Visual Analytics Challenges and Trends in the Age of AI: The BigVis Community Perspective
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866910922973380608 |
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| author | Bikakis, Nikos Chrysanthis, Panos K. Li, Guoliang Papastefanatos, George Yu, Lingyun |
| author_facet | Bikakis, Nikos Chrysanthis, Panos K. Li, Guoliang Papastefanatos, George Yu, Lingyun |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2504_21500 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Visual Analytics Challenges and Trends in the Age of AI: The BigVis Community Perspective Bikakis, Nikos Chrysanthis, Panos K. Li, Guoliang Papastefanatos, George Yu, Lingyun Databases Human-Computer Interaction 97R50, 68P05, 68P15 E.1; H.2.8; H.5.2; H.4 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. |
| title | Visual Analytics Challenges and Trends in the Age of AI: The BigVis Community Perspective |
| topic | Databases Human-Computer Interaction 97R50, 68P05, 68P15 E.1; H.2.8; H.5.2; H.4 |
| url | https://arxiv.org/abs/2504.21500 |