Practitioners' Perspectives on Designing Data Visualizations for the General Public

Paper Title

Practitioners' Perspectives on Designing Data Visualizations for the General Public

Publication Info

• Topic area: Design and evaluation of public-facing data visualizations in journalistic contexts.
• Keywords: Data visualization, public communication, journalism, audience-centered design, social media, evaluation, storytelling, HCI, platform adaptation, simplification.

Background and Problem

• Problem / challenge: Existing research provides limited insight into how practitioners design data visualizations for broad, undefined audiences across various media channels, and how they evaluate their effectiveness in practice.
• Significance: Public-facing visualizations are critical for communicating complex societal issues (e.g., climate change, COVID-19) to diverse audiences, influencing public understanding and discourse.
• Motivation and related work: Prior studies have explored visualization workflows and principles but often focus on non-journalistic settings or specific domains. There is a gap in understanding how practitioners in journalism conceptualize broad audiences, adapt designs for different platforms, and evaluate their work under real-world constraints.

Solution

• Proposed approach: The study investigates how practitioners design and evaluate public-facing data visualizations through semi-structured interviews with 21 professionals in journalistic and related contexts.
• Novelty:
  1. Provides a qualitative account of how practitioners conceptualize and design for broad, heterogeneous audiences.
  2. Explores cross-channel design strategies and challenges in journalistic visualization work.
  3. Examines informal evaluation practices and identifies gaps in systematic feedback mechanisms.
  4. Proposes design implications for tools that support audience-aware, platform-adaptive, and rhetoric-aware workflows.
• Procedure and key techniques:
  • Conducted semi-structured interviews with 21 practitioners from diverse professional backgrounds.
  • Analyzed transcripts using thematic analysis to identify recurring practices, challenges, and strategies.
  • Structured findings around four domains: visibility of data visualization, audience notions, design strategies, and evaluation practices.

Results

• Concrete findings:
  • Practitioners design for broad, vaguely defined audiences, often defaulting to "the general public."
  • Four main design aims: capturing attention, supporting comprehension, fostering credibility, and fostering connection.
  • Simplification, storytelling, and platform-specific adaptations are key strategies.
  • Formal user testing is rare; evaluation relies on peer feedback and social media metrics.
• Advantage over baselines:
  • Highlights real-world practices and challenges in journalistic visualization, complementing prior research focused on theoretical principles or domain-specific workflows.
  • Identifies practical gaps in tool support for audience-aware and multi-platform design.
• Experiments / evaluation:
  • Semi-structured interviews with 21 practitioners from 10 countries, covering diverse roles and media channels.
  • Thematic analysis identified 12 themes across four analytic domains.
• Limitations and future work:
  • Limited cultural diversity in the sample, with a focus on German-speaking regions.
  • Findings are exploratory and based on self-reported practices, which may not fully align with actual workflows.
  • Future work could explore minimal audience definitions, adaptive design tools, and lightweight evaluation methods.

Summary

This study investigates how practitioners design and evaluate public-facing data visualizations for broad, undefined audiences in journalistic contexts. Through interviews with 21 professionals, the authors identify four main design aims—attention, comprehension, credibility, and connection—and highlight strategies such as simplification, storytelling, and platform-specific adaptations. Formal user testing is rare, with evaluation relying on peer feedback and social media metrics. The study proposes three implications for tool design: content-adaptive multi-format authoring, message-first rhetoric-aware workflows, and lightweight in-tool evaluation methods. These findings provide actionable insights for bridging the gap between academic visualization research and the practical realities of public data communication.