Struggles and Strategies in Understanding Information Visualizations.

While the visualization community is increasingly aware that people often find visualizations difficult to understand, there is less information about what we need to do to create comprehensible visualizations. To help visualization creators and designers improve their visualizations, we need to better understand what kind of support people are looking for in their sensemaking process. Empirical studies are needed to tease apart the details of what makes the process of understanding difficult for visualization viewers. We conducted a qualitative study with 14 participants, observing them as they described how they were trying to make sense of 20 information visualizations. We identified the challenges participants faced throughout their sensemaking process and the strategies they employed to help themselves in overcoming the challenges. Our findings show how details and nuances within visualizations can impact comprehensibility and offer research suggestions to help us move toward more understandable visualizations.

Challenges and Opportunities in Data Visualization Education: A Call to Action.

This paper is a call to action for research and discussion on data visualization education. As visualization evolves and spreads through our professional and personal lives, we need to understand how to support and empower a broad and diverse community of learners in visualization. Data Visualization is a diverse and dynamic discipline that combines knowledge from different fields, is tailored to suit diverse audiences and contexts, and frequently incorporates tacit knowledge. This complex nature leads to a series of interrelated challenges for data visualization education. Driven by a lack of consolidated knowledge, overview, and orientation for visualization education, the 21 authors of this paper-educators and researchers in data visualization-identify and describe 19 challenges informed by our collective practical experience. We organize these challenges around seven themes People, Goals & Assessment, Environment, Motivation, Methods, Materials, and Change. Across these themes, we formulate 43 research questions to address these challenges. As part of our call to action, we then conclude with 5 cross-cutting opportunities and respective action items: embrace DIVERSITY+INCLUSION, build COMMUNITIES, conduct RESEARCH, act AGILE, and relish RESPONSIBILITY. We aim to inspire researchers, educators and learners to drive visualization education forward and discuss why, how, who and where we educate, as we learn to use visualization to address challenges across many scales and many domains in a rapidly changing world: viseducationchallenges.github.io.

Enthusiastic and Grounded, Avoidant and Cautious: Understanding Public Receptivity to Data and Visualizations.

Despite an abundance of open data initiatives aimed to inform and empower "general" audiences, we still know little about the ways people outside of traditional data analysis communities experience and engage with public data and visualizations. To investigate this gap, we present results from an in-depth qualitative interview study with 19 participants from diverse ethnic, occupational, and demographic backgrounds. Our findings characterize a set of lived experiences with open data and visualizations in the domain of energy consumption, production, and transmission. This work exposes information receptivity - an individual's transient state of willingness or openness to receive information -as a blind spot for the data visualization community, complementary to but distinct from previous notions of data visualization literacy and engagement. We observed four clusters of receptivity responses to data- and visualization-based rhetoric: Information-Avoidant, Data-Cautious, Data-Enthusiastic, and Domain-Grounded. Based on our findings, we highlight research opportunities for the visualization community. This exploratory work identifies the existence of diverse receptivity responses, highlighting the need to consider audiences with varying levels of openness to new information. Our findings also suggest new approaches for improving the accessibility and inclusivity of open data and visualization initiatives targeted at broad audiences. A free copy of this paper and all supplemental materials are available at https://OSF.IO/MPQ32.

Computerised clinical decision support system for the diagnosis of pulmonary thromboembolism: a preclinical pilot study.

