Hi!👋 Welcome to my academic page, where I share my journey, projects, and aspirations. I’m currently a fourth-year undergraduate student majoring in Computer Science & Technology at BIT.
My academic journey has been driven by a deep passion for software engineering and web development. Throughout my undergraduate years, I’ve dedicated myself to mastering front-end technologies and delving into the intricate world of HCI & big data visualization.
I am now in the process of applying for a master’s degree in Computer Science or Electrical and Computer Engineering in Canada, aiming to further my expertise and open new horizons in my professional journey.
Extracting data insights and generating visual data stories from tabular data are critical parts of data analysis. However, most existing studies primarily focus on tabular data stored as flat tables, typically without leveraging the relations between cells in the headers of hierarchical tables. When properly used, rich table headers can enable the extraction of many additional data insights. To assist analysts in visual data storytelling, an approach is needed to organize these data insights efficiently. In this work, we propose CoInsight, a system to facilitate visual storytelling for hierarchical tables by connecting insights. CoInsight extracts data insights from hierarchical tables and builds insight relations according to the structure of table headers. It further visualizes related data insights using a nested graph with edge bundling. We evaluate the CoInsight system through a usage scenario and a user experiment. The results demonstrate the utility and usability of CoInsight for converting data insights in hierarchical tables into data stories.
@article{li2024coinsight,title={CoInsight: Visual Storytelling for Hierarchical Tables with Connected Insights},author={Li, Guozheng and Li, Runfei and Feng, Yunshan and Zhang, Yu and Luo, Yuyu and Liu, Chi Harold},year={2024},journal={IEEE Transactions on Visualization and Computer Graphics},booktitle={Proceedings of the IEEE Pacific Visualization Symposium 2024 (PacificVis)},note={Accepted for publication in the PacificVis 2024 Papers (IEEE TVCG Journal Track)},}
