Understanding Narrative Linearity for Telling Expressive Time-Oriented Stories

Lan, Xingyu; Xu, Xinyue; Cao, Nan

doi:10.1145/3411764.3445344

Cited by 23 publications

(13 citation statements)

References 43 publications

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“…Due to its importance, many theoretical design spaces have been introduced to help clarify the key concepts about visual narratives [31,40,46] and provide fundamental design principles [24,25,44,45,60]. Early studies focused on high-level concepts.…”

Section: Data-driven Storytellingmentioning

confidence: 99%

“…Stolper et al [46] presented four high-level categories of narrative visualization techniques. Recent studies introduce several design spaces that more elaborately provide fundamental design principles from two major aspects: the narrative structures [25,60] and the visual representation methods [24,44,45], while taking communication goals and design tasks into consideration.…”

Section: Data-driven Storytellingmentioning

confidence: 99%

“…All of these stories consist of 5 data facts with diverse fact types. They were designed by following either the time-oriented narrative structure [25] or the parallel structure [42]. 300 fact trigrams were extracted from these stories as our training set.…”

Section: Fact Embeddermentioning

confidence: 99%

“…To facilitate the creation of data stories, during the past decades, theories, techniques, and tools have been extensively studied and developed. For example, a series of design spaces have been proposed from two major aspects: the narrative structures [25,60] and the visual representation methods [18,24,31,40,[44][45][46], while taking communication goals and tasks into consideration. At the same time, to lower the technical barriers, a number of interactive authoring tools that integrate advanced data analysis and visualization functionalities have been developed [8,27,53,55].…”

Section: Introductionmentioning

confidence: 99%

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Erato: Cooperative Data Story Editing via Fact Interpolation

Sun

Cai

Cui

et al. 2022

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. A data story about natural disasters represented in form of a storyline that was authored by a professional data analyst. The data facts in black (a, c, e, f) were created by the analyst as keyframes of the story, while the facts in red (b, d) were generated based on our interpolation algorithm. The algorithm searches through the fact space to find data facts that best fill the content gap between two keyframes. The story first illustrates an overall situation of global natural disasters (a-c) and gradually focuses on the situation in China (d,e). Finally, it reveals that floods have the most pernicious impact on China (f). The corresponding interpolation process is also shown under the data story. The searching path is marked in red and the nodes with yellow borders are the final selected interpolation results.

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Section: Data-driven Storytellingmentioning

confidence: 99%

Section: Data-driven Storytellingmentioning

confidence: 99%

Section: Fact Embeddermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Erato: Cooperative Data Story Editing via Fact Interpolation

Sun

Cai

Cui

et al. 2022

IEEE Trans. Visual. Comput. Graphics

Self Cite

View full text Add to dashboard Cite

show abstract

“…Moreover, based on combining these three levels, 20 timeline design options were identified to match the narrative style. Lan et al [63] identified six narrative sequencing patterns (chronology, trace-back, trailer, recurrence, halfway-back, anchor). The study results showed that non-linear narratives are more likely to increase user engagement and that non-linear narratives make stories more expressive without hindering comprehension.…”

Section: Timeline and Storylinementioning

confidence: 99%

How Does Automation Shape the Process of Narrative Visualization: A Survey on Tools

Chen¹,

Cao²,

Wang³

et al. 2022

Preprint

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In recent years, narrative visualization has gained a lot of attention. Researchers have proposed different design spaces for various narrative visualization types and scenarios to facilitate the creation process. As users' needs grow and automation technologies advance, more and more tools have been designed and developed. In this paper, we surveyed 122 papers and tools to study how automation can progressively engage in the visualization design and narrative process. By investigating the narrative strengths and the drawing efforts of various visualizations, we created a two-dimensional coordinate to map different visualization types. Our resulting taxonomy is organized by the seven types of narrative visualization on the +x-axis of the coordinate and the four automation levels (i.e., design space, authoring tool, AI-supported tool, and AI-generator tool) we identified from the collected work. The taxonomy aims to provide an overview of current research and development in the automation involvement of narrative visualization tools. We discuss key research problems in each category and suggest new opportunities to encourage further research in the related domain.

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Visually Reporting Geographic Data Insights as Integrated Visual and Textual Representations

Beck,

Latif

2023

Volunteered Geographic Information

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Geographic information volunteered by the public is usually also of public interest. However, just publishing the data is not enough to make the data accessible and usable for the public. The raw data might need to be abstracted and interpreted, as well as visually presented to be understandable to non-experts. To address this, we propose interactive visual reporting solutions that leverage natural language and visualizations for geo-related data. We present these reports as interactive documents, but also in other media such as virtual reality environments. First, we have studied the interplay of textual and visual content in such reports. To ease the creation of content, we have developed solutions for authoring interactive documents with a close linking of textual contents and visually presented data. Moreover, we propose automatic report generation approaches that specifically support the exploration of the geo-related data starting from an explanatory summary.

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Understanding Narrative Linearity for Telling Expressive Time-Oriented Stories

Cited by 23 publications

References 43 publications

Erato: Cooperative Data Story Editing via Fact Interpolation

Erato: Cooperative Data Story Editing via Fact Interpolation

How Does Automation Shape the Process of Narrative Visualization: A Survey on Tools

Visually Reporting Geographic Data Insights as Integrated Visual and Textual Representations

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