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

In- and Out-Groups01:31

In- and Out-Groups

39.1K
People all belong to a gender, race, age, and social economic group. These groups provide a powerful source of our identity and self-esteem (Tajfel & Turner, 1979) and serve as our in-groups. An in-group is a group that we identify with or see ourselves as belonging to.
39.1K
Self-Help Support Groups01:28

Self-Help Support Groups

59
Self-help support groups are voluntary, community-based organizations that provide a platform for individuals with shared concerns to exchange support, insights, and practical strategies for coping with life challenges. Typically led by group members or paraprofessionals, these groups form a cornerstone of mental health care, especially in reaching populations that are underserved by traditional healthcare systems.
Accessibility and Cost-Effectiveness
One of the primary strengths of self-help...
59
Self-Schemas02:16

Self-Schemas

31.2K
In general, a schema is a mental construct consisting of a cluster or collection of related concepts (Bartlett, 1932). There are many different types of schemata, and they all have one thing in common: schemata are a method of organizing information that allows the brain to work more efficiently. When a schema is activated, the brain makes immediate assumptions about the person or object being observed.
31.2K
Group Design02:01

Group Design

9.0K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
9.0K
Levels of Use of a GIS01:29

Levels of Use of a GIS

72
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
72
Eukaryotic Compartmentalization01:46

Eukaryotic Compartmentalization

156.7K
One of the distinguishing features of eukaryotic cells is that they contain membrane-bound organelles, such as the nucleus and mitochondria, that carry out specialized functions. Since biological membranes are only selectively permeable to solutes, they help create a compartment with controlled conditions inside an organelle. These microenvironments are tailored to the organelle's specific functions and help isolate them from the surrounding cytosol.
For example, lysosomes in the animal cells...
156.7K

You might also read

Related Articles

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

Sort by
Same author

Ambient Analytics: Calm Technology for Immersive Visualization and Sensemaking.

IEEE computer graphics and applications·2026
Same author

ISilDR: Isometric Seriation-Based Dimensionality Reduction for Visual Cluster Analysis.

IEEE transactions on visualization and computer graphics·2026
Same author

Integrating artificial intelligence tools in health research.

NPJ digital medicine·2026
Same author

A Large-Scale Quantitative Analysis of Avatars in VR and AR.

IEEE transactions on visualization and computer graphics·2026
Same author

Situated Brushing and Linking in Virtual and Augmented Reality.

IEEE transactions on visualization and computer graphics·2026
Same author

PerSiVal: deep neural networks for pervasive simulation of an activation-driven continuum-mechanical upper limb model.

Medical & biological engineering & computing·2026
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: Jul 26, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

342

ManuKnowVis: How to Support Different User Groups in Contextualizing and Leveraging Knowledge Repositories.

Joscha Eirich, Dominik Jackle, Michael Sedlmair

    IEEE Transactions on Visualization and Computer Graphics
    |June 19, 2023
    PubMed
    Summary
    This summary is machine-generated.

    ManuKnowVis bridges the gap between manufacturing knowledge providers and consumers. This tool enhances data-driven analysis by enabling knowledge sharing and improving efficiency in electric vehicle battery production.

    More Related Videos

    Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
    10:41

    Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms

    Published on: May 9, 2017

    9.3K
    Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
    09:20

    Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

    Published on: February 23, 2019

    8.8K

    Related Experiment Videos

    Last Updated: Jul 26, 2025

    Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
    05:47

    Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

    Published on: June 13, 2025

    342
    Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
    10:41

    Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms

    Published on: May 9, 2017

    9.3K
    Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
    09:20

    Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

    Published on: February 23, 2019

    8.8K

    Area of Science:

    • Manufacturing Process Analysis
    • Data Visualization
    • Knowledge Management

    Background:

    • Discrepancy exists between domain experts and data scientists in manufacturing data analysis.
    • Knowledge providers lack data analysis skills, while consumers lack domain expertise.
    • Bridging this gap is crucial for effective data-driven decision-making in manufacturing.

    Purpose of the Study:

    • To present ManuKnowVis, a tool designed to contextualize data from multiple knowledge repositories in electric vehicle battery module manufacturing.
    • To address the challenge of integrating domain knowledge with data-driven analysis in serial manufacturing processes.
    • To facilitate the creation and completion of manufacturing knowledge by connecting knowledge providers and consumers.

    Main Methods:

    • A multi-stakeholder design study involving iterative development of ManuKnowVis with knowledge providers and consumers from an automotive company.
    • Development of a multiple linked view tool enabling providers to describe and connect manufacturing entities.
    • Leveraging enhanced data by consumers for improved understanding and efficient data analysis.

    Main Results:

    • ManuKnowVis successfully bridges the gap between knowledge providers and consumers in manufacturing.
    • The tool enables providers to externalize their domain knowledge effectively.
    • Consumers can perform data-driven analyses more efficiently using the enhanced data.

    Conclusions:

    • ManuKnowVis significantly impacts the success of data-driven analyses from manufacturing data.
    • The tool facilitates knowledge externalization and improves data analysis efficiency for different stakeholder groups.
    • This approach enhances understanding of complex domain problems in manufacturing settings.