We present and discuss the results of a qualitative analysis of visualization images to derive an image-based typology of visualizations. For each image, we seek to identify its main focus or the essential stimuli. As a result, we derived 10 image-based visualization types. We describe coding decisions we made in the derivation process. The resulting image typology can serve a number of purposes: enabling researchers and practitioners to identify visual design styles, facilitating the categorization of visualization images for the purpose of research and teaching, enabling researchers to study the evolution of the community and its research output over time, and facilitating a discussion of standardization in visualization. In addition, the tool and dataset enable scholars to closely examine the images and how they are published and communicated in our community. osf.io/dxjwt presents a pre-registration and all supplemental materials.
@article{arxiv.2403.05594,
title = {An Image-based Typology for Visualization},
author = {Jian Chen and Petra Isenberg and Robert S. Laramee and Tobias Isenberg and Michael Sedlmair and Torsten Moeller and Rui Li},
journal= {arXiv preprint arXiv:2403.05594},
year = {2025}
}
Comments
arXiv admin note: text overlap with arXiv:2209.07533