STACKED GRAPHS STACKED GRAPHS EVOLUTION OF STACKED GRAPHS Stacked - - PowerPoint PPT Presentation

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A. Thudt | J. Walny | C. Perin | F. Rajabiyazdi | L. MacDonald | R. Vardeleon | S. Greenberg | S. Carpendale ASSESSING THE READABILITY OF STACKED GRAPHS STACKED GRAPHS STACKED GRAPHS EVOLUTION OF STACKED GRAPHS Stacked Area Chart Themeriver

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SLIDE 1

ASSESSING THE READABILITY OF

STACKED GRAPHS

  • A. Thudt | J. Walny | C. Perin | F. Rajabiyazdi | L. MacDonald | R. Vardeleon | S. Greenberg | S. Carpendale
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SLIDE 2

STACKED GRAPHS

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SLIDE 3

STACKED GRAPHS

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SLIDE 4

EVOLUTION OF STACKED GRAPHS

Stacked Area Chart Themeriver Streamgraph

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SLIDE 5

READABILITY

  • W. S. Cleveland and R. McGill. Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical
  • Methods. Journal of the American Statistical Association, 79(387):531–554,1984.
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SLIDE 6

READABILITY

  • W. S. Cleveland and R. McGill. Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical
  • Methods. Journal of the American Statistical Association, 79(387):531–554,1984.
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SLIDE 7

INFORMATION LEVELS

Elementary

  • J. Bertin. Graphics and Graphic Information Processing. Walter de Gruyter & Co, 1981.
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SLIDE 8

INFORMATION LEVELS

Elementary Intermediate

  • J. Bertin. Graphics and Graphic Information Processing. Walter de Gruyter & Co, 1981.
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SLIDE 9

INFORMATION LEVELS

Elementary Intermediate

  • J. Bertin. Graphics and Graphic Information Processing. Walter de Gruyter & Co, 1981.
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SLIDE 10

INFORMATION LEVELS

Elementary Intermediate Global

  • J. Bertin. Graphics and Graphic Information Processing. Walter de Gruyter & Co, 1981.
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SLIDE 11

INFORMATION LEVELS

Elementary Intermediate Global

  • J. Bertin. Graphics and Graphic Information Processing. Walter de Gruyter & Co, 1981.
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SLIDE 12

CONDITIONS

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SLIDE 13

STACKED AREA CHART (STACK)

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SLIDE 14

THEMERIVER (THEME)

  • S. Havre, B. Hetzler, and L. Nowell. ThemeRiver: visualizing theme changes over time.

IEEE Symposium on Information Visualization, INFOVIS’ 00, 2000.

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SLIDE 15

STREAMGRAPH (STREAM)

  • L. Byron and M. Wattenberg. Stacked graphs–geometry & aesthetics. IEEE TVCG, 14(6):1245–52, 2008.
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SLIDE 16

INTERACTIVE STACKED GRAPH (INT)

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SLIDE 17

DATASETS

Box Office Revenue Dataset (Movies) | 300 time-series | 20 time-points 311 Calls in NYC (Calls) | 10 time-series | 35 time-points Random | 30 time-series | 30 time-points

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SLIDE 18

TASKS

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SLIDE 19
  • I. INDIVIDUAL DISCRIMINATION

Which is larger: the value of the blue time-series at A or the value of the yellow time-series at B?

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SLIDE 20
  • II. STREAM COMPARISON

The following area chart represents [time-series data]. In the graph below, which stream represents the same [time-series]?

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SLIDE 21
  • III. AGGREGATE DISCRIMINATION

Is the combined value of all time-series larger at A or at B?

