Advances in a variety of computing fields, including “big data,” machine learning, visualization, and augmented/mixed/virtual reality, have combined to give rise to the emerging field of immersive analytics, which investigates how these new technologies support analysis and decision making. Thus far, we feel that immersive analytics research has been somewhat ad hoc, possibly owing to the fact that there is not yet an organizing framework for immersive analytics research. In this paper, we address this lack by proposing a definition for immersive analytics and identifying some general research areas and specific research questions that will be important for the development of this field. We also present three case studies that, while all being examples of what we would consider immersive analytics, present different challenges, and opportunities. These serve to demonstrate the breadth of immersive analytics and illustrate how the framework proposed in this paper applies to practical research.
- Date of publication:
- September 10, 2019
- Frontiers Robotics and AI
- Publication note:
Richard Skarbez, Nicholas F. Polys, J. Todd Ogle, Chris North, Doug A. Bowman: Immersive Analytics: Theory and Research Agenda. Frontiers Robotics AI 6: 82 (2019)