article

From Visual Exploration to Storytelling and Back Again

Authors:

M. StreitAuthors Info & Claims

Computer Graphics Forum, Volume 35, Issue 3

Pages 491 - 500

Published: 01 June 2016 Publication History

Abstract

The primary goal of visual data exploration tools is to enable the discovery of new insights. To justify and reproduce insights, the discovery process needs to be documented and communicated. A common approach to documenting and presenting findings is to capture visualizations as images or videos. Images, however, are insufficient for telling the story of a visual discovery, as they lack full provenance information and context. Videos are difficult to produce and edit, particularly due to the non-linear nature of the exploratory process. Most importantly, however, neither approach provides the opportunity to return to any point in the exploration in order to review the state of the visualization in detail or to conduct additional analyses. In this paper we present CLUE Capture, Label, Understand, Explain, a model that tightly integrates data exploration and presentation of discoveries. Based on provenance data captured during the exploration process, users can extract key steps, add annotations, and author "Vistories", visual stories based on the history of the exploration. These Vistories can be shared for others to view, but also to retrace and extend the original analysis. We discuss how the CLUE approach can be integrated into visualization tools and provide a prototype implementation. Finally, we demonstrate the general applicability of the model in two usage scenarios: a Gapminder-inspired visualization to explore public health data and an example from molecular biology that illustrates how Vistories could be used in scientific journals.

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Cited By

Li HWang YQu H(2024)Where Are We So Far? Understanding Data Storytelling Tools from the Perspective of Human-AI CollaborationProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642726(1-19)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642726
Zhang YEns BSatriadi KYang YGoodwin S(2023)Embodied Provenance for Immersive SensemakingProceedings of the ACM on Human-Computer Interaction10.1145/36264717:ISS(198-216)Online publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1145/3626471
Li HYing LZhang HWu YQu HWang Y(2023)Notable: On-the-fly Assistant for Data Storytelling in Computational NotebooksProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580965(1-16)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580965
Show More Cited By

Index Terms

From Visual Exploration to Storytelling and Back Again
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Graphical user interfaces

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Published In

cover image Computer Graphics Forum

Computer Graphics Forum Volume 35, Issue 3

June 2016

728 pages

ISSN:0167-7055

EISSN:1467-8659

Issue’s Table of Contents

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The Eurographs Association & John Wiley & Sons, Ltd.

Chichester, United Kingdom

Publication History

Published: 01 June 2016

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Cited By

Li HWang YQu H(2024)Where Are We So Far? Understanding Data Storytelling Tools from the Perspective of Human-AI CollaborationProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642726(1-19)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642726
Zhang YEns BSatriadi KYang YGoodwin S(2023)Embodied Provenance for Immersive SensemakingProceedings of the ACM on Human-Computer Interaction10.1145/36264717:ISS(198-216)Online publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1145/3626471
Li HYing LZhang HWu YQu HWang Y(2023)Notable: On-the-fly Assistant for Data Storytelling in Computational NotebooksProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580965(1-16)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580965
Eckelt KHinterreiter AAdelberger PWalchshofer CDhanoa VHumer CHeckmann MSteinparz CStreit M(2023)Visual Exploration of Relationships and Structure in Low-Dimensional EmbeddingsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.315676029:7(3312-3326)Online publication date: 1-Jul-2023
https://dl.acm.org/doi/10.1109/TVCG.2022.3156760
Stitz HGratzl SPiringer HZichner TStreit M(2019)KnowledgePearls: Provenance-Based Visualization RetrievalIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2018.286502425:1(120-130)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1109/TVCG.2018.2865024
Amabili LKosinka Jvan Meersbergen Mvan Ooijen PRoerdink JSvetachov PYu LJohansson JSadlo FSchreck T(2018)Improving provenance data interaction for visual storytelling in medical imaging data explorationProceedings of the Eurographics/IEEE VGTC Conference on Visualization: Short Papers10.5555/3290776.3290786(43-47)Online publication date: 4-Jun-2018
https://dl.acm.org/doi/10.5555/3290776.3290786
Ceneda DGschwandtner TMay TMiksch SStreit MTominski CTominski Cvon Landesberger T(2018)Guidance or no guidance?Proceedings of the EuroVis Workshop on Visual Analytics10.5555/3290753.3290758(19-23)Online publication date: 4-Jun-2018
https://dl.acm.org/doi/10.5555/3290753.3290758
Wang YZhang HHuang HChen XYin QHou ZZhang DLuo QQu HMandryk RHancock MPerry MCox A(2018)InfoNiceProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3173909(1-12)Online publication date: 21-Apr-2018
https://dl.acm.org/doi/10.1145/3173574.3173909

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