Representing Marginalized Populations: Challenges in Anthropographics

Anthropographics are human-shaped visualizations that have primarily been used within visualization research and data journalism to show humanitarian and demographic data. However, anthropographics have typically been produced by a small group of designers, researchers, and journalists, and most use homogeneous representations of marginalized populations-representations that might have problematic implications for how viewers perceive the people they represent. In this paper, we use a critical lens to examine anthropographic visualization practices in projects about marginalized populations. We present critiques that identify three potential challenges related to the use of anthropographics and highlight possible unintended consequences-namely (1) creating homogeneous depictions of marginalized populations, (2) treating marginalization as an inclusion criteria, and (3) insufficiently contextualizing datasets about marginalization. Finally, we highlight opportunities for anthropographics research, including the need to develop techniques for representing demographic differences between marginalized populations and for studies exploring other potential effects of anthropographics

Simultaneous Worlds: Supporting Fluid Exploration of Multiple Data Sets via Physical Models

We take the well-established use of physical scale models in architecture and identify new opportunities for using them to interactively visualize and examine multiple streams of geospatial data. Overlaying, comparing, or integrating visualizations of complementary data sets in the same physical space is often challenging given the constraints of various data types and the limited design space of possible visual encodings. Our vision of “simultaneous worlds” uses physical models as a substrate upon which visualizations of multiple data streams can be dynamically and concurrently integrated. To explore the potential of this concept, we created three design explorations that use an illuminated campus model to integrate visualizations about building energy use, climate, and movement paths on a university campus. We use a research through design approach, documenting how our interdisciplinary collaborations with domain experts, students, and architects informed our designs. Based on our observations, we characterize the benefits of models for 1) situating visualizations, 2) composing visualizations, and 3) manipulating and authoring visualizations. Our work highlights the potential of physical models to support embodied exploration of spatial and non-spatial visualizations through fluid interactions.Natural Sciences and Engineering Research Council (NSERC

Sharing Information from Personal Digital Notes using Word-Scale Visualizations

International audienceWe describe how small visualizations embedded in text (word-scale visualizations) can be used to share information from and in per- sonal notes. From our previous research, we learned that people see many opportunities for sharing personal notes, for example among a small social group. Yet, people reported that they were hesitant to share raw notes due to the notes’ often disorganized structure, haphazard writing style, or due to the fact that notes may contain a number of unrelated or irrelevant pieces of information. In this paper, we discuss how word-scale visualizations can be used in a collaborative personal visualization setting—to show abstracted information from a shared set of notes in the context of personal note- taking. In particular, we discuss potential kinds of data about notes that can be shared and motivate why sharing them may be helpful. Additionally, we provide two examples that illustrate the challenges and implications of using word-scale visualizations to share data in notes. The first example describes how notes in a shared notebook can be combined with private notes. The second example shows how data from public sources can be mixed with private comments to support sharing between notes on a common topic

FluencyAR: Augmented Reality Language Immersion

FluencyAR is an augmented reality second language learning tool centered around the concepts of language immersion and self-talk. For many second language learners, advancing into upper levels of fluency can be difficult without sufficient opportunities to practice. Traditional solutions of tutoring or finding exchange partners are often inconvenient or limiting. FluencyAR provides situational conversation practice in highly self-directed practice sessions that imitate environments where the target language is dominant. We utilize augmented reality to allow users to practice their target language with immediate feedback at any time, and from any location. Using ChatGPT and the physical space of the user, we can produce unique and challenging conversation prompts relative to a user’s surroundings, ensuring that sessions remain interesting.Natural Sciences and Engineering Research Council (NSERC)Natural Sciences and Engineering Research Council of Canada (NSERC) [RGPIN-2021-02492] and the Canada Research Chairs Program

FlavourFrame: Visualizing Tasting Experiences

We present FlavourFrame, a canvas-based app that helps tasters capture and visualize their perceptions during mindful tasting experiences. Taste perceptions are difficult to document because they are subjective, multisensory, and ephemeral; and everyday people have limited dedicated vocabulary to describe such experiences. Our customizable tool is designed to help novice and experienced tasters structure and record tasting experiences. FlavourFrame superimposes visual and text layers to personalize visual and word- based expression of flavour experience. Through autoethnographic reflections, we generated sample data and identified strengths and limitations of the prototype.Natural Sciences and Engineering Research Council (NSERC)University of Calgary Program for Undergraduate Research Experience (PURE), Natural Sciences and Engineering Research Council of Canada (NSERC) [RGPIN-2021-02492, RGPIN-2023-03533], and Canada Research Chairs Progra

