Immersive experiences are increasingly used to communicate environmental impacts. Such experiences could be useful in raising engagement and knowledge of the general public regarding greenhouse gas (GHG) emissions. However, it is not clear if increasing the degree of gamification or enacted interactions in such immersive experiences could increase the memorability of GHG emissions data. To answer this question, we designed a virtual reality experience allowing people to explore GHG emissions of daily actions with various degrees of enacted and gamified interactions. We conducted a controlled and pre-registered study with 63 participants to understand how quiz-based gamification and enactment could influence GHG emissions memorability, intrinsic motivation and flow. We found evidence for our immersive design to increase general public knowledge about GHG emissions, whatever the condition. However, we found no strong evidence for an effect of enactment on GHG emissions memorability, while we found slight evidence for a small positive effect of quiz-based gamification. Moreover, we showed a positive effect of enactment on flow and intrinsic motivation. This study contributes to the understanding of how immersive visualizations can be optimized for climate education, highlighting the nuanced roles of gamification and enactment in shaping user engagement and knowledge gains. Supplementary material available at https://osf.io/48pnr.

Understanding the difference between small and big values spanning over several orders of magnitude can be difficult. In this demo, we introduce a proof of concept named AR Data Ribbons, an augmented reality visualization scaled so that even smaller values are visible but requiring people to unroll the biggest values of a bar chart going beyond its frame. While the smallest values appear as classic bars on a 2D canvas, participants are invited to pick up a roll handle and to unroll ribbons representing the biggest values of the dataset. Ribbons are then unfolded in the space surrounding the participant until reaching the length corresponding to the data value. We hope our design could lead to a greater engagement, creative ribbon output patterns and better data understanding.

Data videos combine visualization, animation, narration, and often background music to tell stories with data. While music is widely believed to enhance emotion and persuasion, its impact in data videos remains unexplored. We conducted a preregistered between-subjects experiment comparing six widely-viewed data videos with or without background music. Using Bayesian modeling and thematic analysis, we did not observe consistent measurable effects of background music on persuasion, engagement, or information recall. Qualitative responses revealed a more nuanced picture: some participants described the music as distracting or mismatched, while others reported that it enhanced enjoyment, supported focus, or strengthened emotional resonance when well aligned with the video’s tone. These findings suggest that the influence of background music in data videos is highly context-dependent, shaped by genre, familiarity, and its alignment with visual–narrative structure. We discuss possible reasons for the limited measurable effects observed in real-world videos and outline opportunities for future work on purpose-designed, incidental, or adaptive music for data-driven storytelling.

Augmented reality (AR) has increasingly been used to communicate environmental impacts, offering greater engagement than conventional displays. However, its effect on message credibility-how much people believe in the content of the communication-remains unclear. In a preregistered study, we compared the perceived credibility of environmental information presented via visualizations on an AR headset or a desktop display. We created display-specific visual encodings (3D concrete for AR, 2D bar charts for desktop) and added two control conditions to cross display and encoding. We found no difference in message credibility between AR and desktop, though concrete AR was rated most engaging. Supplementary material is available at https://osf.io/n4p5c/.

International audience

“Cultural Windows” is a research initiative aimed at enhancing cross-cultural understanding through immersive extended reality (XR) experiences. The project deploys AR and VR platforms to allow users to explore diverse living spaces, bridging the gap between preconceived notions and the actual appearance of these spaces. By using 3D scanning to create accurate models of culturally significant objects and integrating them into immersive systems, the project provides insights into the use of immersive technologies in cultural education, promoting engagement with global living designs.

This paper explores a novel approach to communicating plausible space-based temporal variability of travel durations. Digital maps most often only convey single numerical values as the estimated duration for a path and this piece of information does not account for the multiple scenarios hidden behind this point estimate, nor for the temporal uncertainty along the route (e.g., the likelihood of being slowed down at an intersection). We explore conveying this uncertainty by animating hypothetical trips onto maps in the form of moving dots along one or more paths. We conducted a study with 16 participants and observed that they were able to correctly extract and infer simple information from our uncertainty visualizations but that identifying moving dots' changes in speed is a more complex task. We discuss design challenges and implications for future visualizations of space-based temporal uncertainty.

