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Immersive Analytics: Theory and Research Agenda.

Richard Skarbez1, Nicholas F Polys1, J Todd Ogle1

  • 1Center for Human-Computer Interaction, Virginia Tech, Blacksburg, VA, United States.

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Summary
This summary is machine-generated.

Immersive analytics integrates big data, machine learning, and extended reality (XR) for enhanced decision-making. This paper proposes a framework to organize this emerging field and guide future research directions.

Keywords:
immersionimmersive analyticsknowledge generationsensemakingvirtual realityvisual analyticsvisualization

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Area of Science:

  • Computer Science
  • Data Science
  • Human-Computer Interaction

Background:

  • Advances in big data, machine learning, and extended reality (XR) technologies.
  • The nascent field of immersive analytics lacks a unifying research framework.
  • Current immersive analytics research is often ad hoc.

Purpose of the Study:

  • To propose a definition and organizing framework for immersive analytics research.
  • To identify key research areas and questions for the field's development.
  • To demonstrate the applicability of the proposed framework through case studies.

Main Methods:

  • Literature review and synthesis of interdisciplinary advancements.
  • Conceptual framework development for immersive analytics.
  • Presentation and analysis of three diverse case studies.

Main Results:

  • A formal definition and structured research agenda for immersive analytics.
  • Identification of critical research challenges and opportunities.
  • Demonstration of the framework's utility across varied applications.

Conclusions:

  • A foundational framework is essential for advancing immersive analytics.
  • The proposed framework provides direction for future research and development.
  • Immersive analytics holds significant potential for transforming analysis and decision-making.