A Probabilistic Grammar of Graphics

Pu, Xiaoying; Kay, Matthew

doi:10.1145/3313831.3376466

Cited by 18 publications

(10 citation statements)

References 39 publications

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“…Several studies have used the Cognitive Dimensions of Notations [6], a set of heuristics, to evaluate the usability of a grammar (e.g. Vega [57], Nebula [15], the Probabilistic Grammar of Graphics [48]). These [69], and ggplot2 specifcation.…”

Section: Evaluating the Benefts Of Visualization Grammarsmentioning

confidence: 99%

“…dimensions imply that if a grammar evaluates favorably, it can promote the iteration of visualization specifcation and the exploration of the visualization design space, as argued in Pu & Kay [48].…”

Section: Evaluating the Benefts Of Visualization Grammarsmentioning

confidence: 99%

“…When evaluated with usability heuristics (i.e. the cognitive dimensions of notations [6]), GoG-based grammars have been found to promote iteration and encourage the exploration of visualization designs [48,57].…”

Section: Introductionmentioning

confidence: 99%

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How Data Analysts Use a Visualization Grammar in Practice

Pu¹,

Kay²

2023

Preprint

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Visualization grammars, often based on the Grammar of Graphics (GoG), have much potential for augmenting data analysis in a programming environment. However, we do not know how analysts conceptualize grammar abstractions, or how a visualization grammar works with data analysis in practice. Therefore, we qualitatively analyzed how experienced analysts (N=6) from TidyTuesday, a social data project, wrangled and visualized data using GoG-based ggplot2 without given tasks in R Markdown. Though participants' analysis and customization needs could mismatch with GoG component design, their analysis processes aligned with the goal of GoG to expedite visualization iteration. We also found a feedback loop and tight coupling between visualization and data transformation code, explaining both participants' productivity and their errors. From these results, we discuss how future visualization grammars can become more practical for analysts and how visualization grammar and analysis tools can better integrate within a programming (i.e., computational notebook) environment.

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Section: Evaluating the Benefts Of Visualization Grammarsmentioning

confidence: 99%

Section: Evaluating the Benefts Of Visualization Grammarsmentioning

confidence: 99%

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How Data Analysts Use a Visualization Grammar in Practice

Pu¹,

Kay²

2023

Preprint

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“…Xiaoying Pu is a Ph.D. candidate at the University of Michigan. In her research, she takes a human-centered approach to communicating uncertainty and statistics with visualizations [41,43]. She has organized a CHI 2021 SIG on visualization grammars [42] and contributed to a research transparency tutorial at IEEE VIS 2020.…”

Section: Instructorsmentioning

confidence: 99%

Transparent Practices for Quantitative Empirical Research

Wacharamanotham

Yang

et al. 2022

CHI Conference on Human Factors in Computing Systems Extended Abstracts

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Transparent research practices analytic methods, and data to be thoroughly evaluated and potentially reproduced. The HCI community has recognized research transparency as one quality aspect of paper submission and review since CHI 2021. This course addresses HCI researchers and students who are already knowledgeable about experiment research design and statistical analysis. Building upon this knowledge, we will present current best practices and tools for increasing research transparency. We will cover relevant concepts and skills in Open Science, frequentist statistics, and Bayesian statistics, and uncertainty visualization. In addition to lectures, there will be hands-on exercises: The course participants will assess transparency practices in excerpts of quantitative reports, interactively explore implications of analytical choices using RStudio Cloud, and discuss their fndings in small groups. In the fnal session, each participant will choose a case study based on their interest and assess its research transparency together with their classmates and instructors.enable the research design, materials, CCS CONCEPTS• Human-centered computing → HCI design and evaluation methods; Visualization techniques; Visualization design and evaluation methods.

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“…In visualization literature, we have been using the term grammar without explicitly articulating what we mean by it. Recent papers have described grammars for interactive visualizations [14], probability distributions [13], and animated transitions [3,6], in addition to GoG-inspired systems in industry (e.g. Plotly Express [12]).…”

Section: What Makes a Grammar?mentioning

confidence: 99%

Special Interest Group on Visualization Grammars

Kay

Drucker

et al. 2021

Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems

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The popularity of these visualization grammars is evident. As open-source packages, ggplot2 (R) has around 1.5 million down-Visualization grammars, often based on the Grammar of Graphics, are popular choices for specifying expressive visualizations and loads from CRAN per month 1 and Vega-Lite (JSON specifcation) supporting visualization systems. However, there are still open has 2 million CDN hits per month 2 . Users of visualization grammars are well beyond the visualization research community -journalquestions about grammar design and evaluation not well-answered in visualization research. In this SIG, we propose to discuss what ists use D3 3 and ggplot2 [5] in their reporting, and authors of ggplot2 books have background in felds like statistics [19] and makes a grammar "good" and explore evaluation methodologies sociology [4]. best suited for visualization grammars. Increasingly, visualization grammars have become building blocks for other formalisms and systems. To support data explo-CCS CONCEPTS ration and question answering in visual analysis, Voyager 2, a • Human-centered computing → Visualization design and mixed-initiative system, is powered through CompassQL, "a generevaluation methods; Visualization theory, concepts and alization of the Vega-Lite grammar" [14, 22]. To depict probability paradigms; Visualization application domains. distributions, A Probabilistic Grammar of Graphics makes probability expressions such as P(A|B) frst-class citizens on top of the KEYWORDS original GoG [13]. For high-performance visual analytics, P6 lever-Grammar of Graphics ages a declarative grammar to integrate interactive visualizations

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A Probabilistic Grammar of Graphics

Cited by 18 publications

References 39 publications

How Data Analysts Use a Visualization Grammar in Practice

How Data Analysts Use a Visualization Grammar in Practice

Transparent Practices for Quantitative Empirical Research

Special Interest Group on Visualization Grammars

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