Visual Analytics Challenges and Trends in the Age of AI: The BigVis Community Perspective

TL;DR

This paper analyzes the BigVis 2024 survey of 32 experts from databases, information visualization, and HCI to map current and future visual analytics challenges in the AI era and compares findings with the 2020 study. It reveals that many pre-AI challenges remain relevant while AI-related issues (e.g., LLM usage, fairness, explanations) have surged to prominence, introducing new priorities for the field. The work identifies top emerging topics—especially human-in-the-loop processing, interactive and human-centered ML, and progressive analytics—and documents first appearances of challenges like high-dimensional/stream data and immersive visualization. Collectively, the study informs research directions and practical priorities for human-data interaction and visual analytics amidst rapid AI advancement.

Abstract

This report provides insights into the challenges, emerging topics, and opportunities related to human-data interaction and visual analytics in the AI era. The BigVis 2024 organizing committee conducted a survey among experts in the field. They invite the Program Committee members and the authors of accepted papers to share their views. Thirty-two scientists from diverse research communities, including Databases, Information Visualization, and Human-Computer Interaction, participated in the study. These scientists, representing both industry and academia, provided valuable insights into the current and future landscape of the field. In this report, we analyze the survey responses and compare them to the findings of a similar study conducted four years ago. The results reveal some interesting insights. First, many of the critical challenges identified in the previous survey remain highly relevant today, despite being unrelated to AI. Meanwhile, the field's landscape has significantly evolved, with most of today's vital challenges not even being mentioned in the earlier survey, underscoring the profound impact of AI-related advancements. By summarizing the perspectives of the research community, this report aims to shed light on the key challenges, emerging trends, and potential research directions in human-data interaction and visual analytics in the AI era.

Figures (3)

• Figure 1: Participants Demographics
• Figure 2: The Importance of the 2020 Challenges Today ["Is this challenge important today?"]
• Figure 3: Emerging Topics: The Percentage of Participants that Voted for Each Topic