@inproceedings{1afa2613d7a04f3bb31ed0cb144f7458,
title = "A classification of infographics",
abstract = "Classifications are useful for describing existing phenomena and guiding further investigation. Several classifications of diagrams have been proposed, typically based on analytical rather than empirical methodologies. A notable exception is the work of Lohse and his colleagues, published in Communications of the ACM in December 1994. The classification of diagrams that Lohse proposed was derived from bottom-up grouping data collected from sixteen participants and based on 60 diagrams. Mean values on ten Likert-scales were used to predict diagram class. We follow a similar methodology to Lohse, using real-world infographics (i.e. embellished data charts) as our stimuli. We propose a structural classification of infographics, and determine whether infographics class can be predicted from values on Likert scales.",
keywords = "Classification, Empirical studies, Infographics",
author = "Purchase, \{Helen C.\} and Katherine Isaacs and Thomas Bueti and Ben Hastings and Aadam Kassam and Allen Kim and \{van Hoesen\}, Steffan",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 10th International Conference on the Theory and Application of Diagrams, Diagrams 2018 ; Conference date: 18-06-2018 Through 22-06-2018",
year = "2018",
doi = "10.1007/978-3-319-91376-6\_21",
language = "English (US)",
isbn = "9783319913759",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag",
pages = "210--218",
editor = "Gem Stapleton and Francesco Bellucci and Amirouche Moktefi and Peter Chapman and Sarah Perez-Kriz",
booktitle = "Diagrammatic Representation and Inference - 10th International Conference, Diagrams 2018, Proceedings",
}