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Supporting Story Synthesis: Bridging the Gap between Visual - - PowerPoint PPT Presentation

Feb 09, 2024 91 likes •568 views

Supporting Story Synthesis: Bridging the Gap between Visual Analytics and Storytelling Siming Chen, Jie Li, Gennady Andrienko, Natalia Andrienko, Yun Wang, Phong H. Nguyen, and Cagatay Turkay (2018) 1 Background Research Problem Related

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Supporting Story Synthesis: Bridging the Gap between Visual Analytics and Storytelling

Siming Chen, Jie Li, Gennady Andrienko, Natalia Andrienko, Yun Wang, Phong H. Nguyen, and Cagatay Turkay

(2018)

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Background
 Research Problem Related Works Bridging the Gap
 Proposed Solution Thoughts

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Background
 Research Problem Related Works Bridging the Gap
 Proposed Solution Thoughts

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Visual Analytics

4 Figure 6. Visual analytics interface of social media, including (a) topic projection view, (b) topic comparison view, (c) user/ location distribution view, (d) temporal view, (e) story slice generation parameters, and (f) raw data table.

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Visual Analytics

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“Fancy visuals, cool interactions, but what does this mean?”

Figure 6. Visual analytics interface of social media, including (a) topic projection view, (b) topic comparison view, (c) user/ location distribution view, (d) temporal view, (e) story slice generation parameters, and (f) raw data table.

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Storytelling

6 Figure 8. Layout methods to organize story slices according to different perspectives: (a) time cycles, (b) locations, (c) users, and (d) keywords.

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Storytelling

7 Figure 8. Layout methods to organize story slices according to different perspectives: (a) time cycles, (b) locations, (c) users, and (d) keywords.

Presenting results in an accessible way!

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Storytelling

  • Helps non-experts connect the dots
  • Effectively communicates insights
  • Provides meaning and context to data

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Background
 Research Problem Related Works Bridging the Gap
 Proposed Solution Thoughts

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The Gap

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The Gap

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The Gap

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The Gap

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How do we move from analysis to storytelling?

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The Gap

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How do we move from analysis to storytelling?

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The Gap

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How do we move from analysis to storytelling? Multiple approaches but what we need is a data analysis to storytelling pipeline

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Background
 Research Problem Related Works Bridging the Gap
 Proposed Solution Thoughts

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Past Work

  • Need for organizing story contents
  • Existing works compose stories with annotated screen

shots of analytic displays

  • Provenance systems rely on completed analysis

bookmarks

  • Other systems rely on completed visualizations

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Past Work

  • Need for organizing story contents
  • Existing works compose stories with annotated screen

shots of analytic displays

  • Provenance systems rely on completed analysis

bookmarks

  • Other systems rely on completed visualizations

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Inherits visual complexity of analytic displays

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Inherits visual complexity of analytic displays

Past Work

  • Need for organizing story contents
  • Existing works compose stories with annotated screen

shots of analytic displays

  • Provenance systems rely on completed analysis

bookmarks

  • Other systems rely on completed visualizations

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No current systems are integrated into the analysis workflow!

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Background
 Research Problem Related Works Bridging the Gap
 Proposed Solution Thoughts

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Bridging the Gap

21 Figure 6. Proposed framework for bridging the gap.

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Bridging the Gap

22 Figure 6. Proposed framework for bridging the gap.

Extend analysis and storytelling workflows toward each other

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Bridging the Gap

23 Figure 6. Proposed framework for bridging the gap.

Story slice generation Extend analysis and storytelling workflows toward each other

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Bridging the Gap

24 Figure 6. Proposed framework for bridging the gap.

Content preparation Story slice generation Extend analysis and storytelling workflows toward each other

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Story Slices

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  • Structured representations of findings during the course
  • f analysis
  • Define what facets (information) to capture
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Story Slices

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VAST Challenge, analyze the circumstances of an epidemic

  • utbreak via microblogs
  • Structured representations of findings during the course
  • f analysis
  • Define what facets (information) to capture
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Story Slices

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VAST Challenge, analyze the circumstances of an epidemic

  • utbreak via microblogs

Epidemic and city were fictitious don’t worry

  • Structured representations of findings during the course
  • f analysis
  • Define what facets (information) to capture
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Analytic Phase

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Produce story slices during Analyze tasks

Figure 5. Visual analytics phase. After topic modelling, analysts explore the collection of messages from four perspectives and extract story slices.