Aparticipatory data physicalization, or PDP, is a physical visualization that allows people to physically participate in the creation of the visualization, by directly encoding their data. PDPs offer a way to engage a community with data of personal relevance that otherwise would be intangible. However, their design space has only begun to be explored, and most prior work shows relatively simple encoding rules. Therefore, we present a design exploration of different ways of faceting contributed data: by week, day, or person. Specifically, we designed Edo, a PDP that allows a small community to contribute their data to a physical visualization showing the climate impact of their dietary choices. In this pictorial, we elaborate on the design process of Edo and reflect on the findings of a three-week deployment of different layouts of Edo. Fabrication instructions and data are available under CC-BY 4.0 at osf.io/q5fr6.

Making time estimates, such as how long a given task might take, frequently leads to inaccurate predictions because of an optimistic bias. Previous attempts to alleviate this bias, including decomposing the task into smaller components and listing potential surprises, have not shown any major improvement. This article builds on the premise that these procedures may have failed because they involve compound probabilities and mixture distributions which are difficult to compute in one’s head. We hypothesize that predictive visualizations of such distributions would facilitate the estimation of task durations. We conducted a crowdsourced study in which 145 participants provided different estimates of overall and sub-task durations and we used these to generate predictive visualizations of the resulting mixture distributions. We compared participants’ initial estimates with their updated ones and found compelling evidence that predictive visualizations encourage less optimistic estimates.

Abstract Analysing data from experiments is a complex, multi‐step process, often with multiple defensible choices available at each step. While analysts often report a single analysis without documenting how it was chosen, this can cause serious transparency and methodological issues. To make the sensitivity of analysis results to analytical choices transparent, some statisticians and methodologists advocate the use of ‘multiverse analysis’: reporting the full range of outcomes that result from all combinations of defensible analytic choices. Summarizing this combinatorial explosion of statistical results presents unique challenges; several approaches to visualizing the output of multiverse analyses have been proposed across a variety of fields (e.g. psychology, statistics, economics, neuroscience). In this article, we (1) introduce a consistent conceptual framework and terminology for multiverse analyses that can be applied across fields; (2) identify the tasks researchers try to accomplish when visualizing multiverse analyses and (3) classify multiverse visualizations into ‘archetypes’, assessing how well each archetype supports each task. Our work sets a foundation for subsequent research on developing visualization tools and techniques to support multiverse analysis and its reporting.

Capturing content of fabrication activities is the first step for producing knowledge resources and an integral part of maker culture. As a secondary task, it conflicts though with the fabrication activity, and thus it is often forgotten and knowledge resources end up incomplete. In this article, we investigate different dimensions of content capture for knowledge resources in fabrication workshops. Based on past work in this area, we first propose a framework through which we identify two research directions to investigate. From these, we derive three dimensions to explore in more depth: The number of capturing devices, their feature variety and the degree of automation of each feature. We then explore the design space resulting from these three dimensions with the help of a design concept and an online survey study (N=66). Results show (1) a variety of needs and preferences justifying feature variety and multiplicity, (2) challenges in defining the right degree of manual and automatic control, and (3) the socio-technical impact of cameras in a shared space regarding privacy and ethics. We conclude with discussions on the benefits and vulnerabilities of equipping fabrication workshop with distributed camera-based capturing devices and offer opportunities for design.

