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Related Experiment Video

Updated: Jun 24, 2026

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

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Published on: August 26, 2018

An overview of two open interactive computing environments useful for data science education.

Robert Hoyt¹, Victoria Wangia-Anderson²

¹Pensacola, Virginia Commonwealth University Health System, Florida, USA.

|January 28, 2020

Summary

Open, collaborative data science platforms offer accessible tools for data science and informatics education. These free platforms support diverse analytics, benefiting students and researchers without prohibitive costs.

Keywords:

data interpretation statistical data mining data science

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Area of Science:

Data Science
Informatics Education

Background:

Traditional data science platforms can be costly and restrictive.
Need for accessible, collaborative tools in data science education.

Purpose of the Study:

Illustrate the utility of open collaborative data science platforms.
Demonstrate benefits for data science and informatics education.

Main Methods:

Outlined features of two distinct online data science platforms.
Highlighted integration with common data analysis programming languages.
Described platform specializations in data exploration vs. containerization/visualization.

Main Results:

Both platforms are open-source, free, and facilitate collaboration.
Platforms support visual, descriptive, and predictive analytics.
Demonstrated capability for diverse data analysis tasks.

Conclusions:

Affordable, open, collaborative platforms enhance data science education.
Ideal for teaching data science skills to informatics students.
Offer advantages over expensive, limited commercial alternatives.