168  |  Highlights from IEEE VIS'22 with Tamara Munzner

2022-11-21 · Source: Data Stories · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Software Development & Engineering · Depth: Intermediate, extended

Summary

This Data Stories podcast episode, featuring hosts Enrico Bertini and Moritz Stefaner with guest Tamara Munzner, provides highlights from the IEEE VIS'22 conference. Munzner, a professor at the University of British Columbia and a long-time attendee of IEEE VIS since 1991, discusses keynotes, capstones, awards, and notable papers. Keynote speaker Marty Hurst's "Show It or Tell It" emphasized language as co-equal with visualization, while Kerry McGruder's capstone on Galileo's telescope discoveries explored visual thinking in science history. Casely Feasler's keynote, "Data is People," addressed research ethics beyond human subjects, introducing the concept of "ethical debt." The episode also covers the 10-Year Test of Time awards for influential papers, including one on enterprise data analysis and visualization, and Munzner's own paper on design study methodology. Discussions extend to new papers on transforming tabular data, visualization grammars, dashboard design patterns, and performance optimization for large datasets.

Key takeaway

For AI Scientists developing visualization tools or conducting data-driven research, consider the ethical implications of your data early to avoid "ethical debt." Integrate natural language processing and generation methods into your visualization workflows, recognizing text's co-equal role with visual elements. Explore design study methodologies to ensure your research directly addresses real-world problems and user needs, moving beyond purely theoretical contributions.

Key insights

IEEE VIS'22 highlighted the evolving role of language, ethics, and practical application in data visualization research.

Principles

• Language is co-equal with visualization.
• Ethical debt accrues from unaddressed social implications.
• Design studies valorize solving real-world problems.

Method

Design study methodology involves collaborative, iterative development with real users and data, followed by reflection on confirmed or refuted guidelines to advance research.

In practice

• Watch Marty Hurst's keynote on text and visualization.
• Explore the Dashboard Design Patterns website.
• Read Colin Ware's "Information Visualization: Perception for Design".

Topics

• Natural Language Processing
• Data Visualization Ethics
• Design Study Methodology
• Visualization Grammars
• Hierarchical Data Visualization

Best for: AI Scientist, Research Scientist, Data Scientist, Data Analyst

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Editorial summary, takeaway, and curation by AIssential. Original article published by Data Stories.