BACKGROUND: Recommendations for the diagnosis of pulmonary embolism are available for healthcare providers. Yet, real practice data show existing gaps in the translation of evidence-based recommendations. This is a study to assess the effect of a computerised decision support system (CDSS) with an enhanced design based on best practices in content and reasoning representation for the diagnosis of pulmonary embolism. DESIGN: Randomised preclinical pilot study of paper-based clinical scenarios in the diagnosis of pulmonary embolism. Participants were clinicians (n=30) from three levels of experience: medical students, residents and physicians. Participants were randomised to two interventions for the diagnosis of pulmonary embolism: a didactic lecture versus a decision tree via a CDSS. The primary outcome of diagnostic pathway concordance (derived as a ratio of the number of correct diagnostic decision steps divided by the ideal number of diagnostic decision steps in diagnostic algorithms) was measured at baseline (five clinical scenarios) and after either intervention for a total of 10 clinical scenarios. RESULTS: The mean of diagnostic pathway concordance improved in both study groups: baseline mean=0.73, post mean for the CDSS group=0.90 (p<0.001, 95% CI 0.10-0.24); baseline mean=0.71, post mean for didactic lecture group=0.85 (p<0.001, 95% CI 0.07-0.2). There was no statistically significant difference between the two study groups or between the three levels of participants. INTERPRETATION: A computerised decision support system designed for both content and reasoning visualisation can improve clinicians' diagnostic decision-making.

KiriPhys: Exploring New Data Physicalization Opportunities.

We present KiriPhys, a new type of data physicalization based on kirigami, a traditional Japanese art form that uses paper-cutting. Within the kirigami possibilities, we investigate how different aspects of cutting patterns offer opportunities for mapping data to both independent and dependent physical variables. As a first step towards understanding the data physicalization opportunities in KiriPhys, we conducted a qualitative study in which 12 participants interacted with four KiriPhys examples. Our observations of how people interact with, understand, and respond to KiriPhys suggest that KiriPhys: 1) provides new opportunities for interactive, layered data exploration, 2) introduces elastic expansion as a new sensation that can reveal data, and 3) offers data mapping possibilities while providing a pleasurable experience that stimulates curiosity and engagement.

Embracing Disciplinary Diversity in Visualization.

Visualization is inherently diverse and is employed in countless domains to enable meaningful interactions with data. There is tremendous opportunity in embracing disciplinary diversity to widen the pool of contributions to visualization design, research, and practice. We describe a few examples of diverse approaches: scientific method, design studies, tool building, participatory research, and co-design with communities, data storytelling, and autographic design. We discuss opening the aperture, pushing back on what we, as a community, deem acceptable and rigorous, and what can be gained through greater inclusivity of approaches.

Perception! Immersion! Empowerment! Superpowers as Inspiration for Visualization.

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.

Communicating Patient Health Data: A Wicked Problem.

Designing patient-collected health data visualizations to support communicating patient data during clinical visits is a challenging problem due to the heterogeneity of the parties involved: patients, healthcare providers, and healthcare systems. Designers must ensure that all parties' needs are met. This complexity makes it challenging to find a definitive solution that can work for every individual. We have approached this research problem-communicating patient data during clinical visits-as a wicked problem. In this article, we outline how wicked problem characteristics apply to our research problem. We then describe the research methodologies we employed to explore the design space of individualized patient data visualization solutions. Lastly, we reflect on the insights and experiences we gained through this exploratory design process. We conclude with a call to action for researchers and visualization designers to consider patients' and healthcare providers' individualities when designing patient data visualizations.

Human-centred design processes for clinical decision support: A pulmonary embolism case study.

BACKGROUND: Clinical Decision Support Systems (CDSS) can make patient care more efficient, cost-effective, and guideline-concordant. Many are created by clinicians who understand the challenges, but may publish concepts before considering subtle but important design details. Human-Centred Design (HCD) approaches provide necessary methods ensuring solid CDSS design. This article highlights HCD approaches in a pulmonary embolism CDSS case study context. METHODS: This pulmonary embolism CDSS results from collaborative work between computer science, psychology, and medicine. HCD methods used include: evaluations of pre-clinical prototype recordings, iterative usability expert reviews with software refinement, formative usability testing, and (separately-published) clinical pilot study. RESULTS: HCD methods were instrumental in iteratively creating an easy to use and functionally-sound CDSS. Retrospective evaluations revealed that participants spent considerable time on items that were out of order from natural cognitive diagnostic workflows. Features missing between original and study version were noted, confusing interface elements reworked, and currently-active decision tree branches were visually emphasized. From iterative usability reviews, positioning of information within the decision tree was radically reworked, information separated into levels of support for different user groups, and supportive versus directive language issues addressed. Formative studies identified issues such as interface adjustments and hospital workflow integration. CONCLUSIONS: Human-centred design approaches provide methods for integrating the skills and knowledge of many disciplines, illustrated by example in this pulmonary embolism CDSS creation. Advantages of leveraging many design guidelines as well as revealing new design considerations that would otherwise have remained hidden are described. The findings reported here support future CDSS design through HCD inclusion.

