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 Run Charts01:25

Interpreting Run Charts

3.0K
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...
3.0K
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

260
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
260
Run Charts01:12

Run Charts

246
Run charts serve as an essential instrument for visualizing the performance of various processes over time, enabling the identification of trends and patterns crucial for quality improvement. These charts map out a series of data points chronologically, offering insights into the stability and efficiency of a process. A run chart's creation involves plotting data points on a graph, with the time intervals on the horizontal axis and the specific measurements on the vertical axis. For...
246
Survival Curves01:18

Survival Curves

601
Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
601
Response Surface Methodology01:16

Response Surface Methodology

567
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
567
Manipulation and Analysis01:21

Manipulation and Analysis

261
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
261

You might also read

Related Articles

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

Sort by
Same author

From Prediction to Insight: Visual Analytics for Understanding Compound Potency Models.

IEEE computer graphics and applications·2026
Same author

The Rise of AI-Generated Anime Avatars: Trends, Challenges, and Opportunities.

IEEE computer graphics and applications·2026
Same author

Leveraging Social Interaction: Stroke Rehabilitation Using Extended Reality.

IEEE computer graphics and applications·2026
Same author

An Immersive Virtual Reality Platform for First Aid and Emergency Training.

IEEE computer graphics and applications·2026
Same author

Hybridizing Expressive Rendering: Stroke-Based Rendering With Classic and Neural Methods.

IEEE computer graphics and applications·2026
Same author

Enhancing Pediatric Liver Transplant Therapy With Virtual Reality.

IEEE computer graphics and applications·2025
Same journal

Graph Pattern Matching based reassembly - 3DGPM.

IEEE computer graphics and applications·2026
Same journal

Making Learning Visible: Turning Public Engagement into Evidence for Academic Learning.

IEEE computer graphics and applications·2026
Same journal

LlymX: Multimodal LLM-Augmented XR for Context-Aware Information Access.

IEEE computer graphics and applications·2026
Same journal

Dynamic Gaussian-Based Digital Twin Reconstruction of Articulated Multi-Joint Objects.

IEEE computer graphics and applications·2026
Same journal

Steiner and Poisson Traversal Initializations: Initial Curve Optimization for Geometric Flow-based Surface Filling.

IEEE computer graphics and applications·2026
Same journal

Insight Into the Insight Toolkit.

IEEE computer graphics and applications·2026
See all related articles

Related Experiment Video

Updated: Jan 4, 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

10.5K

Understanding Failure Mode Effect Analysis Data Using Interactive Visual Analytics.

Rahul C Basole, Ahsan Qamar, Biswajyoti Pal

    IEEE Computer Graphics and Applications
    |November 13, 2019
    PubMed
    Summary
    This summary is machine-generated.

    DataHawk offers interactive visual analytics for systems engineering (SE), enhancing decision-making. This tool empowers engineers to explore Failure Mode and Effect Analysis (FMEA) data dynamically, improving design reviews and problem-solving.

    More Related Videos

    Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
    10:43

    Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

    Published on: June 10, 2021

    5.7K
    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
    10:44

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

    Published on: December 7, 2021

    2.6K

    Related Experiment Videos

    Last Updated: Jan 4, 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

    10.5K
    Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
    10:43

    Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

    Published on: June 10, 2021

    5.7K
    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
    10:44

    Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

    Published on: December 7, 2021

    2.6K

    Area of Science:

    • Systems Engineering
    • Data Visualization
    • Decision Support Systems

    Background:

    • Effective decision-making in complex systems engineering (SE) relies on actionable insights from visual analytics tools.
    • Current SE design reviews often use static data, limiting dynamic exploration and analysis.
    • A gap exists for interactive tools to address SE data complexity and support robust decision-making.

    Purpose of the Study:

    • To introduce DataHawk, an interactive visual analytics tool designed for systems engineering domains.
    • To address the limitations of static data analysis in design reviews, specifically within Failure Mode and Effect Analysis (FMEA).
    • To enable system engineers, designers, and managers to dynamically explore and analyze FMEA data.

    Main Methods:

    • Development of the DataHawk tool featuring interactive visual analytics capabilities.
    • Application of DataHawk to Failure Mode and Effect Analysis (FMEA) data.
    • Illustration of tool capabilities through a usage scenario in the automotive industry.

    Main Results:

    • DataHawk provides powerful exploration capabilities for FMEA data.
    • Users can probe data from multiple starting points and build questions dynamically.
    • The tool facilitates rapid triangulation of answers using multiple, interactive views.

    Conclusions:

    • DataHawk demonstrates versatility, scalability, and effectiveness for real-world engineering data.
    • Interactive visual analytics tools like DataHawk are crucial for improving SE decision-making.
    • The tool enhances the analysis of complex engineering data, such as FMEA, in practical applications.