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

Ogive Graph01:07

Ogive Graph

5.6K
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...
5.6K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

3.1K
3.1K
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

12.1K
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...
12.1K
Bar Graph01:07

Bar Graph

16.4K
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...
16.4K
Time-Series Graph00:54

Time-Series Graph

4.3K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
4.3K
Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

5.0K
It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
5.0K

You might also read

Related Articles

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

Sort by
Same author

A high-molecular-weight polysaccharide from Polygonatum sibiricum inhibits distant tumor growth associated with gut microbiota remodeling and synergizes with αPD-1 therapy.

International journal of biological macromolecules·2026
Same author

NANOS3-YTHDF2 drives aberrant P-body accumulation to impair folliculogenesis in offspring of maternal aristolochic acid I exposure.

Cell communication and signaling : CCS·2026
Same author

The crosstalk between lymphatic endothelial cells and immune cells in Physiological and Pathological conditions.

Cellular and molecular life sciences : CMLS·2026
Same author

Challenges and Solutions in Deploying Systematized Nomenclature of Medicine-Clinical Terms in the Chinese Healthcare Context.

Health care science·2026
Same author

Effect of noise isolation during general anaesthesia on the incidence of moderate-to-severe pain after major abdominal surgery: multicentre randomized clinical study.

BJS open·2026
Same author

Sequence-Engineered G-Triplex/Methylene Blue System as a Label-Free Electrochemical Signal Module for Biosensor.

Analytical chemistry·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
Same journal

Spatial-temporal Relation guided Motion Transfer via Diffusion Model.

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

Related Experiment Video

Updated: Jun 24, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

1.6K

Linking Text and Visualizations via Contextual Knowledge Graph.

Xiwen Cai, Di Weng, Taotao Fu

    IEEE Transactions on Visualization and Computer Graphics
    |June 11, 2024
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a semi-automatic pipeline to link text and visualizations, making data insights more accessible. The method uses knowledge graphs and user input for effective text-visualization integration.

    More Related Videos

    Visualizing Lignification Dynamics in Plants with Click Chemistry: Dual Labeling is BLISS!
    10:40

    Visualizing Lignification Dynamics in Plants with Click Chemistry: Dual Labeling is BLISS!

    Published on: January 26, 2018

    12.0K
    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
    07:36

    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects

    Published on: November 30, 2018

    15.7K

    Related Experiment Videos

    Last Updated: Jun 24, 2025

    A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
    07:35

    A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

    Published on: October 13, 2023

    1.6K
    Visualizing Lignification Dynamics in Plants with Click Chemistry: Dual Labeling is BLISS!
    10:40

    Visualizing Lignification Dynamics in Plants with Click Chemistry: Dual Labeling is BLISS!

    Published on: January 26, 2018

    12.0K
    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects
    07:36

    Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects

    Published on: November 30, 2018

    15.7K

    Area of Science:

    • Human-Computer Interaction
    • Data Visualization
    • Natural Language Processing

    Background:

    • Integrating text and visualizations is crucial for data communication but technically challenging.
    • Existing methods often require advanced programming skills, limiting accessibility.
    • Effective linking enhances understanding of data insights.

    Purpose of the Study:

    • To propose a semi-automatic pipeline for creating links between textual content and visualizations.
    • To simplify the process of integrating text and visual data representations.
    • To enable flexible customization of text-visualization relationships.

    Main Methods:

    • Structuring visualizations and data as a contextual knowledge graph.
    • Extracting, grouping, and mapping text key phrases with visual elements.
    • Incorporating user knowledge for mixed-initiative revision of text-visualization links.

    Main Results:

    • Demonstrated versatility through interactive visualizations, annotations, and text-chart interactions.
    • Preliminary model tests and a user study indicated the method's effectiveness.
    • Successful replication of prior studies using the developed prototype system.

    Conclusions:

    • The proposed pipeline effectively links text and visualizations, reducing technical barriers.
    • The mixed-initiative approach allows for user-driven customization and refinement.
    • This method enhances the creation of informative and interactive data narratives.