# Visualizing Uncertainty in Sets

## TL;DR

This paper explores how to effectively visualize uncertainty in set data, addressing the impact of uncertainty on set attributes and proposing a conceptual framework for integrating uncertainty into set visualizations.

## Contribution

It introduces a comprehensive conceptual framework for visualizing uncertainty in set data, bridging gaps between set-specific and general uncertainty visualization techniques.

## Key findings

- Developed a conceptual framework linking set attributes and uncertainty categories.
- Systematically discussed visualization examples incorporating uncertainty in sets.
- Identified key aspects of set data affected by uncertainty and their visualization implications.

## Abstract

Set visualization facilitates the exploration and analysis of set-type data. However, how sets should be visualized when the data is uncertain is still an open research challenge. To address the problem of depicting uncertainty in set visualization, we ask (i) which aspects of set type data can be affected by uncertainty and (ii) which characteristics of uncertainty influence the visualization design. We answer these research questions by first developing a conceptual framework that brings together (i) the information that is primarily relevant in sets (i.e., set membership, set attributes, and element attributes) and (ii) different plausible categories of (un)certainty (i.e., certainty, undefined uncertainty as a binary fact, and defined uncertainty as quantifiable measure). Based on the conceptual framework, we systematically discuss visualization examples of integrating uncertainty in set visualizations. We draw on existing knowledge about general uncertainty visualization and fill gaps where set-specific aspects have not yet been considered sufficiently.