PixelClipper: Supporting Public Engagement and Conversation About Visualizations.

In this article, we present PixelClipper, a tool built for facilitating data engagement events. PixelClipper supports conversations around visualizations in public settings through annotation and commenting capabilities. It is recognized that understanding data is important for an informed society. However, even when visualizations are available on the web, open data is not yet reaching all audiences. Public facilitated events centered around data visualizations may help bridge this gap. PixelClipper is designed to promote discussion and engagement with visualizations in public settings. It allows viewers to quickly and expressively extract visual clippings from visualizations and add comments to them. Ambient and facilitator displays attract attention by showing clippings. They function as entry points to the full visualizations while supporting deeper conversations about the visualizations and data. We describe the design goals of PixelClipper, share our experiences from deploying it, and discuss its future potential in supporting data visualization engagement events.

Design by Immersion: A Transdisciplinary Approach to Problem-Driven Visualizations.

While previous work exists on how to conduct and disseminate insights from problem-driven visualization projects and design studies, the literature does not address how to accomplish these goals in transdisciplinary teams in ways that advance all disciplines involved. In this paper we introduce and define a new methodological paradigm we call design by immersion, which provides an alternative perspective on problem-driven visualization work. Design by immersion embeds transdisciplinary experiences at the center of the visualization process by having visualization researchers participate in the work of the target domain (or domain experts participate in visualization research). Based on our own combined experiences of working on cross-disciplinary, problem-driven visualization projects, we present six case studies that expose the opportunities that design by immersion enables, including (1) exploring new domain-inspired visualization design spaces, (2) enriching domain understanding through personal experiences, and (3) building strong transdisciplinary relationships. Furthermore, we illustrate how the process of design by immersion opens up a diverse set of design activities that can be combined in different ways depending on the type of collaboration, project, and goals. Finally, we discuss the challenges and potential pitfalls of design by immersion.

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.

Broadening Intellectual Diversity in Visualization Research Papers.

Promoting a wider range of contribution types can facilitate healthy growth of the visualization community, while increasing the intellectual diversity of visualization research papers. In this paper, we discuss the importance of contribution types and summarize contribution types that can be meaningful in visualization research. We also propose several concrete next steps we can and should take to ensure a successful launch of the contribution types.

Exploration Strategies for Discovery of Interactivity in Visualizations.

We investigate how people discover the functionality of an interactive visualization that was designed for the general public. While interactive visualizations are increasingly available for public use, we still know little about how the general public discovers what they can do with these visualizations and what interactions are available. Developing a better understanding of this discovery process can help inform the design of visualizations for the general public, which in turn can help make data more accessible. To unpack this problem, we conducted a lab study in which participants were free to use their own methods to discover the functionality of a connected set of interactive visualizations of public energy data. We collected eye movement data and interaction logs as well as video and audio recordings. By analyzing this combined data, we extract exploration strategies that the participants employed to discover the functionality in these interactive visualizations. These exploration strategies illuminate possible design directions for improving the discoverability of a visualization's functionality.

Decal-Lenses: Interactive Lenses on Surfaces for Multivariate Visualization.