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Story Slices

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… …

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Story Slices

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… … Facets help guide visual arrangements in story contents

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Story Slices

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… Facets help guide visual arrangements in story contents … Story slices are the input to the story synthesis phase

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Facet Types

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  • Discrete categories with no relationships
  • Discrete entities with domain-specific relationships
  • Linearly ordered elements
  • Linearly ordered elements with distances
  • Time
  • 1D/2D/3D space
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Facet Types

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  • Discrete categories with no relationships
  • Discrete entities with domain-specific relationships
  • Linearly ordered elements
  • Linearly ordered elements with distances
  • Time
  • 1D/2D/3D space

Facets specify possible arrangements and aggregations

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Facet Types

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  • Discrete categories with no relationships
  • Discrete entities with domain-specific relationships
  • Linearly ordered elements
  • Linearly ordered elements with distances
  • Time
  • 1D/2D/3D space

Facets specify possible arrangements and aggregations These are very similar to the Abstract Data Types in VAD…

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Background
 Research Problem Related Works Bridging the Gap
 Proposed Solution Thoughts

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Story Synthesis

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Story synthesis creates story contents from story slices by…

  • Aggregating and summarizing story slices according to

facets/measurements

  • Embedding details into views/layouts
  • Arranging story slices onto layouts according to facets/

relationships

  • Showing facets by priority and from multiple perspectives
  • Annotating
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Story Synthesis

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Story synthesis creates story contents from story slices by…

  • Aggregating and summarizing story slices according to

facets/measurements

  • Embedding details into views/layouts
  • Arranging story slices onto layouts according to facets/

relationships

  • Showing facets by priority and from multiple perspectives
  • Annotating

Story synthesis does not include the design

  • f the final story!
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Story Synthesis

38 Figure 11. Output from story synthesis phase performed by sociology researcher.

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Story Synthesis

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story slice keys

Figure 11. Output from story synthesis phase performed by sociology researcher.

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Story Synthesis

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story slice attributes story slice keys

Figure 11. Output from story synthesis phase performed by sociology researcher.

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Story Synthesis

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Channels are used to convey facet information

Figure 11. Output from story synthesis phase performed by sociology researcher.

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New Framework

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  • 1. Define types and structures of story slices - What facets
  • r patterns may be used from the data analysis phase?
  • 2. Design representations of story slices - What data

structure will be used to contain slice information? How will slices be visualized in the synthesis workspace?

  • 3. Define story synthesis support functions.
  • 4. Design the visual analytics system, including support for

discovery of potential story slices.

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New Framework

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  • 1. Define types and structures of story slices - What facets
  • r patterns may be used from the data analysis phase?
  • 2. Design representations of story slices - What data

structure will be used to contain slice information? How will slices be visualized in the synthesis workspace?

  • 3. Define story synthesis support functions.
  • 4. Design the visual analytics system, including support for

discovery of potential story slices. This framework can be used in designing visual analytics systems that provide support for story synthesis.

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Background
 Research Problem Related Works Bridging the Gap
 Proposed Solution Thoughts

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Good

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☺Need for framework is well backed by current research ☺Story slices help reason about abstract data more ☺Story slices capture model of analysis concept generation ☺Evaluated by two sociology experts (positive feedback)

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Bad

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☹ Paper didn’t do a great job proving generality of framework ☹ Majority of examples used online text message data ☹ Paper structure could be improved to help understanding ☹ Both experts only interviewed for 1.5h using similar data ☹ Is this framework better suited for messaging data?