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eulerAPE: Drawing Area-Proportional 3-Venn Diagrams Using Ellipses

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  • Luana Micallef
  • Peter Rodgers

Abstract

Venn diagrams with three curves are used extensively in various medical and scientific disciplines to visualize relationships between data sets and facilitate data analysis. The area of the regions formed by the overlapping curves is often directly proportional to the cardinality of the depicted set relation or any other related quantitative data. Drawing these diagrams manually is difficult and current automatic drawing methods do not always produce appropriate diagrams. Most methods depict the data sets as circles, as they perceptually pop out as complete distinct objects due to their smoothness and regularity. However, circles cannot draw accurate diagrams for most 3-set data and so the generated diagrams often have misleading region areas. Other methods use polygons to draw accurate diagrams. However, polygons are non-smooth and non-symmetric, so the curves are not easily distinguishable and the diagrams are difficult to comprehend. Ellipses are more flexible than circles and are similarly smooth, but none of the current automatic drawing methods use ellipses. We present eulerAPE as the first method and software that uses ellipses for automatically drawing accurate area-proportional Venn diagrams for 3-set data. We describe the drawing method adopted by eulerAPE and we discuss our evaluation of the effectiveness of eulerAPE and ellipses for drawing random 3-set data. We compare eulerAPE and various other methods that are currently available and we discuss differences between their generated diagrams in terms of accuracy and ease of understanding for real world data.

Suggested Citation

  • Luana Micallef & Peter Rodgers, 2014. "eulerAPE: Drawing Area-Proportional 3-Venn Diagrams Using Ellipses," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-18, July.
  • Handle: RePEc:plo:pone00:0101717
    DOI: 10.1371/journal.pone.0101717
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    Cited by:

    1. Gem Stapleton & Peter Chapman & Peter Rodgers & Anestis Touloumis & Andrew Blake & Aidan Delaney, 2019. "The efficacy of Euler diagrams and linear diagrams for visualizing set cardinality using proportions and numbers," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-25, March.
    2. de Nooy, Wouter & Leydesdorff, Loet, 2015. "The dynamics of triads in aggregated journal–journal citation relations: Specialty developments at the above-journal level," Journal of Informetrics, Elsevier, vol. 9(3), pages 542-554.
    3. Hansel Tookes & Chanelle Diaz & Hua Li & Rafi Khalid & Susanne Doblecki-Lewis, 2015. "A Cost Analysis of Hospitalizations for Infections Related to Injection Drug Use at a County Safety-Net Hospital in Miami, Florida," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-11, June.
    4. Mikael Laakso & Andrea Polonioli, 2018. "Open access in ethics research: an analysis of open access availability and author self-archiving behaviour in light of journal copyright restrictions," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 291-317, July.
    5. Charles Warwick & Joseph Salsovic & Junichi Hachisuka & Kelly M. Smith & Tayler D. Sheahan & Haichao Chen & James Ibinson & H. Richard Koerber & Sarah E. Ross, 2022. "Cell type-specific calcium imaging of central sensitization in mouse dorsal horn," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    6. Matthias Buntins & Katja Buntins & Frank Eggert, 2016. "Psychological tests from a (fuzzy-)logical point of view," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(6), pages 2395-2416, November.
    7. Rishi Kumar, 2018. "Different Approaches to Identify the Poor: Do They converge?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 139(2), pages 589-610, September.
    8. Lei Sun & Hui Liu & Lin Zhang & Jia Meng, 2015. "lncRScan-SVM: A Tool for Predicting Long Non-Coding RNAs Using Support Vector Machine," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-16, October.
    9. Stefano Biagetti & Debora Zurro & Jonas Alcaina-Mateos & Eugenio Bortolini & Marco Madella, 2021. "Quantitative Analysis of Drought Management Strategies across Ethnographically-Researched African Societies: A Pilot Study," Land, MDPI, vol. 10(10), pages 1-15, October.

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