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From Visual Exploration to Storytelling and Back Again.

S Gratzl1, A Lex2, N Gehlenborg3

  • 1Johannes Kepler University Linz, Austria.

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Summary
This summary is machine-generated.

This study introduces CLUE (Capture, Label, Understand, Explain), a novel model for documenting visual data exploration. CLUE enables researchers to create shareable "Vistories" from exploration history, facilitating reproducible insights.

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Area of Science:

  • Data Visualization
  • Scientific Communication
  • Human-Computer Interaction

Background:

  • Documenting visual data exploration is crucial for insight reproducibility.
  • Current methods like images and videos lack provenance and interactivity.
  • Existing approaches fail to capture the full context and history of discovery.

Purpose of the Study:

  • To present CLUE (Capture, Label, Understand, Explain), a model integrating data exploration with discovery presentation.
  • To enable users to document and share their visual data exploration process.
  • To facilitate the review, reproduction, and extension of data-driven insights.

Main Methods:

  • CLUE captures provenance data during visual data exploration.
  • Users can extract key exploration steps, add annotations, and create "Vistories".
  • Vistories are visual stories based on the exploration history, allowing for review and extension.

Main Results:

  • A prototype implementation of the CLUE model is provided.
  • The model demonstrates applicability in public health data exploration and molecular biology.
  • Vistories can be shared for viewing, retracing, and extending analyses.

Conclusions:

  • CLUE offers a robust solution for documenting and communicating visual data discoveries.
  • The Vistories approach enhances the reproducibility and collaborative potential of data exploration.
  • Integrating CLUE into visualization tools can significantly improve scientific communication and insight validation.