Immersive analytics turns the very space surrounding the user into a canvas for data analysis, supporting human cognitive abilities in myriad ways. We present the results of a design study, contextual inquiry, and longitudinal evaluation involving professional economists using a Virtual Reality (VR) system for multidimensional visualization to explore actual economic data. Results from our preregistered evaluation highlight the varied use of space depending on context (exploration vs. presentation), the organization of space to support work, and the impact of immersion on navigation and orientation in the 3D analysis space.

We introduce IATK, the Immersive Analytics Toolkit, a software package for Unity that allows interactive authoring and exploration of data visualisation in immersive environments. The design of IATK was informed by interdisciplinary expert-collaborations as well as visual analytics applications and iterative refinement over several years. IATK allows for easy assembly of visualisations through a grammar of graphics that a user can configure in a GUI-in addition to a dedicated visualisation API that supports the creation of novel immersive visualisation designs and interactions. IATK is designed with scalability in mind, allowing visualisation and fluid responsive interactions in the order of several million points at a usable frame rate. This paper outlines our design requirements, IATK's framework design and technical features, its user interface, as well as application examples.

In the past, several systems have been presented that enable users to view occluded points of interest using Augmented Reality X-ray visualizations. It is challenging to design a visualization that provides correct occlusions between occluder and occluded objects while maximizing legibility. We have previously published an Augmented Reality X-ray visualization that renders edges of the occluder region over the occluded region to facilitate correct occlusions while providing foreground context. While this approach is simple and works in a wide range of situations, it provides only minimal context of the occluder object. In this paper, we present the background, design, and implementation of our novel visualization technique that aims at providing users with richer context of the occluder object. While our previous visualization only employed one salient feature (edges) to determine which parts of the occluder to display, our novel visualization technique is an initial attempt to explore the design space of employing multiple salient features for this task. The prototype presented in this paper employs three additional salient features: hue, luminosity, and motion. We have conducted two evaluations with human participants to investigate the benefits and limitations of our prototype compared to our previous system. The first evaluation showed that although our novel visualization provides a richer context of the occluder object, it does not impede users to select objects in the occluded area; but, it also indicated problems in our prototype. In the second evaluation, we have investigated these problems through an online survey with systematically varied occluder and occluded scenes, focussing on the qualitative aspects of our visualizations. The results were encouraging, but pointed out that our novel visualization needs a higher level of adaptiveness.

We present Embodied Axes, a controller which supports selection operations for 3D imagery and data visualisations in Augmented Reality. The device is an embodied representation of a 3D data space -- each of its three orthogonal arms corresponds to a data axis or domain specific frame of reference. Each axis is composed of a pair of tangible, actuated range sliders for precise data selection, and rotary encoding knobs for additional parameter tuning or menu navigation. The motor actuated sliders support alignment to positions of significant values within the data, or coordination with other input: e.g., mid-air gestures in the data space, touch gestures on the surface below the data, or another Embodied Axes device supporting multi-user scenarios. We conducted expert enquiries in medical imaging which provided formative feedback on domain tasks and refinements to the design. Additionally, a controlled user study was performed and found that the Embodied Axes was overall more accurate than conventional tracked controllers for selection tasks.

This paper introduces GeoGate, an Augmented Reality tabletop system that extends the Space-Time Cube and utilizes a ring-shaped tangible user interface to explore correlations between entities in multiple location datasets. We demonstrate GeoGate in the context of the maritime domain, where operators seek to find geo-temporal associations between trajectories recorded from a global positioning system, and light data extracted from night time satellite images. GeoGate utilizes a tabletop system displaying a traditional 2D map in conjunction with a Microsoft Hololens to present a single view of the data with a novel Augmented Reality extension of the Space-Time Cube. To validate GeoGate, we present the results of a user study comparing GeoGate with the existing 2D approach used in a normal desktop environment. The outcomes of the user study show that GeoGate's approach reduces mistakes in the interpretation of the correlations between various datasets, while the qualitative results show that such a system is preferable for the majority of geo-temporal maritime tasks compared.