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|a 10.1109/TVCG.2022.3158236
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|a eng
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|a Sarvghad, Ali
|e verfasserin
|4 aut
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|a Scientometric Analysis of Interdisciplinary Collaboration and Gender Trends in 30 Years of IEEE VIS Publications
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|c 2023
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|a Date Completed 29.05.2023
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|a Date Revised 30.05.2023
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a We present the results of a scientometric analysis of 30 years of IEEE VIS publications between 1990-2020, in which we conducted a multifaceted analysis of interdisciplinary collaboration and gender composition among authors. To this end, we curated BiblioVIS, a bibliometric dataset that contains rich metadata about IEEE VIS publications, including 3032 articles and 6113 authors. One of the main factors differentiating BiblioVIS from similar datasets is the authors' gender and discipline data, which we inferred through iterative rounds of computational and manual processes. Our analysis shows that, by and large, inter-institutional and interdisciplinary collaboration has been steadily growing over the past 30 years. However, interdisciplinary research was mainly between a few fields, including Computer Science, Engineering and Technology, and Medicine and Health disciplines. Our analysis of gender shows steady growth in women's authorship. Despite this growth, the gender distribution is still highly skewed, with men dominating ( ≈ 75%) of this space. Our predictive analysis of gender balance shows that if the current trends continue, gender parity in the visualization field will not be reached before the third quarter of the century ( ≈ 2070). Our primary goal in this work is to call the visualization community's attention to the critical topics of collaboration, diversity, and gender. Our research offers critical insights through the lens of diversity and gender to help accelerate progress towards a more diverse and representative research community
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|a Journal Article
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|a Franqui-Nadal, Rolando
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1 |
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|a Reznik-Zellen, Rebecca
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|a Chawla, Ria
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|a Mahyar, Narges
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|t IEEE transactions on visualization and computer graphics
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|g 29(2023), 7 vom: 14. Juli, Seite 3340-3353
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|g year:2023
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|u http://dx.doi.org/10.1109/TVCG.2022.3158236
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