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

Transformations of Functions III01:20

Transformations of Functions III

264
Transformations modify the graphical representation of a function without changing its fundamental form. One common transformation is reflection, which flips the graph across a designated axis. When the vertical coordinates of all points are multiplied by the negative one, the entire graph is mirrored over the horizontal axis. This transformation reverses the vertical orientation of peaks and troughs, akin to signal inversion in electrical systems, where a waveform is flipped, but the timing of...
264
Multiple Bar Graph01:07

Multiple Bar Graph

10.5K
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...
10.5K
Bar Graph01:07

Bar Graph

23.7K
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...
23.7K
Interpreting R Charts01:22

Interpreting R Charts

403
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...
403
Pie Chart01:04

Pie Chart

16.9K
A pie chart (or a pie graph) is a circular graphical chart or a pictorial representation of categorical data. It is divided into slices of pie each indicating numerical proportions. It is also used to show the relative sizes of data in a single chart.
In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. Some real-world examples that can be depicted using pie charts include marks obtained by students...
16.9K
Modified Boxplots00:57

Modified Boxplots

11.7K
A standard box and whisker plot informs us about the spread of the data in a given sample. One can identify the minimum value, maximum value, first quartile value, second quartile or median value, and third quartile.
However, the box plot does not tell the reader about outliers - values that lie far from the center of the data. We can modify the standard box and whisker plot to identify the outliers and visualize the actual spread of the data in a sample.
Initially, we calculate the adjusted...
11.7K

You might also read

Related Articles

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

Sort by
Same author

Performance of large language models as an information resource on functional hypothalamic amenorrhea for patients and healthcare professionals.

Frontiers in artificial intelligence·2026
Same author

Differences in overall survival for invasive epithelial ovarian cancer by race and ethnicity: results from the Ovarian Cancer Association Consortium.

British journal of cancer·2026
Same author

Sex, Not Age, Predicts Weight Loss Outcomes With Tirzepatide: A Retrospective Analysis.

Obesity (Silver Spring, Md.)·2026
Same author

United States Menopausal Hormone Therapy Usage Trends: An Observational Study.

Mayo Clinic proceedings·2026
Same author

A human-in-the-loop explanation framework for morphologically transparent AI predictions from whole-slide images.

NPJ digital medicine·2026
Same author

Multi‑scale immune and spatial profiling of sclerosing adenosis and surrounding breast tissue identifies an immune‑cold field phenotype associated with breast cancer risk.

Breast cancer research : BCR·2026
Same journal

The human claustrum supports cognitive networks for externally and internally driven task demands.

PLoS biology·2026
Same journal

Unusual decay: Recombination loss leads to splicing errors in green algae.

PLoS biology·2026
Same journal

Angptl5 restricts primitive hematopoiesis by promoting retinoic acid signaling in zebrafish.

PLoS biology·2026
Same journal

Engineered bipaternal mice reveal the consequences of life without a maternal genomic contribution.

PLoS biology·2026
Same journal

Multiple adhesion molecules act together in oligodendrocyte-mediated axonal selection and myelin formation.

PLoS biology·2026
Same journal

Splicing deficiency is driven by genomic erosion in non-recombining algal mating-type chromosomes.

PLoS biology·2026
See all related articles

Related Experiment Video

Updated: Mar 19, 2026

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

10.6K

From Static to Interactive: Transforming Data Visualization to Improve Transparency.

Tracey L Weissgerber1, Vesna D Garovic1, Marko Savic2

  • 1Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, United States of America.

Plos Biology
|June 23, 2016
PubMed
Summary
This summary is machine-generated.

Static figures in small sample size studies limit data exploration. Interactive graphics offer dynamic alternatives, transforming publications into explorable datasets and enhancing critical evaluation of research findings.

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

1.6K
Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

2.8K

Related Experiment Videos

Last Updated: Mar 19, 2026

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

10.6K
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

1.6K
Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma
09:17

Digital Spatial Profiling for Characterization of the Microenvironment in Adult-Type Diffusely Infiltrating Glioma

Published on: September 13, 2022

2.8K

Area of Science:

  • Biostatistics
  • Scientific Visualization
  • Data Science

Background:

  • Traditional data presentation in scientific publications relies on static figures and tables.
  • This format is often insufficient for critical evaluation, especially in small sample size studies.
  • There is a need for more dynamic and interactive methods for data exploration.

Purpose of the Study:

  • To introduce interactive graphics as a superior alternative to static figures for presenting data in scientific publications.
  • To demonstrate the potential of dynamic visualization tools for enhancing the exploration of empirical datasets from small sample size studies.
  • To promote the adoption of interactive graphics in scientific research.

Main Methods:

  • Development of a novel interactive line graph tool.
  • The tool is web-based, free, and accessible online.
  • The interactive graph allows for dynamic exploration of data points and trends.

Main Results:

  • The interactive line graph effectively demonstrates the concept of dynamic data visualization.
  • This approach allows for deeper exploration of empirical datasets compared to static graphics.
  • The tool serves as a proof-of-concept for more widespread use of interactive graphics.

Conclusions:

  • Interactive graphics can significantly improve data presentation and exploration in scientific publications.
  • Dynamic visualization tools are particularly beneficial for small sample size studies.
  • Widespread adoption of such tools can lead to more thorough evaluation of research data.