Flow Immersive: A Multiuser, Multidimensional, Multiplatform Interactive Covid-19 Data Visualization Tool

Area of Science:

• Data visualization
• Scientific communication
• Emerging technologies in education

Background:

• The Covid-19 pandemic led to widespread data visualization, but many lacked public appeal or understanding.
• Existing methods often failed to engage both laypeople and experts effectively.
• A need exists for innovative platforms to bridge the gap in scientific data comprehension.

Purpose of the Study:

• To introduce Flow Immersive, a novel data storytelling platform designed for enhanced public understanding of complex information.
• To demonstrate the integration of augmented reality (AR) and virtual reality (VR) within a multiplatform, multiuser publishing approach.
• To document the development, deployment, and user feedback of Flow Immersive, focusing on scalability and engagement.

Main Methods:

• Development of the Flow Immersive platform, integrating AR and VR technologies.
• Implementation of a multiplatform, multiuser publishing strategy.
• Collection and analysis of user feedback and engagement metrics.

Main Results:

• Flow's Covid-19 AR videos garnered 9 million views between October and December 2020.
• The platform was utilized in numerous professional presentations, indicating expert adoption.
• User feedback contributed to significant advancements in scalability and engagement levels.

Conclusions:

• Flow Immersive successfully engages diverse audiences, including laypeople and experts, in understanding complex scientific data.
• The integration of AR and VR technologies proves effective in increasing the appeal and comprehension of data visualizations.
• The platform's development journey highlights breakthroughs in achieving scalability and high user engagement for scientific communication.