Personal Reflection through Adaptive Data Comics: A Story on Reading Data
Abstract
Data comics are an appealing medium for visualizing personal taste and interests. As a design study, this paper presents an interactive data comic that analyzes personal reading data. It adapts both content and structure to users’ data and selections. Combining elements of data visualization, sequential storytelling, and user interactivity, the comic transforms the data into a relatable narrative organized in different chapters. Accompanying the visualizations, data analysis guidance and book recommendations are generated specific to the personal data through a large language model. An exploratory user study with six participants investigated the impact of the comic on user experience.
Citation
@inproceedings{Zieglmeier2026Personal,
author = {Maria Zieglmeier, Shivam Agarwal, Lukas Panzer, and Fabian Beck},
title = {Personal Reflection through Adaptive Data Comics: A Story on Reading Data},
booktitle = {Companion Proceedings of the 31st International Conference on Intelligent User Interfaces},
pages = {85–88},
year = {2026},
publisher = {Association for Computing Machinery},
doi = {10.1145/3742414.3794715},
paperurl = {/publications/Zieglmeier2026Personal/Zieglmeier2026Personal.pdf},
demo = {https://personal-datacomic.web.app/},
abstract = {Data comics are an appealing medium for visualizing personal taste and interests. As a design study, this paper presents an interactive data comic that analyzes personal reading data. It adapts both content and structure to users’ data and selections. Combining elements of data visualization, sequential storytelling, and user interactivity, the comic transforms the data into a relatable narrative organized in different chapters. Accompanying the visualizations, data analysis guidance and book recommendations are generated specific to the personal data through a large language model. An exploratory user study with six participants investigated the impact of the comic on user experience.}
}