# Characterizing Grounded Theory Approaches in Visualization

arXiv: https://arxiv.org/abs/2203.01777 · HTML: https://mlsanity.com/paper/2203.01777/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Mar 2022.

## Built on by (most cited first, 1 of 1)

- [Understanding How Humans Inject Knowledge into Machine Learning Workflows through Visual Analytics](https://mlsanity.com/paper/2607.00969/) (2026)

## Abstract (arXiv)

Grounded theory (GT) is a research methodology that entails a systematic workflow for theory generation grounded on emergent data. In this paper, we juxtapose GT workflows with typical workflows in visualization and visual analytics, shortly VIS, and underline the characteristics shared by these workflows. We explore the research landscape of VIS to observe where GT has been applied to generate VIS theories, explicitly as well as implicitly. We propose a "why" typology for characterizing aspects in VIS where GT can potentially play a significant role. We outline a "how" methodology for conducting GT research in VIS, which addresses the need for theoretical advancement in VIS while benefitting from other methods and techniques in VIS. We exemplify this "how" methodology by adopting GT approaches in studying the messages posted on VisGuides - an Open Discourse Forum for discussing visualization guidelines.