Tracing Tuples Across Dimensions

A Comparison of Scatterplots and Parallel Coordinate Plots

Xiaole Kuang (Master student, NUS)

Haimo Zhang (PhD student, NUS)

Shengdong (Shen) Zhao (Faculty member, NUS)

Michael J. McGuffin

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(Faculty member, École de technologie supérieure)

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The Last Talk of The Last Session of

The Last Day!

Welcome to

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of

Vienna

Singapore

9697 km

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Vignette (CHI ‘12)SandCanvas (CHI ‘11)MOGCLASS (CHI ‘11)Magic Cards (CHI ‘09)

earPod (CHI ‘07)Zone & Polygon Menu (CHI ‘06)

Elastic Hierarchy (InfoVis ‘05)

Simple Marking Menu (UIST ‘04)

Systems, Tools, Interaction Techniques

Visualization Techniques for Multi-Variate Data

Scatter Plot (SCP)

Parallel Coordinate Plot

(PCP)

Scatter Plot Matrix

(SPLOM)

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Why PCP vs. SCP?Both techniques are popular!Yet, we know very little about their comparative advantages.

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Viau et al., TVGC10

Yuan et al., TVGC09

Claessen & van Wijk, TVGC11

We need more systematic evaluations between PCP & SCP!

Basics of Evaluation Research question• What’s the comparative advantages

between PCP & SCP for certain tasks?

Task Independent variablesDependent variables

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Basics of Evaluation Research question• What’s the comparative advantages

between PCP & SCP for certain tasks?

Task Independent variablesDependent variables

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Basic Analytical Tasks

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serves as a subtask for many other tasks

Amar et al.: Low-level components of analytic activity in information visualization. InfoVis05, 111–117.

(Holten & van Wijk, EuroVis10)

(Li et al., InfoVis10)

PCP is inferior than SCP

Value Retrieval TaskDefinition: • Given the numerical value of one attribute

of a data tuple, find the numerical value of another attribute of the same data tuple.

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Multi-Variate Data Tuple (X1, X2, X3, …. , Xn)

a ?

Basics of Evaluation Research question• What’s the comparative advantages

between PCP & SCP for certain tasks?

Task Independent variablesDependent variables

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Independent Variables

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Technique

Parallel Coordinate Plot (PCP)

Scatter Plot (SCP)

X2

X1

X3

X2

X4

X3

X1

X2

X3

X2

X4

X2

X 2X 1

X 2X 3

X 4X 3

SCP-rotated (Qu et al., TVCG07)

SCP-common (SPLOM)

SCP-staircase (Viau et al., TVCG10)

Independent Variable – 4 Technique

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PCP

SCP-common(i.e., SPLOM)

SCP-rotated(i.e., Qu et al., TVCG07)

SCP-staircase(i.e., Viau et al., TVCG10)

Additional Independent Variables

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X2

X1

X3

X2

X4

X3

Number of Dimensions

X2

X1

X3

X2

X4

X3

X5

X4

Data Density

X2

X1

X3

X2

X4

X3

Independent Variables• Technique• Dimension• Density

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Dependent Variables• Completion time• Error distance

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Experiment Demo

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Experiment 1 Design 12 participants

× 4 visualization techniques (PCP, SCP-common, SCP-rotate, SCP-standard)

× 3 levels of data dimension (2D, 4D, 6D)

× 3 levels of data density (10 tuples, 20 tuples, 30 tuples)

× 3 repetitions of trials

= 1296 trials in total.

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Secon

ds

SCP-rotate

SCP-common SCP-staircase

PCP

Overall Results

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Best Good

Poor

Completion Time Error Distance

Err

or

Dis

tan

ce

SCP-rotate

SCP-common SCP-staircase

PCP

Poor

Good

Poorer

1st Take-away Lesson

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PCP

SCP-common(i.e., SPLOM)

SCP-rotated(i.e., Qu et al., TVCG07)

SCP-staircase(i.e., Viau et al., TVCG10)

PCP vs. SCP-common

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PCP vs. SCP-common

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Density

Performance Difference

PCP vs. SCP-common

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Density

Performance Switch Order

Important Observation

There seems to be a

Density & Number of Dimension Trade-off

between PCP & SCP-common!

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Experiment 2× 18 participants

× 2 techniques (PCP, SCP-common)

× 3 dimensions (4D, 6D, 8D) [2D, 4D, 6D in Exp. 1]

× 3 densities (20 tuples, 30 tuples, 40 tuples) [10, 20, 30 in Exp. 1]× 5 trials for each combination

= 1620 trials in total.25

Results – Completion Time

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Overall result for Exp. 2

SCP-common (15.41s) PCP (18.23s)

Result in Exp. 1

SCP-common (12.02s) PCP (8.99s)

faster

faster

Trade-off between number of dimensions & data density

Dimension Density

Results – Error Distance

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Trade-off between number of dimensions & data density

Dimension Density

Take-away LessonsThe value retrieval performance of PCP increases depending on dimensionality.The performance of SCP-common seems independent of dimensionality.

Increasing density affects the performance of PCP more than it affects SCP-common.

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Dimension

Density

Let’s Recap the Take Away-Messages and Ask

Why1) Both SCP-rotate and SCP-staircase are inferior for value retrieval task

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Let’s Recap the Take Away Messages

2) Performance trade-off between PCP & SCP-common for both dimensionalities and data density.• PCP increases depending

on dimensionality. • SCP-common

performance seems to be independent.

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Let’s Recap the Take Away Messages

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10 tuples

40 tuples

2) Performance trade-off between PCP & SCP-common for both dimensionalities and data density.• PCP increases depending

on dimensionality. • SCP-common

performance seems to be independent.

• Increasing density affects the performance of PCP more than it affects SCP-common.

Conclusion and Future Work

Our study helps to understand the comparative advantages between PCP & SCP

However, this is only a starting point,

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The Grand VisionIdeally, this problem can be solved by …

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InfoVisevaluation

package

Results/Recommendations

AcknowledgmentThis research is supported by:

The National University of Singapore Academic Research Fund R-252-000-375-133

and by:

The Singapore National Research Foundation under its International Research Centre @ Singapore Funding Initiative and administered by the IDM Programme Office.

Q & A

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Elastic Hierarchy (InfoVis ‘05)

Tracing Tuples Across Dimensions (EuroVis ‘12)

End

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