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

Manipulation and Analysis01:21

Manipulation and Analysis

337
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...
337
Introduction to Scalers01:21

Introduction to Scalers

2.7K
2.7K
Run Charts01:12

Run Charts

404
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...
404
Interpreting Run Charts01:25

Interpreting Run Charts

3.2K
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...
3.2K
Outliers and Influential Points01:08

Outliers and Influential Points

5.1K
An outlier is an observation of data that does not fit the rest of the data. It is sometimes called an extreme value. When you graph an outlier, it will appear not to fit the pattern of the graph. Some outliers are due to mistakes (for example, writing down 50 instead of 500), while others may indicate that something unusual is happening. Outliers are present far from the least squares line in the vertical direction. They have large "errors," where the "error" or residual is the...
5.1K
Statgraphics01:10

Statgraphics

485
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
485

You might also read

Related Articles

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

Sort by
Same author

FLUID: A Neural Operator-Based Framework for Learning Multi-Fidelity of Unstructured Data.

IEEE transactions on visualization and computer graphics·2026
Same author

VizGenie: Toward Self-Refining, Domain-Aware Workflows for Next-Generation Scientific Visualization.

IEEE transactions on visualization and computer graphics·2025
Same author

Stand-alone L5-S1 transdiscal screw fixation and direct foraminal decompression as a minimally invasive fusion method in high grade isthmic spondylolisthesis: technical note and case series.

Journal of spine surgery (Hong Kong)·2025
Same author

Current Trends and Future Directions of Statistical Methods in Medical Research: A Scientometric Analysis.

Journal of evaluation in clinical practice·2025
Same author

Navigating Uncertainty: Challenges in Visualizing Ensemble Data and Surrogate Models for Decision Systems.

IEEE computer graphics and applications·2025
Same author

Explorable INR: An Implicit Neural Representation for Ensemble Simulation Enabling Efficient Spatial and Parameter Exploration.

IEEE transactions on visualization and computer graphics·2025

Related Experiment Video

Updated: May 3, 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

9.5K

The top 10 challenges in extreme-scale visual analytics.

Pak Chung Wong1, Han-Wei Shen2, Christopher R Johnson3

  • 1Pacific Northwest National Laboratory.

IEEE Computer Graphics and Applications
|February 4, 2014
PubMed
Summary
This summary is machine-generated.

Scientists identify the top 10 challenges in extreme-scale visual analytics (VA), examining technical and social issues for scientific and nonscientific data applications.

More Related Videos

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
06:02

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

Published on: October 6, 2020

2.1K
A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

465

Related Experiment Videos

Last Updated: May 3, 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

9.5K
Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
06:02

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

Published on: October 6, 2020

2.1K
A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

465

Area of Science:

  • Computer Science
  • Data Science
  • Information Visualization

Background:

  • Extreme-scale data presents significant challenges for traditional visual analytics (VA) methods.
  • The increasing volume and complexity of data necessitate advanced VA techniques.
  • Both scientific and nonscientific domains face hurdles in leveraging VA effectively.

Purpose of the Study:

  • To identify and discuss the top 10 critical challenges in extreme-scale visual analytics.
  • To provide a comprehensive overview of technical and social perspectives on VA challenges.
  • To guide future research and development in the field of visual analytics.

Main Methods:

  • Expert discussion and consensus-building among scientists and researchers.
  • Analysis of current limitations and future needs in visual analytics applications.
  • Categorization of challenges from both technical and social viewpoints.

Main Results:

  • A curated list of the top 10 challenges in extreme-scale visual analytics.
  • Detailed examination of issues related to data scalability, computational resources, and algorithm design.
  • Exploration of human factors, ethical considerations, and user trust in VA systems.

Conclusions:

  • Addressing these challenges is crucial for advancing the capabilities of visual analytics.
  • Interdisciplinary collaboration is essential for overcoming the identified technical and social hurdles.
  • Future VA research must consider the broader societal impact and ethical implications of data analysis.