Gender in 30 Years of IEEE Visualization

We present an exploratory analysis of gender representation among the authors, committee members, and award winners at the IEEE Visualization (VIS) conference over the last 30 years. Our goal is to provide descriptive data on which diversity discussions and efforts in the community can build. We look in particular at the gender of VIS authors as a proxy for the community at large. We consider measures of overall gender representation among authors, differences in careers, positions in author lists, and collaborations. We found that the proportion of female authors has increased from 9% in the first five years to 22% in the last five years of the conference. Over the years, we found the same representation of women in program committees and slightly more women in organizing committees. Women are less likely to appear in the last author position, but more in the middle positions. In terms of collaboration patterns, female authors tend to collaborate more than expected with other women in the community. All non-gender related data is available on https://osf.io/ydfj4/ and the gender-author matching can be accessed through https://nyu.databrary.org/volume/1301.

1 Introduction

We present a descriptive, exploratory data analysis of gender representation in the academic visualization community. We draw data from authors of papers published at the IEEE Visualization (VIS) conference, the largest and oldest academic visualization-focused venue. At the VIS conference, gender as well as more broad diversity efforts have started to emerge. Since 2014, we have seen efforts such as the first Family Room (2014), VisKids Chairs (2015), and in 2017 the first panel on the topic of diversity more broadly. Since 2018, inclusivity chairs are part of the organizing committee and have put tremendous efforts into new initiatives such as the inclusivity and diversity scholarships. The new VIS charter [20] emphasizes that “all committees should be diverse in their membership in terms of research area, academic lineage, gender, geographic origin, sector (academia, industry, government), demographics and other characteristics as they emerge:”