Search research articles

Related Concept Videos

Statgraphics

Statgraphics

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,...

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

Quantum Computing and Visualization Research Challenges and Opportunities.

IEEE computer graphics and applications·2026

Same author

Visualizing the Chain of Thought in Large Language Models.

IEEE computer graphics and applications·2026

Same author

From 2D to 4D: a containerized workflow and browser to explore dynamic chromatin architecture.

BMC bioinformatics·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

How to Reject a VIS Paper, or Not?

IEEE computer graphics and applications·2025

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Dec 30, 2025

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Enabling Domain Expertise in Scientific Visualization With CinemaScience.

Terece L Turton, Divya Banesh, Trinity Overmyer

IEEE Computer Graphics and Applications

|January 17, 2020

Summary

This summary is machine-generated.

The CinemaScience project helps scientists use their expertise in visualization workflows. This approach enhances efficiency and drives scientific insight through better data analysis.

More Related Videos

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Published on: December 18, 2014

Related Experiment Videos

Last Updated: Dec 30, 2025

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Scalable Nanohelices for Predictive Studies and Enhanced 3D Visualization

Published on: November 12, 2014

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis

Published on: December 18, 2014

Area of Science:

Computer Science
Data Visualization
Scientific Computing

Background:

Scientific users have unique visualization needs due to their domain-specific expertise.
Traditional visualization tools may not fully leverage this expertise, creating challenges for researchers.
Integrating domain knowledge into visualization workflows is crucial for scientific discovery.

Purpose of the Study:

Introduce the CinemaScience project to a wider audience.
Demonstrate how CinemaScience facilitates efficient visualization workflows.
Showcase the integration of scientist expertise to drive scientific insight.

Main Methods:

The CinemaScience project provides a framework for interactive visualization.
It enables the incorporation of domain-specific knowledge into the visualization process.
Case studies illustrate the application of CinemaScience in scientific research.

Main Results:

CinemaScience enables more efficient and effective visualization workflows for scientific users.
The project successfully integrates expert domain knowledge into the visualization pipeline.
Demonstrated ability to drive deeper scientific insight through enhanced visualization techniques.

Conclusions:

CinemaScience offers a powerful solution for addressing the visualization challenges faced by scientific users.
By leveraging domain expertise, CinemaScience enhances the potential for scientific discovery.
The project promotes a more integrated approach between visualization researchers and domain scientists.