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The State of Reproducibility Stamps for Visualization Research Papers

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  • Additional Information
    • Contributors:
      Isenberg, Tobias; Analysis and Visualization (AVIZ); Inria Saclay - Ile de France; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Interdisciplinaire des Sciences du Numérique (LISN); Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Interaction avec l'Humain (IaH); Laboratoire Interdisciplinaire des Sciences du Numérique (LISN); Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS); IEEE Computer Society
    • Publication Information:
      Preprint
    • Publication Information:
      IEEE, 2024.
    • Publication Date:
      2024
    • Abstract:
      I analyze the evolution of papers certified by the Graphics Replicability Stamp Initiative (GRSI) to be reproducible, with a specific focus on the subset of publications that address visualization-related topics. With this analysis I show that, while the number of papers is increasing overall and within the visualization field, we still have to improve quite a bit to escape the replication crisis. I base my analysis on the data published by the GRSI as well as publication data for the different venues in visualization and lists of journal papers that have been presented at visualization-focused conferences. I also analyze the differences between the involved journals as well as the percentage of reproducible papers in the different presentation venues. Furthermore, I look at the authors of the publications and, in particular, their affiliation countries to see where most reproducible papers come from. Finally, I discuss potential reasons for the low reproducibility numbers and suggest possible ways to overcome these obstacles. This paper is reproducible itself, with source code and data available from github.com/tobiasisenberg/Visualization-Reproducibility as well as a free paper copy and all supplemental materials at osf.io/mvnbj.
      9 pages plus appendix; 12 figures plus 14 figures in the appendix
    • File Description:
      application/pdf
    • Accession Number:
      10.1109/beliv64461.2024.00016
    • Accession Number:
      10.48550/arxiv.2408.03889
    • Rights:
      STM Policy #29
      CC BY
    • Accession Number:
      edsair.doi.dedup.....eb1ec8993f7416d7e76e1264d62ed3fd