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

Empirical Method to Interpret Standard Deviation01:09

Empirical Method to Interpret Standard Deviation

9.4K
The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The rule states that 68% of the data lies within one standard deviation from the mean, 95% lies within two standard deviations from the mean, and 99.7% lies within three standard deviations from the mean. Additionally, this rule is also called the 68-95-99.7 rule.
This rule is used widely in statistics to calculate the proportion of data values...
9.4K
Psychology as a Science01:13

Psychology as a Science

3.8K
Psychology, as a scientific discipline, aims to understand the mind and behavior through rigorous and systematic methods. The foundation of psychological research is evidence-based, relying heavily on the scientific method to derive and validate knowledge. This structured approach ensures that findings are reliable, valid, and applicable to broader contexts.
The scientific method in psychology involves six critical steps: making observations, formulating hypotheses, conducting tests, analyzing...
3.8K
Overview of Biostatistics in Health Sciences01:19

Overview of Biostatistics in Health Sciences

4.8K
Biostatistics involves the application of statistical techniques to scientific research in health-related fields, including biology and public health. These techniques are essential for designing studies, collecting data, and analyzing it to draw meaningful conclusions. Given the complexity of biological processes, particularly in studies involving human subjects, biostatistical methods are crucial for effectively organizing and interpreting data that might otherwise obscure underlying patterns...
4.8K
Statistical Package for the Social Sciences (SPSS)01:22

Statistical Package for the Social Sciences (SPSS)

1.2K
The Statistical Package for the Social Sciences, or SPSS, is a data management and analysis software suite. Developed by SPSS Inc. in 1968 and acquired by IBM in 2009, this tool was initially designed for social science data analysis, evolving to serve a wider range of disciplines. It was later renamed to Statistical Product and Service Solutions.
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
1.2K
Protein Complex Assembly02:41

Protein Complex Assembly

16.7K
Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
Many viruses self-assemble into a fully functional unit using the infected host cell to...
16.7K
Protein Complexes with Interchangeable Parts01:57

Protein Complexes with Interchangeable Parts

2.9K
Groups of proteins may form a complex where each protein in this complex has a different role in the overall execution of the complex’s function. Often some of the proteins in the complex can be replaced by a closely related variant to give a complex that contains many of the same components yet is functionally distinct.
The SCF ubiquitin ligase is a protein complex of five individual proteins. This complex attaches ubiquitin to other target proteins to mark them for degradation. In order...
2.9K

You might also read

Related Articles

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

Sort by
Same author

Mapping of PTP1B, TCPTP, SHP2, and Putative Substrates Reveals Novel Networks in Glomerular Podocytes.

Journal of cellular physiology·2026
Same author

SigTime: Learning and Visually Explaining Time Series Signatures.

IEEE transactions on visualization and computer graphics·2025
Same author

ClimateSOM: A Visual Analysis Workflow for Climate Ensemble Datasets.

IEEE transactions on visualization and computer graphics·2025
Same author

GSCache: Real-Time Radiance Caching for Volume Path Tracing Using 3D Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2025
Same author

Bridging Theory and Practice: A Multiphase Study of GenAI-Assisted Visualization Learning.

IEEE computer graphics and applications·2025
Same author

VISTA: A Visual Analytics Framework to Enhance Foundation Model-Generated Data Labels.

IEEE transactions on visualization and computer graphics·2025
Same journal

Two-phase Impulse Fluid on Particle Flow Map.

IEEE transactions on visualization and computer graphics·2026
Same journal

FGO-SLAM++: Real-time Geometry-Aware Gaussian SLAM with Continuous Opacity Field.

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

Related Experiment Video

Updated: Jan 20, 2026

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

609

Decoding a Complex Visualization in a Science Museum - An Empirical Study.

Joyce Ma, Kwan-Liu Ma, Jennifer Frazier

    IEEE Transactions on Visualization and Computer Graphics
    |August 20, 2019
    PubMed
    Summary
    This summary is machine-generated.

    Museum visitors took 43 seconds to decode visualizations for data exploration and 54 seconds for initial interpretation. Decoding occurred throughout their interaction, not just initially, highlighting design implications for informal science learning.

    More Related Videos

    Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry
    16:11

    Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry

    Published on: June 8, 2022

    2.7K
    Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
    06:33

    Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding

    Published on: October 11, 2018

    7.2K

    Related Experiment Videos

    Last Updated: Jan 20, 2026

    Decoding Natural Behavior from Neuroethological Embedding
    08:00

    Decoding Natural Behavior from Neuroethological Embedding

    Published on: October 3, 2025

    609
    Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry
    16:11

    Thermochemical Studies of NiII and ZnII Ternary Complexes Using Ion Mobility-Mass Spectrometry

    Published on: June 8, 2022

    2.7K
    Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding
    06:33

    Decomposing the Variance in Reading Comprehension to Reveal the Unique and Common Effects of Language and Decoding

    Published on: October 11, 2018

    7.2K

    Area of Science:

    • Human-Computer Interaction
    • Information Visualization
    • Informal Science Learning

    Background:

    • Museums increasingly use complex datasets and visualizations to engage visitors.
    • Understanding visitor interaction with data visualizations is crucial for effective informal science learning.

    Purpose of the Study:

    • To analyze the visitor decoding process of data visualizations in a museum setting.
    • To identify challenges and successes in mapping visual representations to data.
    • To provide design implications for visualizations in informal science learning venues.

    Main Methods:

    • Quantitative and qualitative analysis of visitor interactions with a complex dataset visualization.
    • Analysis of think-aloud data to understand the decoding process and identify issues.
    • Examination of the impact of multiple visual encodings on visitor decoding.

    Main Results:

    • Visitors required an average of 43 seconds to decode visualizations for pattern recognition.
    • An average of 54 seconds was needed for the first correct data interpretation.
    • Decoding was an ongoing process throughout the visitor's interaction with the visualization.
    • Issues in mapping visual elements to data referents were identified and analyzed.

    Conclusions:

    • The design of data visualizations significantly impacts visitor understanding and data interpretation.
    • Multiple visual encodings can both aid and impede the decoding process.
    • Insights inform the design and adaptation of visualizations for enhanced informal science learning experiences.