We introduce DashSpace, a live collaborative immersive and ubiquitous analytics (IA/UA) platform designed for handheld and head-mounted Augmented/Extended Reality (AR/XR) implemented using WebXR and open standards. To bridge the gap between existing web-based visualizations and the immersive analytics setting, DashSpace supports visualizing both legacy D3 and Vega-Lite visualizations on 2D planes, and extruding Vega-Lite specifications into 2.5D. It also supports fully 3D visual representations using the Optomancy grammar. To facilitate authoring new visualizations in immersive XR, the platform provides a visual authoring mechanism where the user groups specification snippets to construct visualizations dynamically. The approach is fully persistent and collaborative, allowing multiple participants---whose presence is shown using 3D avatars and webcam feeds---to interact with the shared space synchronously, both co-located and remotely. We present three examples of DashSpace in action: immersive data analysis in 3D space, synchronous collaboration, and immersive data presentations.

We propose the notion of attention-aware visualizations (AAVs) that track the user's perception of a visual representation over time and feed this information back to the visualization. Such context awareness is particularly useful for ubiquitous and immersive analytics where knowing which embedded visualizations the user is looking at can be used to make visualizations react appropriately to the user's attention: for example, by highlighting data the user has not yet seen. We can separate the approach into three components: (1) measuring the user's gaze on a visualization and its parts; (2) tracking the user's attention over time; and (3) reactively modifying the visual representation based on the current attention metric. In this paper, we present two separate implementations of AAV: a 2D data-agnostic method for web-based visualizations that can use an embodied eyetracker to capture the user's gaze, and a 3D data-aware one that uses the stencil buffer to track the visibility of each individual mark in a visualization. Both methods provide similar mechanisms for accumulating attention over time and changing the appearance of marks in response. We also present results from a qualitative evaluation studying visual feedback and triggering mechanisms for capturing and revisualizing attention.

Consumer-level XR hardware now enables immersive spatial computing, yet most knowledge work remains confined to traditional 2D desktop environments. These worlds exist in isolation: writing emails or editing presentations favors desktop interfaces, while viewing 3D simulations or architectural models benefits from immersive environments. We address this fragmentation by combining spatial hypermedia, shareable dynamic media, and cross-reality computing to provide (1) composability of heterogeneous content and of nested information spaces through spatial transclusion, (2) pervasive cooperation across heterogeneous devices and platforms, and (3) congruent spatial representations despite underlying environmental differences. Our implementation, the Spatialstrates platform, embodies these principles using standard web technologies to bridge 2D desktop and 3D immersive environments. Through four scenarios---collaborative brainstorming, architectural design, molecular science visualization, and immersive analytics---we demonstrate how Spatialstrates enables collaboration between desktop 2D and immersive 3D contexts, allowing users to select the most appropriate interface for each task while maintaining collaborative capabilities.

The advent of low-cost, accessible, and high-performance augmented reality (AR) has shed light on a situated form of analytics where in-situ visualizations embedded in the real world can facilitate sensemaking based on the user's physical location. In this work, we identify prior literature in this emerging field with a focus on situated analytics. After collecting 47 relevant situated analytics systems, we classify them using a taxonomy of three dimensions: situating triggers, view situatedness, and data depiction. We then identify four archetypical patterns in our classification using an ensemble cluster analysis. We also assess the level which these systems support the sensemaking process. Finally, we discuss insights and design guidelines that we learned from our analysis.

What if magic could be used as an effective metaphor to perform data visualization and analysis using speech and gestures while mobile and on-the-go? In this paper, we introduce Wizualization, a visual analytics system for eXtended Reality (XR) that enables an analyst to author and interact with visualizations using such a magic system through gestures, speech commands, and touch interaction. Wizualization is a rendering system for current XR headsets that comprises several components: a cross-device (or Arcane Focuses) infrastructure for signalling and view control (Weave), a code notebook (Spellbook), and a grammar of graphics for XR (Optomancy). The system offers users three modes of input: gestures, spoken commands, and materials. We demonstrate Wizualization and its components using a motivating scenario on collaborative data analysis of pandemic data across time and space.

Native game engines have long been the 3-D development platform of choice for research in mixed and augmented reality. For this reason, they have also been adopted in many immersive visualization and immersive analytics systems and toolkits. However, with the rapid improvements of WebXR and related open technologies, this choice may not always be optimal for future visualization research. In this article, we investigate common assumptions about native game engines versus WebXR and find that while native engines still have an advantage in many areas, WebXR is rapidly catching up and is superior for many immersive analytics applications.