples is mapped to point marks (P in column M), which have their retinal property of color (C in column R) mapped to the Ozone variable. The ozone mapping includes a function (f) that converts the quantitative (Q) ozone measurements to an ordinal (O) set that can be easily mapped to a set of colors. The quantitative (Q) variables of Longitude, Latitude, and Height are mapped to the positions X, Y, and Z, which determine the position of the point marks. The Date variable is mapped to time (T), which creates an animated visualization. Table 1 makes it clear that Figure 1 is a 3D animated visualization involving colored points.

7. Example 2: GIS

8. Example 2: GIS
Table 2 describes the map part of Figure 2. The Offices variable is mapped to line marks (L). The Profit variable is mapped to the size of these lines (Sz in the R column). Profits are also mapped to the Z-axis and via a function (f) to a nominal set indicating the sign of the profits. This nominal set is mapped to the color of the lines (C in the R column). Table 2 clearly reveals that multiple graphical techniques are used to describe the Profit variable in order to enhance the perception of this important data variable

9. Other Examples

11. Treemap Example

12. Exercise: Treemap
Let’s think about your assignment 1: Squarified Treemap.
How many (minimum) dimensions of data does it need?
Accept 1 dimension or 2 dimensions
Write out the “mapping” of Squarified Treemap
Starting with the basic (no hierarchy)
Add hierarchy

13. Treemap Example
The problem is that the same variable is mapped onto two different position presentations, each half of the time Q -> X (half time) Q -> Y (half time) giving an inconsistent mapping and prohibiting the user from forming an easy image. What the user should be able to take from the image is essentially Retinal: Size coding, but the same Size can have many different visual manifestations, each with a different aspect ratio. Thus the space-filling property of the visualization comes at a perceptual cost, which is clearly shown in Table 9.

14. Remco’s Claim
All visualizations depicting the same data that follow bijective visual-data mapping are in fact isomorphic to each other
Never tested, but would love to be able to prove this
For example:

15. Remco’s Claim
Note that this does not mean that there is only one way to transition from one visualization to another.
For example, for two bivariate visualizations of dimensions (x, y), there are at least two ways to do the transition:
Animate X, followed by animate Y
Animate Y, followed by animate X
(Note: don’t try to do two at the same time. More on this later)

16. Remco’s Claim
For example, for two bivariate visualizations of dimensions (x, y), there are at least two ways to do the transition:
Animate X, followed by animate Y
Animate Y, followed by animate X
Following this logic, consider the case of:
Bar  Line
How many ways are there to do this transition?
(Hint: define the mappings first)

17. Exercise
Considering that all the visualizations depict the same data and relationships, how can one go from one visualization to another? ?

18. Tree -> Tree (with Nodes)

19. Tree (with Nodes) -> Icicle

20. Icicle -> Circle Icicle(?)

21. Circle Icicle -> Packed Circle?
Invert Space
(negative space becomes positive space) OR
Shift each row up from child into parent (recursively)

22. Circle Icicle -> Packed Circle
Invert Space
(negative space becomes positive space) OR
Shift each row up from child into parent (recursively)

23. Other Paths?

24. Remco’s Claim #2
For every visualization that uses the Cartesian coordinate system, there is a corresponding visualization in the Polar coordinate system (and vice versa)
Question is with the mapping
(x -> r, y -> theta), or
treemap to circle packing?
This was one really easy way to get publications in the visualization community in the early days

25. Layout2:
(because “size” is vague)
Marks
Layout

26. Notice that… There is a clear difference between
Visual layout (visual metaphor)
Visual marks
Each of these can have a coordinate system
WARNING! While some times it’s easy to swap a visual mark with another, these two considerations are not always independent
For example, think “wedge” as a visual mark. Works well with pie chart, but does not work with a rectangular layout

27. Animation vs. Animated Transitioning
Animated Transition is a subset of animation techniques in general:
Animated transitioning focuses on the specific goal of leading the user from one view to another in a cohesive way
Whereas animation, as it is often mapped to the “time” component of temporal data, introduces new information.

28. Powers of Animation
Animation (movement) directly connects to our visual system
<blink> In fact, a moving object entering your perceptual space immediate draws your attention. You cannot avoid this or suppress this instinct. </blink>

29. Animation
Long story short, use animation sparingly. Some exceptions to this rule:
Animated Transitioning: To better denote a “cause” and “effect” relationship. E.g., in zooming. Or to help the user transition between two states in a visualization.
Storytelling: Focus the user on a specific aspect of the visualization.
Artistic reasons (part of storytelling?) to particularly highlight certain emotions (sense of chaos, sense of flatness, etc.)

30. Why is Animation So Bad? Part 1
Overused. When every object in the visualization is moving, it is impossible for any one person to keep track of all of them. E.g. think Gapminder video
This means that two viewers of the same animation walks away with different findings (if you don’t have Hans narrating to you)

31. Why is Animation So Bad? Part 2
Limited cognitive abilities
The human’s short-term memory starts to degrade within a second or so. Animation of important information overloads this cognitive resource in no time. This is easy to test – if I ask you to recall a particular frame in the Gapminder video, you probably can’t do it.
The humans’ attention span is limited. Asking someone to focus (keep track) of a lot of moving objects over a long period of time is extremely taxing!

32. Why is Animation So Bad? Part 3
The limited attention leads to:
Change Blindness
This Task is much harder if we were to animate these two frames…

33. Why is Animation So Bad? Part 3
The limited attention leads to:
Change Blindness

34. Alternative to Animation
There are different ways to “flatten” the animation.
In temporal data visualization, one easy way is to treat time as a quantitative value. For example, map time to the y-axis of a line chart
Treat animation as a sequence of images and use small-multiples
Research has shown that user’s are faster and more accurate when using small-multiples to analyze the same data used in the Hans Rosling video (than using animation).