Immersive Analytics: Theory and Research Agenda

Abstract

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.

Grand Challenges in Immersive Analytics

“…Alternatively, Hackathorn and Margolis [59] emphasise collaboration in their definition "to enhance collaborative decision support". A more recent approach by Skarbez et al [125] describes Immersive Analytics as "the science of analytical reasoning facilitated by immersive human-computer interfaces", situating it with respect to the knowledge generation loop [106]. • Survey: Over the past years, the field has produced an increasing number of publications, extensively summarised in a 2019 survey [51].…”

“…By overlaying a visual representation on an object or location associated with the data's source, known as a referent [140], users may be made aware of useful spatial relationships in a data set-all while keeping their hands free during industrial work or other mobile tasks. However, [125].…”

DeepCinema: Adding Depth with X3D Image-Based Rendering

“…One exciting future application will be the integration of depthenhanced IBR objects to Immersive Analytic Workspaces [Dwyer et al 2016] [Marriott et al 2018] [Skarbez et al 2019], such as GLEE [Dahshan et al 2019], where Cinema thumbnails are used to drive human-in-the-loop Machine Learning known as Semantic Interaction [Endert et al 2012] [Dowling et al 2018]. Semantic Interaction in 2D workspaces has shown benefits, especially in the visualization of ensembles.…”

Comparing Understanding and Memorization in Physicalization and VR Visualization

“…Nevertheless, Immersive Visualisation [1] has the potential to support spatial understanding and memory in similar ways as physical representations, allowing for vivid and increasingly realistic imagery and a feeling of presence. 'Immersive Analytics' is the "use of engaging embodied analysis tools to support data understanding and decision making" [3], and is often tied to immersive human-computer interfaces [10]. As a prior step to investigating the role of physically touch for understanding data representations, we decided to study whether there is a difference to experiencing the representation in physical 3D or as a 3D visualisation, i.e.…”