Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

16.6K
Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...
16.6K
Ogive Graph01:07

Ogive Graph

6.6K
An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
6.6K
Multiple Bar Graph01:07

Multiple Bar Graph

8.9K
As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
8.9K
Statgraphics01:10

Statgraphics

370
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
370
Components of Language01:24

Components of Language

723
Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs.
723
Bar Graph01:07

Bar Graph

21.3K
A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show comparisons among categories. The bars can be rectangles, or they can be rectangular boxes (used in three-dimensional plots). One axis of the graph represents the specific categories being compared, and the other axis shows a discrete value. In this graph, the length of the bar for each category is proportional to the number or percent of individuals...
21.3K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Quantifying Visualization Vibes: Measuring Socio-Indexicality at Scale.

IEEE transactions on visualization and computer graphics·2025
Same author

Visualization Vibes: The Socio-Indexical Function of Visualization Design.

IEEE transactions on visualization and computer graphics·2025
Same author

Charting EDA: Characterizing Interactive Visualization Use in Computational Notebooks with a Mixed-Methods Formalism.

IEEE transactions on visualization and computer graphics·2024
Same author

Heuristics for Supporting Cooperative Dashboard Design.

IEEE transactions on visualization and computer graphics·2023
Same author

Animated Vega-Lite: Unifying Animation with a Grammar of Interactive Graphics.

IEEE transactions on visualization and computer graphics·2022
Same author

Striking a Balance: Reader Takeaways and Preferences when Integrating Text and Charts.

IEEE transactions on visualization and computer graphics·2022
Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026
Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026
Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026
Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

IEEE transactions on visualization and computer graphics·2026
Same journal

RTF2Mesh: Restricted Tangent Face Based Mesh Compression With Neural Displacement Fields.

IEEE transactions on visualization and computer graphics·2026
Same journal

Practical Occluder Generation for Mobile Games.

IEEE transactions on visualization and computer graphics·2026
See all related articles

Related Experiment Video

Updated: Jan 9, 2026

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
05:33

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Published on: January 29, 2020

6.4K

GoFish: A Grammar of More Graphics!

Josh Pollock, Arvind Satyanarayan

    IEEE Transactions on Visualization and Computer Graphics
    |December 3, 2025
    PubMed
    Summary
    This summary is machine-generated.

    GoFish is a new declarative visualization grammar that expands beyond the limitations of the Grammar of Graphics (GoG). It formalizes Gestalt principles for greater expressive power and an infinite design space.

    More Related Videos

    Using Generative Art to Convey Past and Future Climate Transitions
    06:10

    Using Generative Art to Convey Past and Future Climate Transitions

    Published on: March 31, 2023

    1.4K
    Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
    10:58

    Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

    Published on: August 28, 2021

    4.9K

    Related Experiment Videos

    Last Updated: Jan 9, 2026

    Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
    05:33

    Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

    Published on: January 29, 2020

    6.4K
    Using Generative Art to Convey Past and Future Climate Transitions
    06:10

    Using Generative Art to Convey Past and Future Climate Transitions

    Published on: March 31, 2023

    1.4K
    Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
    10:58

    Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

    Published on: August 28, 2021

    4.9K

    Area of Science:

    • Computer Science
    • Human-Computer Interaction
    • Information Visualization

    Background:

    • The Grammar of Graphics (GoG) is a foundational theory for visualization grammars like ggplot2 and Vega-Lite.
    • While GoG expanded visualization capabilities beyond fixed chart types, it has limitations, excluding charts like mosaics and waffles.
    • Current GoG implementations require custom mark types or lower-level frameworks for unsupported charts.

    Purpose of the Study:

    • Introduce GoFish, a novel declarative visualization grammar.
    • Formalize Gestalt principles within a visualization grammar framework.
    • Enable recursive composition for a more expressive and flexible design space.

    Main Methods:

    • Developed GoFish, a declarative grammar formalizing Gestalt principles (e.g., uniform spacing, containment, connection).
    • Implemented graphical operators that support arbitrary nesting and overlapping (recursive composition).
    • Demonstrated GoFish's capabilities through a diverse gallery of visualization examples.

    Main Results:

    • GoFish operators enable greater expressive power compared to existing GoG implementations.
    • Users can arrange shapes in diverse ways while retaining high-level grammar benefits (scale resolution, coordinate transforms).
    • Recursive composition creates an infinite design space, blurring lines between low-level and high-level grammars.

    Conclusions:

    • GoFish overcomes limitations of current visualization grammars by incorporating Gestalt principles and recursive composition.
    • This approach offers an updated theory of visualization, embracing an innumerable space of graphic representations.
    • GoFish provides a powerful, flexible, and concise tool for visualization design.