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

Data Reporting and Recording01:24

Data Reporting and Recording

4.7K
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
4.7K
Data Collection by Observations01:08

Data Collection by Observations

12.1K
Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
12.1K
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

6.6K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
6.6K
Data Collection by Experiments01:13

Data Collection by Experiments

24.3K
Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...
24.3K
Interpreting Run Charts01:25

Interpreting Run Charts

105
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...
105
Overview of Minitab01:11

Overview of Minitab

145
Minitab is a statistical software package designed for data analysis. With its origins in the 1970s and development at Pennsylvania State University, Minitab has grown significantly in its capabilities and applications. It plays a crucial role in quality management projects, especially in Six Sigma initiatives, by offering tools for process improvement and statistical analysis. Minitab's significance lies in its user-friendly interface, making complex statistical analysis accessible to...
145

You might also read

Related Articles

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

Sort by
Same author

Refining the Definition for "Low Risk" in Pulmonary Arterial Hypertension: Time to Reduce Morbidity and Mortality.

JACC. Heart failure·2026
Same author

Intelligent Reasoning Cues: A Framework and Case Study of the Roles of AI Information in Complex Decisions.

Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference·2026
Same author

Mosaic Selections: Managing and Optimizing User Selections for Scalable Data Visualization Systems.

IEEE transactions on visualization and computer graphics·2025
Same author

EncQA: Benchmarking Vision-Language Models on Visual Encodings for Charts.

IEEE transactions on visualization and computer graphics·2025
Same author

Toward Softerware: Enabling Personalization of Interactive Data Representations for Users With Disabilities.

IEEE computer graphics and applications·2025
Same author

Sketching AI Concepts with Capabilities and Examples: AI Innovation in the Intensive Care Unit.

Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference·2025
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: Jul 12, 2025

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

10.2K

Dead or Alive: Continuous Data Profiling for Interactive Data Science.

Will Epperson, Vaishnavi Gorantla, Dominik Moritz

    IEEE Transactions on Visualization and Computer Graphics
    |October 30, 2023
    PubMed
    Summary
    This summary is machine-generated.

    Continuous data profiling with AutoProfiler streamlines analysis by providing live, interactive data summaries. This automation helps data scientists detect errors and discover insights more efficiently than manual methods.

    More Related Videos

    Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective
    13:57

    Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

    Published on: July 1, 2015

    12.5K
    Trajectory Data Analyses for Pedestrian Space-time Activity Study
    16:14

    Trajectory Data Analyses for Pedestrian Space-time Activity Study

    Published on: February 25, 2013

    13.6K

    Related Experiment Videos

    Last Updated: Jul 12, 2025

    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

    10.2K
    Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective
    13:57

    Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

    Published on: July 1, 2015

    12.5K
    Trajectory Data Analyses for Pedestrian Space-time Activity Study
    16:14

    Trajectory Data Analyses for Pedestrian Space-time Activity Study

    Published on: February 25, 2013

    13.6K

    Area of Science:

    • Data Science
    • Human-Computer Interaction
    • Software Engineering

    Background:

    • Manual data profiling is time-consuming, leading to infrequent analysis and potential missed insights.
    • Existing methods require analysts to write custom code for data examination after each transformation.

    Purpose of the Study:

    • To introduce continuous data profiling for immediate, interactive data summaries.
    • To evaluate the effectiveness of the AutoProfiler system in facilitating data analysis and insight discovery.

    Main Methods:

    • Developed AutoProfiler with features for automatic data distribution display, live updates, and code authoring.
    • Conducted a user study comparing 'live' and 'dead' (on-demand) update versions of AutoProfiler.
    • Performed a longitudinal case study with domain scientists using AutoProfiler.

    Main Results:

    • Both AutoProfiler versions significantly facilitated insight discovery, with 91% of insights generated by the tools.
    • Users found live updates intuitive for transformation verification; on-demand updates were valued for reviewing past visualizations.
    • AutoProfiler enabled domain scientists to find serendipitous insights through automatic, live data profiles.

    Conclusions:

    • Continuous data profiling, particularly with live updates, enhances data comprehension and accelerates the discovery of errors and insights.
    • AutoProfiler's automated code authoring supports follow-up analysis and documentation.
    • The findings inform the design of future automated data analysis support tools.