When showing data about people, visualization designers and data journalists often use design strategies that presumably help the audience relate to those people. The term anthropographics has been recently coined to refer to this practice and the resulting visualizations. Anthropographics is a rich and growing area, but the work so far has remained scattered. Despite preliminary empirical work and a few web essays written by practitioners, there is a lack of clear language for thinking about and communicating about anthropographics. We address this gap by introducing a conceptual framework and a design space for anthropographics. Our design space consists of seven elementary design dimensions that can be reasonably hypothesized to have some effect on prosocial feelings or behavior. It extends a previous design space and is informed by an analysis of 105 visualizations collected from newspapers, websites, and research articles. We use our conceptual framework and design space to discuss trade-offs, common design strategies, as well as future opportunities for design and research in the area of anthropographics.

We explore how the lens of fictional superpowers can help characterize how visualizations empower people and provide inspiration for new visualization systems. Researchers and practitioners often tout visualizations' ability to "make the invisible visible" and to "enhance cognitive abilities." Meanwhile superhero comics and other modern fiction often depict characters with similarly fantastic abilities that allow them to see and interpret the world in ways that transcend traditional human perception. We investigate the intersection of these domains, and show how the language of superpowers can be used to characterize existing visualization systems and suggest opportunities for new and empowering ones. We introduce two frameworks: The first characterizes seven underlying mechanisms that form the basis for a variety of visual superpowers portrayed in fiction. The second identifies seven ways in which visualization tools and interfaces can instill a sense of empowerment in the people who use them. Building on these observations, we illustrate a diverse set of "visualization superpowers" and highlight opportunities for the visualization community to create new systems and interactions that empower new experiences with data Material and illustrations are available under CC-BY 4.0 at osf.io/8yhfz.

Visualizations designed to make readers compassionate with the persons whose data is represented have been called anthropographics and are commonly employed by practitioners. Empirical studies have recently examined whether anthropographics indeed promote empathy, compassion, or the likelihood of prosocial behavior, but findings have been inconclusive so far. This work contributes a detailed overview of past experiments, and two new experiments that use large samples and a combination of design strategies to maximize the possibility of finding an effect. We tested an information-rich anthropographic against a simple bar chart, asking participants to allocate hypothetical money in a crowdsourcing study. We found that the anthropographic had, at best, a small effect on money allocation. Such a small effect may be relevant for large-scale donation campaigns, but the large sample sizes required to observe an effect and the noise involved in measuring it make it very difficult to study in more depth. Data and code are available at https://osf.io/xqae2/.

Abstract Physical representations of data offer physical and spatial ways of looking at, navigating, and interacting with data. While digital fabrication has facilitated the creation of objects with data‐driven geometry, rendering data as a physically fabricated object is still a daunting leap for many physicalization designers. Rendering in the scope of this research refers to the back‐and‐forth process from digital design to digital fabrication and its specific challenges. We developed a corpus of example data physicalizations from research literature and physicalization practice. This survey then unpacks the “rendering” phase of the extended InfoVis pipeline in greater detail through these examples, with the aim of identifying ways that researchers, artists, and industry practitioners “render” physicalizations using digital design and fabrication tools.

While surgical videos are valuable support material for activities around surgery, their summarization demands great amounts of time from surgeons, resulting in the production of very few videos. We study the practices involving surgical video to motivate and inform the future design of tools for their summarization. Through interviews and observations in a field study, we find that (1) video summaries provide an important support for surgery, being used for self-improvement, education, discussing cases, scientific research, patient communication and as legal resources; (2) video summarization follows a process hindered by the loss of knowledge that originates during recording; and, (3) surgeons develop ad-hoc coordination strategies which involve using the video itself for articulation work, making it both the field of work and coordination artifact. We discuss ways in which tools can facilitate capturing knowledge during live action using these strategies.

We present explorable multiverse analysis reports, a new approach to statistical reporting where readers of research papers can explore alternative analysis options by interacting with the paper itself. This approach draws from two recent ideas: i) multiverse analysis, a philosophy of statistical reporting where paper authors report the outcomes of many different statistical analyses in order to show how fragile or robust their findings are; and ii) explorable explanations, narratives that can be read as normal explanations but where the reader can also become active by dynamically changing some elements of the explanation. Based on five examples and a design space analysis, we show how combining those two ideas can complement existing reporting approaches and constitute a step towards more transparent research papers.