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SLIDE 22

HYPOTHESES

H1: Correctness for Aggregated Discrimination (III): > > STACK INT THEME STREAM

Less Correct More Correct

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SLIDE 23

HYPOTHESES

H2: Correctness for Individual Discrimination (I) and Stream Comparison (II): > > > STACK INT THEME STREAM

Less Correct More Correct

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SLIDE 24

HYPOTHESES

H3: Completion Time for all tasks: > STREA STACK INT THEME STREAM

Slower Faster

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SLIDE 25

16 PARTICIPANTS

9 male, 5 female, 2 did not specify 18–65 years various occupations

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SLIDE 26

STUDY SETUP

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SLIDE 27

STUDY DESIGN

within-subjects design balanced 4x4 Latin square training with all tasks for each condition 4 cond × 3 tasks x 3 datasets = 36 trials

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SLIDE 28

DATA

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SLIDE 29

EFFECT SIZES

strong & large effect strong & small effect

> ¡

> >

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SLIDE 30

EFFECT SIZES

weak & large effect weak & small effect

≥ ¡

≥ ¡

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SLIDE 31

RESULTS

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SLIDE 32

INDIVIDUAL DISCRIMINATION

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SLIDE 33

INDIVIDUAL DISCRIMINATION

Less Correct More Correct

Strong & small effect

STACK INT THEME STREAM

> ¡

C o r re c t n e s s

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SLIDE 34

INDIVIDUAL DISCRIMINATION

INT STACK INT STREAM

> ¡

Strong & small effect

C o m p l e t i o n Ti m e

Slower Faster

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SLIDE 35

STREAM COMPARISON

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SLIDE 36

STREAM COMPARISON

STACK THEME STREAM

Strong & small effect Strong & small effect

> >

INT

Less Correct More Correct

C o r re c t n e s s

Weak & large effect

≥ ¡

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SLIDE 37

STREAM COMPARISON

C o m p l e t i o n Ti m e

Strong & small effect Weak & small effect Weak & small effect

> ≥ ¡ ≥ ¡

Slower Faster

STACK THEME STREAM INT

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SLIDE 38

AGGREGATE DISCRIMINATION

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SLIDE 39

AGGREGATE DISCRIMINATION

THEME STREAM

Strong & small effect

>

Less Correct More Correct

C o r re c t n e s s

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SLIDE 40

AGGREGATE DISCRIMINATION

STACK INT THEME STREAM

Strong & small effect Strong & small effect

> >

Less Correct More Correct

C o r re c t n e s s

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SLIDE 41

AGGREGATE DISCRIMINATION

STACK INT STREAM

C o r re c t n e s s

THEME

≈ 100% Correctness

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SLIDE 42

AGGREGATE DISCRIMINATION

STACK THEME

Strong & small effect

>

C o m p l e t i o n Ti m e

Slower Faster

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SLIDE 43

AGGREGATE DISCRIMINATION

STACK INT THEME STREAM

Strong & small effect Strong & large effect Strong & small effect

>

> ¡

>

C o m p l e t i o n Ti m e

Slower Faster

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SLIDE 44

AGGREGATE DISCRIMINATION

STACK INT STREAM

Strong & large effect Strong & large effect

> ¡ > ¡

C o m p l e t i o n Ti m e

Slower Faster

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SLIDE 45

IMPLICATIONS

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SLIDE 46

WHEN TO USE WHICH STACKED GRAPH?

STREAM for elementary and global level tasks with static graph

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WHEN TO USE WHICH STACKED GRAPH?

STREAM for elementary and global level tasks with static graph INT for intermediate and global level tasks

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WHEN TO USE WHICH STACKED GRAPH?

STREAM for elementary and global level tasks with static graph INT for intermediate and global level tasks STACK did not provide advantage, but perceived as pleasing and easy to read

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OTHER IMPLICATIONS

Theoretical Models can work to predict perceptual advantages

do not show extent of advantages

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SLIDE 50

OTHER IMPLICATIONS

Theoretical Models can work to predict perceptual advantages

do not show extent of advantages

Interaction can be used for mitigating perceptual difficulties

avoid increasing memory load

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SLIDE 51

THANK YOU!

Project Page: http://j.mp/stackedgraphs

  • A. Thudt | J. Walny | C. Perin | F. Rajabiyazdi | L. MacDonald | R. Vardeleon | S. Greenberg | S. Carpendale