O documento descreve o sistema Visualization Tree, que utiliza uma abordagem baseada em árvore para explorar múltiplas técnicas de visualização ligadas e reduzir sobrecarga cognitiva. O sistema permite a composição flexível de visualizações, interação para criar árvores de classificação e recursos de sumarização como estatísticas e relevância de pontos de dados.

1. The 5th International Symposium on Smart Graphics
(SG-2005) - Frauenwoerth Cloister, Germany, August 22-24, 2005
Visualization TTrreeee,, mmuullttiippllee
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Rodrigues Jr., José Fernando
Traina, Agma J. M.
Traina Jr., Caetano
University of São Paulo
Computer Science Department
ICMC-USP
Brazil

2. (SG-05)
2/30
• Introduction
• Developed System
• Interaction Systematization
• Summarization Features
• Conclusions and Ending
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3. (SG-05)
¨ Techniques used to generate scenes whose
graphical attributes rely on the data values
Scientific Visualization
3/30
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Visualization
Information Visualization
(InfoVis)
¨Information Visualization (Infovis), manages
to develop techniques for the analysis of data
sets that do not have an intrinsic graphical
nature

4. (SG-05)
¨ Increasing volume of data that cannot be well
utilized to produce useful knowledge
¨ Raw visualization techniques are limited in the
task of data analysis, while datasets are
unlimited both in size and complexity
There is a need for visualization
mechanisms that reduce the
drawback of massive datasets.
¨ The efficient analysis of multivariate data can
provide assistance in decision making
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MM

5. (SG-05)
¨ Due to overlap of graphical items, some regions
of the visualization seam like blots in the display
¨ Massively populated datasets tend to result in a
visualization scene with an unacceptable level of
clutter
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Overlap of graphical items
Visual clutter

6. (SG-05)
6/30
• Introduction
• Developed System
• Interaction Systematization
• Summarization Features
• Conclusions and Ending
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7. (SG-05)
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¨ Visualization Tree
DD
– Data analysis  multiple visualization techniques
– Graphical overlap  Visual pipeline
– Cognitive flow  Workspaces refinement and
composition
The Visualization Tree system is a
– systematic effort to enhance the
Visual clutter InfoVis  Tree practice scheme
by utilizing
– Enhance integrated exploration presentation,  New interaction interaction
systematization
based and on the summarization tree metaphor
mechanisms.
– Overpopulated data sets  Frequency plot
– Data summarization  Statistics presentation
–

8. (SG-05)
8/30
• Introduction
• Developed System
• Interaction Systematization
• Summarization Features
• Conclusions and Ending
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Developed System

9. (SG-05)
¨Multiple visualization techniques at each
workspace permits to explore each technique’s
advantages in order to aid the analysis process
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MM
Scatter Plots
Parallel
Coordinates
Star
Coordinates
Table Lens

10. (SG-05)
¨ The visual pipeline allows to extend one
workspace’s visualization to multiple workspaces
¨ It naturally diminishes graphical items overlap by
extending the boundaries in derived workspaces
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Via successive pipelines, it is possible
to grasp details until only one item
populates its own workspace.

11. (SG-05)
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¨The tree scheme allows to build multiple
views in a decision-tree style
Cars
European
Japanese
American
4 cylinders
3 cyliners
1976 - 1982
1970 - 1976

12. (SG-05)
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¨The use of multiple views is a known
strategy that can help to diminish user
cognitive overhead:
– single views create cognitive overhead by
requiring In other simultaneously words, the tree comprehension scheme can
of
diverse help data
to bypass the drawbacks of
– easier visual to accomplish clutter presentation.
than single view
memory-based comparison
– “divide and conquer,” aiding memory by
reducing the amount of data they need to
consider at the same time

13. (SG-05)
The composition of workspaces
addresses these issues in an easy-to-use
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¨ Besides refining the views, it may be
interesting to merge views for extra
analytical possibilities:
– when two or more views have similar,
correlated or worthy-comparing semantics
interaction.
– for easy comparison, it may be worthy to put
together branches of the tree in side-by-side,
rather than node-like, positioning
Cars
European
Japanese
American
4 cylinders
3 cyliners
1976 - 1982
1970 - 1975
(European 4 cylinder moels) OR
(Older American models)

14. (SG-05)
By promoting multiple views
exploration, the systems allows
scalability and flexibility.
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¨ The developed system proposes a new interaction
systematization to explore multiple linked
workspaces
¨ The tree structure keeps track of the decisions made
by the analyst
¨ Interaction tasks can be performed either in each
node or in the whole tree
¨ The system interaction promotes the creation of
classification trees that help to interpret the
visualization in a partitioned manner

15. (SG-05)
15/30
• Introduction
• Developed System
• Interaction Systematization
• Summarization Features
• Conclusions and Ending
uuOO
Developed System

16. (SG-05)
cues can transform the cognition task of
view registration into a faster perception
16/30
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¨ A method that
combines selective
filtering with
automatic frequency
calculus within a
given selection
Dynamic visual auditing
inference task.
¨ The frequency is
visually presented
through the opacity
of the graphical
items

17. (SG-05)
The use of statistics can characterize
an entire visual workspace
diminishing cognitive load.
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SS
¨ To summarize the
data, basic statistics
are presented over
the visualizations
¨ Average (green),
standard deviation
(yellow), median
(cyan) and mode
values (magenta)

18. (SG-05)
¨The data is presented according to its
relevance to a user’s defined set of
interesting points
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X1
X1 = RP1 + MRD
Relevance = 0
X0
X0 = RP0
Relevance = 1
X2
X3
Null RP2  Not
Considered
Dist = 1
Relevance = - 1
The relevance point is over
the attribute value
The distance is equal the
Maximum relevance
distance The distance is the
Relevance = 1 + 0 + (-1) = maximum possible
0/3 = 0
RR
The Relevance Plot can be used to
determine speculative queries in sets where
categorical selections are not efficient.

19. (SG-05)
19/30
• Introduction
• Developed System
• Interaction Systematization
• Summarization Features
• Conclusions and Ending
uuOO
Developed System

20. (SG-05)
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¨ The Visualization Tree systematization can help
to diminish InfoVis techniques limitations
¨ The interaction, exploration and summarization
functionalities, together, can be considered a
step further in multivariate visual analysis
¨ The future of InfoVis do not rely on
revolutionary new techniques but on integrated
systematizations presenting interaction and
summarization capabilities

21. (SG-05)
¨All this information did not fit in the paper,
so the tool (MSWindows) can be
downloaded at
http://www.gbdi.icmc.usp.br/~junio/vistree
or at
http://vistree.got.to (alias)
¨We have validated most of the system’s
features based on literature knowledge.
However…
¨To do: perform a systematic evaluation of
the tool usability
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