Wall displays support people in interacting with large information spaces in two ways: On the one hand, the physical space in front of such displays enables them to navigate information spaces physically. On the other hand, the visual overview of the information space on the display may promote the formation of spatial memory; from studies of desktop computers we know this can boost performance. However, it remains unclear how the benefits of locomotion and overviews relate and whether one is more important than the other. We study this question through a wall display adaptation of the classic Data Mountain system to separate the effects of locomotion and visual overview. Our findings suggest that overview improves recall and that the combination of overview and locomotion outperforms all other combinations of factors.

The concept of power pose originates from a Psychology study from 2010 which suggested that holding an expansive pose can change hormone levels and increase risk-taking behavior. Follow-up experiments suggested that expansive poses incidentally imposed by the design of an environment lead to more dishonest behaviors. While multiple replication attempts of the 2010 study failed, the follow-up experiments on incidental postures have so far not been replicated. As UI design in HCI can incidentally lead to expansive body postures, we attempted two conceptual replications: we first asked 44 participants to tap areas on a wall-sized display and measured their self-reported sense of power; we then asked 80 participants to play a game on a large touch-screen and measured risk-taking. Based on Bayesian analyses we find that incidental power poses had little to no effect on our measures but could cause physical discomfort. We conclude by discussing our findings in the context of theory-driven research in HCI.

We provide a reappraisal of Tal and Wansink's study "Blinded with Science", where seemingly trivial charts were shown to increase belief in drug efficacy, presumably because charts are associated with science. Through a series of four replications conducted on two crowdsourcing platforms, we investigate an alternative explanation, namely, that the charts allowed participants to better assess the drug's efficacy. Considered together, our experiments suggest that the chart seems to have indeed promoted understanding, although the effect is likely very small. Meanwhile, we were unable to replicate the original study's findings, as text with chart appeared to be no more persuasive - and sometimes less persuasive - than text alone. This suggests that the effect may not be as robust as claimed and may need specific conditions to be reproduced. Regardless, within our experimental settings and considering our study as a whole (), the chart's contribution to understanding was clearly larger than its contribution to persuasion.

In this pictorial, we present a method to facilitate hands-on physicalization processes during workshops. Data physicalization -- encoding data in physical artefacts -- allows for new ways to represent and communicate data and, as a process, can make the principles of data representation more "graspable". In order to (1) engage different research communities to discuss data physicalization from a social and technology point of view, (2) promote data-driven prototyping, and (3) teach physicalization as a creative process in educational settings we have run hands-on data physicalization workshops within Human Computer Interaction, Information visualization and Design communities. Based on these workshops, we identified three main pitfalls that can cause participants to get stuck in the data preparation, ideation and construction phases. To address these, we designed a workshop to facilitate a rapid engagement in physicalization activities. Testing this method as part of another physicalization workshop shows its potential for participant engagement, prototyping and design reflection.

Physical data representations, or data physicalizations, are a promising new medium to represent and communicate data. Previous work mostly studied passive physicalizations which require humans to perform all interactions manually. Dynamic shape-changing displays address this limitation and facilitate data exploration tasks such as sorting, navigating in data sets which exceed the fixed size of a given physical display, or preparing "views" to communicate insights about data. However, it is currently unclear how people approach and interact with such data representations. We ran an exploratory study to investigate how non-experts made use of a dynamic physical bar chart for an open-ended data exploration and presentation task. We asked 16 participants to explore a data set on European values and to prepare a short presentation of their insights using a physical display. We analyze: (1) users' body movements to understand how they approach and react to the physicalization, (2) their hand-gestures to understand how they interact with physical data, (3) system interactions to understand which subsets of the data they explored and which features they used in the process, and (4) strategies used to explore the data and present observations. We discuss the implications of our findings for the use of dynamic data physicalizations and avenues for future work.

