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

Interpreting R Charts01:22

Interpreting R Charts

135
R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
135
Interpreting Run Charts01:25

Interpreting Run Charts

2.8K
Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
2.8K
Time-Series Graph00:54

Time-Series Graph

4.6K
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...
4.6K
Scatter Plot01:15

Scatter Plot

10.0K
The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:
10.0K
Sleep-Wake Cycles01:24

Sleep-Wake Cycles

1.8K
Sleep is an essential physiological process vital to maintaining overall well-being. The reticular activating system (RAS), a network of neurons in the brainstem, regulates wakefulness and sleep. While it may seem passive, sleep consists of distinct cycles, each with its unique characteristics and functions. Two key sleep phases are non-rapid eye movement (NREM) and  rapid eye movement (REM).
NREM Sleep
NREM sleep comprises four progressive stages that seamlessly merge:
1.8K
Graphical and Analytic Representation of Sinusoids01:20

Graphical and Analytic Representation of Sinusoids

545
Analyzing two sinusoidal voltages with equal amplitude and period but different phases on an oscilloscope, an instrument used to display and analyze waveforms, involves a three-step process.
The first step is measuring the peak-to-peak value, which is twice the amplitude of the sinusoid. This provides information about the maximum voltage swing of the waveform.
Secondly, the period and angular frequency are determined. The period is the time taken for one complete cycle of the waveform, while...
545

You might also read

Related Articles

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

Sort by
Same author

The impact of abiraterone and enzalutamide on hypokalemia incidence in patients with prostate cancer: a systematic review and meta-analysis.

BMC cancer·2026
Same author

Polysaccharides-gut microbiota interaction: mechanisms regulating the hepatocellular carcinoma immune microenvironment.

Frontiers in immunology·2026
Same author

Shared molecular signatures linking gastroesophageal reflux disease and major depressive disorder revealed by integrated machine learning.

BMC gastroenterology·2026
Same author

GVHMR: Gravity-View Coordinates for Global Human Motion Recovery From Monocular Videos.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

RuleScope: Semantic-Aware Authoring of Data Validation Rules.

IEEE transactions on visualization and computer graphics·2026
Same author

Adaptive resistance in cancer immunotherapy.

Cellular & molecular immunology·2026
Same journal

Blue Noise Dithering for Reservoir-based Spatio-temporal Importance Resampling.

IEEE transactions on visualization and computer graphics·2026
Same journal

ROS-GS: Relightable Outdoor Scenes With Gaussian Splatting.

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

Related Experiment Videos

Visualizing the Scripts of Data Wrangling With Somnus.

Kai Xiong, Siwei Fu, Guoming Ding

    IEEE Transactions on Visualization and Computer Graphics
    |January 25, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces Somnus, a visualization tool that helps data workers understand data transformations more easily. Somnus improves accuracy and reduces time spent on complex code, making data transformation more accessible.

    Related Experiment Videos

    Area of Science:

    • Computer Science
    • Data Visualization
    • Human-Computer Interaction

    Background:

    • Data transformation using scripting languages like SAS, R, and Python often requires advanced programming skills.
    • This complexity hinders data workers' intuitive understanding of data transformation processes.
    • Program visualization offers a potential solution for intuitive and interactive illustration of transformations.

    Purpose of the Study:

    • To explore visualization design for demonstrating the semantics of code in data transformation.
    • To develop a system that aids data workers in understanding and performing data transformations.
    • To evaluate the effectiveness and usability of the proposed visualization approach.

    Main Methods:

    • Structured a design space for depicting data transformations based on encoding parameters and visual channels.
    • Derived 23 glyphs to visualize the semantics of various transformations.
    • Designed and implemented a pipeline named Somnus, utilizing a provenance graph for data table evolution overview and detailed transformation investigation.

    Main Results:

    • User feedback on Somnus was positive, indicating improved accuracy and reduced completion time compared to textual descriptions.
    • Participants preferred Somnus over traditional textual explanations for understanding data transformations.
    • Two example applications demonstrated the utility and versatility of the Somnus pipeline.

    Conclusions:

    • Visualization design is effective for illustrating data transformation semantics.
    • The Somnus pipeline provides an intuitive and efficient approach to understanding data transformations.
    • Somnus has the potential to lower the barrier for data workers to grasp complex data manipulation concepts.