Abstract
Visualization and artificial intelligence (AI) are well-applied approaches to data analysis. On one hand, visualization can facilitate humans in data understanding through intuitive visual representation and interactive exploration. On the other hand, AI is able to learn from data and implement bulky tasks for humans. In complex data analysis scenarios, like epidemic traceability and city planning, humans need to understand large-scale data and make decisions, which requires complementing the strengths of both visualization and AI. Existing studies have introduced AI-assisted visualization as AI4VIS and visualization-assisted AI as VIS4AI. However, how can AI and visualization complement each other and be integrated into data analysis processes are still missing. In this paper, we define three integration levels of visualization and AI. The highest integration level is described as the framework of VIS+AI, which allows AI to learn human intelligence from interactions and communicate with humans through visual interfaces. We also summarize future directions of VIS+AI to inspire related studies.
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This work was supported by the National Natural Science Foundation of China (Grant Nos. 62202244, 62132017, and 62036010).
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Xumeng Wang is a lecturer in the College of Computer Science, Nankai University, China. She earned the PhD in computer science and technology from Zhejiang University, China in 2021. Her research interests include visual analytics and privacy preservation.
Ziliang Wu received the BS degree in computer science from Zhejiang University, China in 2020. He is currently working toward the PhD in the College of Computer Science and Technology, Zhejiang University, China. His research interests include visual analysis powered by AI, visualization recommendation.
Wenqi Huang is the leader of Artificial Intelligence and Intelligent Software Team in R&D Center, Digital Grid Research Institute, China Southern Power Grid, China. She holds BS (2010) and PhD (2015) degrees from the Department of Information Science and Electronic Engineering, Zhejiang University, China. Her research interests span artificial intelligence, data mining and blockchain application technology in the field of power industry.
Yating Wei is a PhD student in the State Key Lab of CAD&CG, Zhejiang University, China. She earned the BS degree in software engineering from Central South University, China in 2017. Her research interests include visual analytics and perceptual consistency.
Zhaosong Huang is with Huawei Cloud, China. He received his PhD in the College of Computer Science and Technology from Zhejiang University, China. He was a joint PhD student at Arizona State University, USA in 2017–2018. His research interests include visualization and visual analysis of urban data.
Mingliang Xu is a professor and director of the School of Computer and Artificial Intelligence, Zhengzhou University, China, and the director of the Engineering Research Center of Ministry of Education on Intelligent Swarm Systems, China. He received his PhD degree from the State Key Lab of CAD&CG from Zhejiang University, China. He was awarded as the National Science Foundation for Excellent Young Scholars. His current research interests include computer graphics, multimedia and artificial intelligence. He has published 100+ papers in ACM/IEEE Transactions and full papers on top-tier conferences, such as CVPR and ACM Multimedia.
Wei Chen is a professor of the State Key Lab of CAD&CG, Zhejiang University, China. His research interests include visualization and visual analysis. He has published more than 70 IEEE/ACM Transactions and IEEE VIS papers. He actively served as guest or associate editors of the ACM Transactions on Intelligent System and Technology, the IEEE Computer Graphics and Applications, and Journal of Visualization.
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Wang, X., Wu, Z., Huang, W. et al. VIS+AI: integrating visualization with artificial intelligence for efficient data analysis. Front. Comput. Sci. 17, 176709 (2023). https://doi.org/10.1007/s11704-023-2691-y
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DOI: https://doi.org/10.1007/s11704-023-2691-y