We introduce embedded data representations, the use of visual and physical representations of data that are deeply integrated with the physical spaces, objects, and entities to which the data refers. Technologies like lightweight wireless displays, mixed reality hardware, and autonomous vehicles are making it increasingly easier to display data in-context. While researchers and artists have already begun to create embedded data representations, the benefits, trade-offs, and even the language necessary to describe and compare these approaches remain unexplored. In this paper, we formalize the notion of physical data referents - the real-world entities and spaces to which data corresponds - and examine the relationship between referents and the visual and physical representations of their data. We differentiate situated representations, which display data in proximity to data referents, and embedded representations, which display data so that it spatially coincides with data referents. Drawing on examples from visualization, ubiquitous computing, and art, we explore the role of spatial indirection, scale, and interaction for embedded representations. We also examine the tradeoffs between non-situated, situated, and embedded data displays, including both visualizations and physicalizations. Based on our observations, we identify a variety of design challenges for embedded data representation, and suggest opportunities for future research and applications.

Humans have represented data in many forms for thousands of years, yet the main sensory channel we use to perceive these representations today still remains largely exclusive to sight. Recent developments, such as advances in digital fabrication, microcontrollers, actuated tangibles, and shape-changing interfaces offer new opportunities to encode data in physical forms and have stimulated the emergence of 'Data Physicalization' as a research area.

Physical visualizations, or data physicalizations, encode data in attributes of physical shapes. Despite a considerable body of work on visual variables, "physical variables" remain poorly understood. One of them is physical size. A difficulty for solid elements is that "size" is ambiguous - it can refer to either length/diameter, surface, or volume. Thus, it is unclear for designers of physicalizations how to effectively encode quantities in physical size. To investigate, we ran an experiment where participants estimated ratios between quantities represented by solid bars and spheres. Our results suggest that solid bars are compared based on their length, consistent with previous findings for 2D and 3D bars on flat media. But for spheres, participants' estimates are rather proportional to their surface. Depending on the estimation method used, judgments are rather consistent across participants, thus the use of perceptually-optimized size scales seems possible. We conclude by discussing implications for the design of data physicalizations and the need for more empirical studies on physical variables.

Physical representations of data have existed for thousands of years. Yet it is now that advances in digital fabrication, actuated tangible interfaces, and shape-changing displays are spurring an emerging area of research that we call Data Physicalization. It aims to help people explore, understand, and communicate data using computer-supported physical data representations. We call these representations physicalizations, analogously to visualizations -- their purely visual counterpart. In this article, we go beyond the focused research questions addressed so far by delineating the research area, synthesizing its open challenges and laying out a research agenda.

Visualizations such as bar charts help users reason about data, but are mostly screen-based, rarely physical, and almost never physical and dynamic. This paper investigates the role of physically dynamic bar charts and evaluates new interactions for exploring and working with datasets rendered in dynamic physical form. To facilitate our exploration we constructed a 10x10 interactive bar chart and designed interactions that supported fundamental visualisation tasks, specifically; annotation, filtering, organization, and navigation. The interactions were evaluated in a user study with 17 participants. Our findings identify the preferred methods of working with the data for each task i.e. directly tapping rows to hide bars, highlight the strengths and limitations of working with physical data, and discuss the challenges of integrating the proposed interactions together into a larger data exploration system. In general, physical interactions were intuitive, informative, and enjoyable, paving the way for new explorations in physical data visualizations.

Physical visualizations come in increasingly diverse forms, and are used in domains including art and entertainment, business analytics, and scientific research. However, creating physical visualizations requires laborious craftsmanship and demands expertise in both data visualization and digital fabrication. We present three case studies that illustrate limitations of current visualization fabrication workflows. We then present MakerVis, a prototype tool that integrates the entire process of creating physical visualizations, from data filtering to physical fabrication. Design sessions with three end users demonstrate how tools such as MakerVis can dramatically lower the barriers to producing physical visualizations. Observations and interviews from these sessions highlighted future research areas, including customization support, using material properties to represent data variables, and allowing the reuse of physical data objects in new visualizations.