Eliciting Multi-touch Selection Gestures for Interactive Data Graphics

International audienceWe report the results of a study in which we elicited selection gestures for multi-touch data graphics. The selection of data items is a common and extremely important form of interaction with data graphics, and serves as the basis for many other data interaction techniques. However, interactive charting tools for multi-touch displays typically only provide dedicated multi-touch gestures for single-point selection or zooming. Our study used gesture elicitation to explore a wider range of possible selection interactions for multi-touch data graphics. The results show a strong preference for simple, one-handed selection gestures. They also show that users tend to interact with chart axes and make figurative selection gestures outside the chart, rather than interact with the visual marks themselves. Finally, we found strong consensus around several unique selection gestures related to visual chart features

Data Changes Everything: Challenges and Opportunities in Data Visualization Design Handoff

Complex data visualization design projects often entail collaboration between people with different visualization-related skills. For example, many teams include both designers who create new visualization designs and developers who implement the resulting visualization software. We identify gaps between data characterization tools, visualization design tools, and development platforms that pose challenges for designer-developer teams working to create new data visualizations. While it is common for commercial interaction design tools to support collaboration between designers and developers, creating data visualizations poses several unique challenges that are not supported by current tools. In particular, visualization designers must characterize and build an understanding of the underlying data, then specify layouts, data encodings, and other data-driven parameters that will be robust across many different data values. In larger teams, designers must also clearly communicate these mappings and their dependencies to developers, clients, and other collaborators. We report observations and reflections from five large multidisciplinary visualization design projects and highlight six data-specific visualization challenges for design specification and handoff. These challenges include adapting to changing data, anticipating edge cases in data, understanding technical challenges, articulating data-dependent interactions, communicating data mappings, and preserving the integrity of data mappings across iterations. Based on these observations, we identify opportunities for future tools for prototyping, testing, and communicating data-driven designs, which might contribute to more successful and collaborative data visualization design.Comment: 11 pages, 11 figures. To appear in IEEE Transactions on Visualization and Computer Graphics. To be presented at the IEEE VIS 2019 Conferenc

Perceptual Affordances of Wall-Sized Displays for Visualization Applications: Color

International audienceWall-sized displays offer the opportunity to display very large information spaces. Most data representations can be scaled to wall size but display walls are not simply big desktop monitors. We do not yet know how the perceptual affordances of a wall, such as the wide viewing angles they cover, affect how data is perceived and comprehended. In this paper we call for more studies on the perception of data on wall-sized displays and discuss-with the example of color-several aspects of wall setups that we hypothesize will most affect the perception of this visual variable

An Exploratory Study of Word-Scale Graphics in Data-Rich Text Documents

International audienceWe contribute an investigation of the design and function of word-scale graphics and visualizations embedded in text documents. Word-scale graphics include both data-driven representations such as word-scale visualizations and sparklines, and non-data-driven visual marks. Their design, function, and use has so far received little research attention. We present the results of an open ended exploratory study with 9 graphic designers. The study resulted in a rich collection of different types of graphics, data provenance, and relationships between text, graphics, and data. Based on this corpus, we present a systematic overview of word-scale graphic designs, and examine how designers used them. We also discuss the designers’ goals in creating their graphics, and characterize how they used word-scale graphics to visualize data, add emphasis, and create alternative narratives. Building on these examples, we discuss implications for the design of authoring tools for word-scale graphics and visualizations, and explore how new authoring environments could make it easier for designers to integrate them into documents

You say Potato, I say Po-Data:Physical Template Tools for Authoring Visualizations

Data visualization authoring tools for the general public remains an ongoing challenge. Inspired by block-printing, we explore how visualization stamps as a physical tool for authoring visualizations could leverage both visual freedom and ease of repetition. We conducted two workshops where participants authored visualizations on paper using hand-carved stamps made from potatoes and sponges. The low-fidelity medium freed participants to test new stamp patterns and accept mistakes. From the created visualizations, we observed several unique traits and uses of block-printing tools for authoring visualizations, including: modularity of patterns; annotation guides; creation of multiple patterns from one stamp; and various techniques to apply data onto paper. We discuss issues around expressivity and effectiveness of block-printing stamps in authoring visualizations, and identify implications for the design and assembly of primitives in potential visualization stamp kits, as well as applications for future use in non-digital environments