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Visualisasi Data

Program Studi Informatika

Fakultas Sains dan Matematika

Universitas Diponegoro

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MIK1624713

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Agenda

  • What's Vis, and Why Do It?
  • Analysis: Nested Model
  • Data Abstraction
  • Task Abstraction
  • Marks & Channels
  • Arrange Tables
  • Rules of Thumb

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Visualization Analysis & Design

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Analysis: Nested Model (Ch 4)

@tamaramunzner

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Analysis framework: Four levels, three questions

  • domain situation
    • who are the target users?

4

domain

[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Analysis framework: Four levels, three questions

  • domain situation
    • who are the target users?
  • abstraction
    • translate from specifics of domain to vocabulary of vis
      • what is shown? data abstraction
      • why is the user looking at it? task abstraction

5

abstraction

domain

[A Multi-Level Typology of Abstract Visualization Tasks. Brehmer and Munzner. IEEE TVCG 19(12):2376-2385, 2013 (Proc. InfoVis 2013). ]

[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Analysis framework: Four levels, three questions

  • domain situation
    • who are the target users?
  • abstraction
    • translate from specifics of domain to vocabulary of vis
      • what is shown? data abstraction
      • why is the user looking at it? task abstraction
  • idiom
    • how is it shown?
      • visual encoding idiom: how to draw
      • interaction idiom: how to manipulate

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idiom

abstraction

domain

[A Multi-Level Typology of Abstract Visualization Tasks. Brehmer and Munzner. IEEE TVCG 19(12):2376-2385, 2013 (Proc. InfoVis 2013). ]

[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Analysis framework: Four levels, three questions

  • domain situation
    • who are the target users?
  • abstraction
    • translate from specifics of domain to vocabulary of vis
      • what is shown? data abstraction
      • why is the user looking at it? task abstraction
  • idiom
    • how is it shown?
      • visual encoding idiom: how to draw
      • interaction idiom: how to manipulate
  • algorithm
    • efficient computation

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algorithm

idiom

abstraction

domain

[A Multi-Level Typology of Abstract Visualization Tasks. Brehmer and Munzner. IEEE TVCG 19(12):2376-2385, 2013 (Proc. InfoVis 2013). ]

[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Nested model

  • downstream: cascading effects

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[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Nested model

  • downstream: cascading effects
  • upstream: iterative refinement

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[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Why is validation difficult?

  • different ways to get it wrong at each level

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[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Why is validation difficult?

  • solution: use methods from different fields at each level

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[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Why is validation difficult?

  • solution: use methods from different fields at each level

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computer science

technique-driven work

[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Why is validation difficult?

  • solution: use methods from different fields at each level

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computer science

design

cognitive psychology

[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

technique-driven work

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Why is validation difficult?

  • solution: use methods from different fields at each level

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computer science

design

cognitive psychology

anthropology/�ethnography

anthropology/�ethnography

technique-driven work

[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Why is validation difficult?

  • solution: use methods from different fields at each level

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computer science

design

cognitive psychology

anthropology/�ethnography

anthropology/�ethnography

problem-driven work (design study)

technique-driven work

[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Avoid mismatches

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computational benchmarks do not confirm idiom design

[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Avoid mismatches

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computational benchmarks do not confirm idiom design

lab studies do not confirm task abstraction

[A Nested Model of Visualization Design and Validation. Munzner. IEEE TVCG 15(6):921-928, 2009 (Proc. InfoVis 2009). ]

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Visualization Analysis & Design

​

Analysis: Nested Model (Ch 4) II

@tamaramunzner

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Analysis examples: Single paper includes only subset of methods

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Analysis examples: Single paper includes only subset of methods

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MatrixExplorer. Henry and Fekete. InfoVis 2006.

measure system time/memory

qualitative result image analysis

observe and interview target users

justify encoding/interaction design

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Analysis examples: Single paper includes only subset of methods

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MatrixExplorer. Henry and Fekete. InfoVis 2006.

LiveRAC. McLachlan, Munzner, Koutsofios, and North. CHI 2008.

measure system time/memory

qualitative result image analysis

observe and interview target users

justify encoding/interaction design

qualitative result image analysis

observe and interview target users

justify encoding/interaction design

field study, document deployed usage

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Analysis examples: Single paper includes only subset of methods

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qualitative/quantitative image analysis

MatrixExplorer. Henry and Fekete. InfoVis 2006.

An energy model for visual graph clustering. (LinLog)�Noack. Graph Drawing 2003

LiveRAC. McLachlan, Munzner, Koutsofios, and North. CHI 2008.

measure system time/memory

qualitative result image analysis

observe and interview target users

justify encoding/interaction design

qualitative result image analysis

observe and interview target users

justify encoding/interaction design

field study, document deployed usage

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Analysis examples: Single paper includes only subset of methods

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qualitative/quantitative image analysis

lab study, measure time/errors for operation

MatrixExplorer. Henry and Fekete. InfoVis 2006.

An energy model for visual graph clustering. (LinLog)�Noack. Graph Drawing 2003

LiveRAC. McLachlan, Munzner, Koutsofios, and North. CHI 2008.

Effectiveness of animation in trend visualization.�Robertson et al. InfoVis 2008.

measure system time/memory

qualitative result image analysis

observe and interview target users

justify encoding/interaction design

qualitative result image analysis

observe and interview target users

justify encoding/interaction design

field study, document deployed usage

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Analysis examples: Single paper includes only subset of methods

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justify encoding/interaction design

​

qualitative result image analysis

test on target users, get utility anecdotes

qualitative/quantitative image analysis

lab study, measure time/errors for operation

MatrixExplorer. Henry and Fekete. InfoVis 2006.

An energy model for visual graph clustering. (LinLog)�Noack. Graph Drawing 2003

LiveRAC. McLachlan, Munzner, Koutsofios, and North. CHI 2008.

Effectiveness of animation in trend visualization.�Robertson et al. InfoVis 2008.

measure system time/memory

qualitative result image analysis

observe and interview target users

justify encoding/interaction design

qualitative result image analysis

observe and interview target users

justify encoding/interaction design

field study, document deployed usage

Interactive visualization of genealogical graphs. �McGuffin and Balakrishnan. InfoVis 2005.

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Analysis examples: Single paper includes only subset of methods

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justify encoding/interaction design

​

qualitative result image analysis

test on target users, get utility anecdotes

justify encoding/interaction design

measure system time/memory

qualitative result image analysis

computational complexity analysis

qualitative/quantitative image analysis

lab study, measure time/errors for operation

MatrixExplorer. Henry and Fekete. InfoVis 2006.

An energy model for visual graph clustering. (LinLog)�Noack. Graph Drawing 2003

Flow map layout. Phan et al. InfoVis 2005.

LiveRAC. McLachlan, Munzner, Koutsofios, and North. CHI 2008.

Effectiveness of animation in trend visualization.�Robertson et al. InfoVis 2008.

measure system time/memory

qualitative result image analysis

observe and interview target users

justify encoding/interaction design

qualitative result image analysis

observe and interview target users

justify encoding/interaction design

field study, document deployed usage

Interactive visualization of genealogical graphs. �McGuffin and Balakrishnan. InfoVis 2005.

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