The accessibility of infovis authoring tools to a wide audience has been identified as a major research challenge. A key task in the authoring process is the development of visual mappings. While the infovis community has long been deeply interested in finding effective visual mappings, comparatively little attention has been placed on how people construct visual mappings. In this paper, we present the results of a study designed to shed light on how people transform data into visual representations. We asked people to create, update and explain their own information visualizations using only tangible building blocks. We learned that all participants, most of whom had little experience in visualization authoring, were readily able to create and talk about their own visualizations. Based on our observations, we discuss participants' actions during the development of their visual representations and during their analytic activities. We conclude by suggesting implications for tool design to enable broader support for infovis authoring.

Data sculptures are an increasingly popular form of physical visualization whose purposes are essentially artistic, communicative or educational. But can physical visualizations help carry out actual information visualization tasks? We present the first infovis study comparing physical to on-screen visualizations. We focus on 3D visualizations, as these are common among physical visualizations but known to be problematic on computers. Taking 3D bar charts as an example, we show that moving visualizations to the physical world can improve users' efficiency at information retrieval tasks. In contrast, augmenting on-screen visualizations with stereoscopic rendering alone or with prop-based manipulation was of limited help. The efficiency of physical visualizations seems to stem from features that are unique to physical objects, such as their ability to be touched and their perfect visual realism. These findings provide empirical motivation for current research on fast digital fabrication and self-reconfiguring interfaces.

We present an interaction model for beyond-desktop visualizations that combines the visualization reference model with the instrumental interaction paradigm. Beyond-desktop visualizations involve a wide range of emerging technologies such as wall-sized displays, 3D and shape-changing displays, touch and tangible input, and physical information visualizations. While these technologies allow for new forms of interaction, they are often studied in isolation. New conceptual models are needed to build a coherent picture of what has been done and what is possible. We describe a modified pipeline model where raw data is processed into a visualization and then rendered into the physical world. Users can explore or change data by directly manipulating visualizations or through the use of instruments. Interactions can also take place in the physical world outside the visualization system, such as when using locomotion to inspect a large scale visualization. Through case studies we illustrate how this model can be used to describe both conventional and unconventional interactive visualization systems, and compare different design alternatives.

We explore the use of customizable tangible remote controllers for interacting with wall-size displays. Such controllers are especially suited to visual exploration tasks where users need to move to see details of complex visualizations. In addition, we conducted a controlled user study suggesting that tangibles make it easier for users to focus on the visual display while they interact. We explain how to build such controllers using off-the-shelf touch tablets and describe a sample application that supports multiple dynamic queries.

We present Silicone iLluminated Active Peripherals (SLAP), a system of tangible, translucent widgets for use on multitouch tabletops. SLAP Widgets are cast from silicone or made of acrylic, and include sliders, knobs, keyboards, and buttons. They add tactile feedback to multi-touch tables, improving input accuracy. Using rear projection, SLAP Widgets can be relabeled dynamically, providing inexpensive, battery-free, and untethered augmentations. Furthermore, SLAP combines the flexibility of virtual objects with physical affordances. We evaluate how SLAP Widgets influence the user experience on tabletops compared to virtual controls. Empirical studies show that SLAPWidgets are easy to use and outperform virtual controls significantly in terms of accuracy and overall interaction time.

We present SLAPbook, an application using SLAP, translucent and tangible widgets for use on vision-based multi-touch tabletops in Single Display Groupware (SDG) environments. SLAP stands for Silicone ILluminated Active Peripherals and includes widgets such as sliders, knobs, keyboards, and buttons. The widgets and tactile feedback to multi-touch tables while simultaneously providing dynamic relabeling to tangible objects using the table's rear projection. SLAPbook provides multiple users the ability to add and edit content to a guestbook, browse other peoples' entries, and access personal data using a token-based personalization system. Interaction with the table takes place in the personal and public space so that users can make use of personal and shared controls to perform separate and coordinative actions.