Visual Analytics Challenges and Trends in the Age of AI: The BigVis Community Perspective
April 30, 2025 ยท Declared Dead ยท ๐ SIGMOD record
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Nikos Bikakis, Panos K. Chrysanthis, Guoliang Li, George Papastefanatos, Lingyun Yu
arXiv ID
2504.21500
Category
cs.DB: Databases
Cross-listed
cs.HC
Citations
2
Venue
SIGMOD record
Last Checked
3 months ago
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.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Databases
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
The Case for Learned Index Structures
R.I.P.
๐ป
Ghosted
Untangling Blockchain: A Data Processing View of Blockchain Systems
R.I.P.
๐ป
Ghosted
Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccades
R.I.P.
๐ป
Ghosted
BLOCKBENCH: A Framework for Analyzing Private Blockchains
R.I.P.
๐ป
Ghosted
Data Synthesis based on Generative Adversarial Networks
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted