Eleven Years of Gender Data Visualization: A Step Towards More Inclusive Gender Representation
Florent Cabric, Margr\'et Vilborg Bjarnad\'ottir, Meng Ling,, Gu{\dh}bj\"org Linda Rafnsd\'ottir, Petra Isenberg

TL;DR
This paper analyzes gender data visualization practices across disciplines, highlighting biases and proposing considerations to promote more inclusive and ethical representations of gender in visualizations.
Contribution
It provides a comprehensive analysis of gender visualization practices, identifying biases and offering guidelines to improve inclusivity and ethical standards in data visualizations.
Findings
Color hue is the dominant visual variable for gender data.
Representation of nonconforming gender is under-represented.
Representation types vary significantly across disciplines.
Abstract
We present an analysis of the representation of gender as a data dimension in data visualizations and propose a set of considerations around visual variables and annotations for gender-related data. Gender is a common demographic dimension of data collected from study or survey participants, passengers, or customers, as well as across academic studies, especially in certain disciplines like sociology. Our work contributes to multiple ongoing discussions on the ethical implications of data visualizations. By choosing specific data, visual variables, and text labels, visualization designers may, inadvertently or not, perpetuate stereotypes and biases. Here, our goal is to start an evolving discussion on how to represent data on gender in data visualizations and raise awareness of the subtleties of choosing visual variables and words in gender visualizations. In order to ground this…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsData Visualization and Analytics
