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What Makes a Data-GIF Understandable? (2008.07227v2)

Published 17 Aug 2020 in cs.HC

Abstract: GIFs are enjoying increasing popularity on social media as a format for data-driven storytelling with visualization; simple visual messages are embedded in short animations that usually last less than 15 seconds and are played in automatic repetition. In this paper, we ask the question, "What makes a data-GIF understandable?" While other storytelling formats such as data videos, infographics, or data comics are relatively well studied, we have little knowledge about the design factors and principles for "data-GIFs". To close this gap, we provide results from semi-structured interviews and an online study with a total of 118 participants investigating the impact of design decisions on the understandability of data-GIFs. The study and our consequent analysis are informed by a systematic review and structured design space of 108 data-GIFs that we found online. Our results show the impact of design dimensions from our design space such as animation encoding, context preservation, or repetition on viewers' understanding of the GIF's core message. The paper concludes with a list of suggestions for creating more effective Data-GIFs.

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Authors (6)
  1. Xinhuan Shu (12 papers)
  2. Aoyu Wu (21 papers)
  3. Junxiu Tang (4 papers)
  4. Benjamin Bach (31 papers)
  5. Yingcai Wu (47 papers)
  6. Huamin Qu (141 papers)
Citations (54)

Summary

  • The paper empirically investigates factors impacting the understandability of data-GIFs by analyzing 108 examples through interviews and online studies.
  • Key findings reveal that basic visualization types and temporal animation encoding significantly enhance comprehension within the short data-GIF format.
  • Effective data-GIF design recommendations include leveraging temporal animations, integrating meaningful narrative progress, and judiciously using context preservation.

Understanding Data-GIFs: Design Factors Impacting Comprehension

The paper "What Makes a Data-GIF Understandable?" addresses the emergent and increasingly prevalent format of data-driven storytelling using GIFs. As the digital landscape evolves, traditional media like infographics and data videos have given way to new formats, such as data-GIFs, which present data insights in short, repeatable animations. This empirical paper explores the nuances of data-GIFs, evaluating the factors which contribute to their understandability.

The authors of the paper conducted semi-structured interviews and online studies with participants analyzing 108 data-GIFs sourced from online platforms. This collection informed their understanding of how design decisions influence comprehension. Data-GIFs, which typically last less than 15 seconds, are evaluated for how effectively they communicate their core messages through key design elements. The paper identifies five central design dimensions: visualization types, narrative progress, animation encoding, context preservation, and repetition.

Key Findings and Design Implications

Visualization Types

The paper reveals that data-GIFs often utilize basic visualization types such as maps, line charts, and bar charts. These familiar formats are easier for viewers to interpret within the limited duration of a GIF. Conversely, more complex visualizations, such as scatter plots or area charts, may hinder comprehension due to added cognitive load.

Animation Encoding

A significant portion of data-GIFs animate temporal processes, which viewers intuitively understand, linked to time. However, non-temporal animations like setup or narrative steps can confuse audiences, especially if they mimic temporal behaviors without conveying time-based data. The paper suggests encoding animation to visually signal its relation to data, ensuring clarity in communication.

Context Preservation

Maintaining visual context through techniques like trails or baselines enhances understanding by aligning current and previous data points. Yet, excessive complexity in preserving context may distract viewers or obscure the core message. The paper indicates a balance is needed to utilize context effectively without introducing clutter.

Narrative Progress

Narrative progress within a GIF provides a way for viewers to understand the sequence or development of data. However, its implementation should complement the data visualization, aiding rather than distracting viewers.

Repetition

Repetition techniques impact viewer engagement and comprehension. A pause at the end of a GIF can allow viewers to reflect and better interpret its content. While straightforward loops are preferred for maintaining focus, distinguishing repeated elements and emphasizing conclusions can bolster understanding, especially when data is dense or complex.

Future Directions in Data Storytelling

The paper concludes by presenting design suggestions for effective data-GIF creation: leveraging temporal animations, integrating meaningful narrative progress, and utilizing context preservation judiciously. While data-GIFs share characteristics with both static images and videos, they uniquely facilitate quick, repeated viewing experiences conducive to capturing audience attention in fast-paced digital environments.

Looking ahead, the paper highlights the need for further exploration of engagement metrics, the role of complexity, and opportunities in authoring tools for data-GIFs. The paper sets the groundwork for continued research into optimizing data communication formats, ensuring they are both comprehensible and impactful.

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