Cheat Sheets for Data Visualization Techniques

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

doi:10.1145/3313831.3376271

Cheat Sheets for Data Visualization Techniques

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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
format for presentation. We assess these with a qualitative user study using 11 participants that demonstrates the readability and usefulness of our cheat sheets.

Original language	English
Title of host publication	CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
Publisher	ACM
Number of pages	13
ISBN (Electronic)	9781450367080
DOIs	https://doi.org/10.1145/3313831.3376271
Publication status	Published - 21 Apr 2020
Event	ACM CHI Conference on Human Factors in Computing Systems - Hawaiʻi Convention Center on the island of Oahu, Honolulu, United States Duration: 25 Apr 2020 → 30 Apr 2020 https://chi2020.acm.org/

Conference

Conference	ACM CHI Conference on Human Factors in Computing Systems
Abbreviated title	CHI 2020
Country	United States
City	Honolulu
Period	25/04/20 → 30/04/20
Internet address	https://chi2020.acm.org/

Access to Document

10.1145/3313831.3376271Licence: All Rights Reserved

wang2020cheatAccepted author manuscript, 23.9 MB

https://visualinteractivedata.github.io/papers/wang2020cheat.pdf
https://dl.acm.org/doi/10.1145/3313831.3376271Licence: All Rights Reserved

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Cite this

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title = "Cheat Sheets for Data Visualization Techniques",

abstract = "This paper introduces the concept of {\textquoteleft}cheat sheets{\textquoteright} for datavisualization 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, andformat for presentation. We assess these with a qualitative user study using 11 participants that demonstrates the readability and usefulness of our cheat sheets.",

author = "Zezhong Wang and Lovisa Sundin and Dave Murray-Rust and Benjamin Bach",

year = "2020",

month = apr,

day = "21",

doi = "10.1145/3313831.3376271",

language = "English",

booktitle = "CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems",

publisher = "ACM",

note = "ACM CHI Conference on Human Factors in Computing Systems, CHI 2020 ; Conference date: 25-04-2020 Through 30-04-2020",

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AU - Wang, Zezhong

AU - Sundin, Lovisa

AU - Murray-Rust, Dave

AU - Bach, Benjamin

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Y1 - 2020/4/21

N2 - This paper introduces the concept of ‘cheat sheets’ for datavisualization 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, andformat for presentation. We assess these with a qualitative user study using 11 participants that demonstrates the readability and usefulness of our cheat sheets.

AB - This paper introduces the concept of ‘cheat sheets’ for datavisualization 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, andformat for presentation. We assess these with a qualitative user study using 11 participants that demonstrates the readability and usefulness of our cheat sheets.

U2 - 10.1145/3313831.3376271

DO - 10.1145/3313831.3376271

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BT - CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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Y2 - 25 April 2020 through 30 April 2020

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