Cheat Sheets for Data Visualization Techniques

Zezhong Wang, Lovisa Sundin, Dave Murray-Rust, Benjamin Bach

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

30 Citations (Scopus)

Abstract

This paper introduces the concept of 'cheat sheets' for data visualization techniques, a set of concise graphical explanations and textual annotations inspired by infographics, data comics, and cheat sheets in other domains. Cheat sheets aim to address the increasing need for accessible material that supports a wide audience in understanding data visualization techniques, their use, their fallacies and so forth. We have carried out an iterative design process with practitioners, teachers and students of data science and visualization, resulting six types of cheat sheet (anatomy, construction, visual patterns, pitfalls, false-friends and well-known relatives) for six types of visualization, and formats for presentation. We assess these with a qualitative user study using 11 participants that demonstrates the readability and usefulness of our cheat sheets.

Original languageEnglish
Title of host publicationCHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery (ACM)
ISBN (Electronic)9781450367080
DOIs
Publication statusPublished - 2020
Externally publishedYes
Event2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020 - Honolulu, United States
Duration: 25 Apr 202030 Apr 2020

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020
Country/TerritoryUnited States
CityHonolulu
Period25/04/2030/04/20
OtherVirtual/online event due to COVID-19

Keywords

  • cheat sheet
  • visualization literacy

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