We present decal-lenses, a new interaction technique that extends the concept of magic lenses to augment and manage multivariate visualizations on arbitrary surfaces. Our object-space lenses follow the surface geometry and allow the user to change the point of view during data exploration while maintaining a spatial reference to positions where one or more lenses were placed. Each lens delimits specific regions of the surface where one or more attributes can be selected or combined. Similar to 2D lenses, the user interacts with our lenses in real-time, switching between different attributes within the lens context. The user can also visualize the surface data representations from the point of view of each lens by using local cameras. To place lenses on surfaces of intricate geometry, such as the human brain, we introduce the concept of support surfaces for designing interaction techniques. Support surfaces provide a way to place and interact with the lenses while avoiding holes and occluded regions during data exploration. We further extend decal-lenses to arbitrary regions using brushing and lassoing operations. We discuss the applicability of our technique and present several examples where our lenses can be useful to create a customized exploration of multivariate data on surfaces.

Does Local Structure Bias How a Crystal Nucleus Evolves?

The broad scientific and technological importance of crystallization has led to significant research probing and rationalizing crystal nucleation processes. Previous work has generally neglected the possibility of the molecular-level dynamics of individual crystal nuclei coupling to local structures. However, recent experimental work has conjectured that this can occur. Therefore, to address a deficiency in scientific understanding of crystallization, we have probed the nucleation of prototypical single and multicomponent crystals (specifically, ice and mixed gas hydrates). We establish that local structures can bias the evolution of nascent crystal phases on a nanosecond time scale by, for example, promoting the appearance or disappearance of specific crystal motifs and thus reveal a new facet of crystallization behavior. Moreover, we demonstrate structural biases are likely present during crystallization processes beyond ice and gas hydrate formation. Structurally biased dynamics are a lens for understanding existing computational and experimental results while pointing to future opportunities.

MyBrush: Brushing and Linking with Personal Agency.

We extend the popular brushing and linking technique by incorporating personal agency in the interaction. We map existing research related to brushing and linking into a design space that deconstructs the interaction technique into three components: source (what is being brushed), link (the expression of relationship between source and target), and target (what is revealed as related to the source). Using this design space, we created MyBrush, a unified interface that offers personal agency over brushing and linking by giving people the flexibility to configure the source, link, and target of multiple brushes. The results of three focus groups demonstrate that people with different backgrounds leveraged personal agency in different ways, including performing complex tasks and showing links explicitly. We reflect on these results, paving the way for future research on the role of personal agency in information visualization.

Assessing the Graphical Perception of Time and Speed on 2D+Time Trajectories.

We empirically evaluate the extent to which people perceive non-constant time and speed encoded on 2D paths. In our graphical perception study, we evaluate nine encodings from the literature for both straight and curved paths. Visualizing time and speed information is a challenge when the x and y axes already encode other data dimensions, for example when plotting a trip on a map. This is particularly true in disciplines such as time-geography and movement analytics that often require visualizing spatio-temporal trajectories. A common approach is to use 2D+time trajectories, which are 2D paths for which time is an additional dimension. However, there are currently no guidelines regarding how to represent time and speed on such paths. Our study results provide InfoVis designers with clear guidance regarding which encodings to use and which ones to avoid; in particular, we suggest using color value to encode speed and segment length to encode time whenever possible.

Active Reading of Visualizations.

We investigate whether the notion of active reading for text might be usefully applied to visualizations. Through a qualitative study we explored whether people apply observable active reading techniques when reading paper-based node-link visualizations. Participants used a range of physical actions while reading, and from these we synthesized an initial set of active reading techniques for visualizations. To learn more about the potential impact such techniques may have on visualization reading, we implemented support for one type of physical action from our observations (making freeform marks) in an interactive node-link visualization. Results from our quantitative study of this implementation show that interactive support for active reading techniques can improve the accuracy of performing low-level visualization tasks. Together, our studies suggest that the active reading space is ripe for research exploration within visualization and can lead to new interactions that make for a more flexible and effective visualization reading experience.