Glanceable Visualization: Studies of Data Comparison Performance on Smartwatches

Path-Based Design Model for Constructing and Exploring Alternative Visualisations

We present a path-based design model and system for designing and creating visualisations. Our model represents a systematic approach to constructing visual representations of data or concepts following a predefined sequence of steps. The initial step involves outlining the overall appearance of the visualisation by creating a skeleton structure, referred to as a flowpath. Subsequently, we specify objects, visual marks, properties, and appearance, storing them in a gene. Lastly, we map data onto the flowpath, ensuring suitable morphisms. Alternative designs are created by exchanging values in the gene. For example, designs that share similar traits, are created by making small incremental changes to the gene. Our design methodology fosters the generation of diverse creative concepts, space-filling visualisations, and traditional formats like bar charts, circular plots and pie charts. Through our implementation we showcase the model in action. As an example application, we integrate the output visualisations onto a smartwatch and visualisation dashboards. In this article we (1) introduce, define and explain the path model and discuss possibilities for its use, (2) present our implementation, results, and evaluation, and (3) demonstrate and evaluate an application of its use on a mobile watch.

User Experience of Visualizations in Motion: A Case Study and Design Considerations

We present a systematic review, an empirical study, and a first set of considerations for designing visualizations in motion, derived from a concrete scenario in which these visualizations were used to support a primary task. In practice, when viewers are confronted with embedded visualizations, they often have to focus on a primary task and can only quickly glance at a visualization showing rich, often dynamically updated, information. As such, the visualizations must be designed so as not to distract from the primary task, while at the same time being readable and useful for aiding the primary task. For example, in games, players who are engaged in a battle have to look at their enemies but also read the remaining health of their own game character from the health bar over their character's head. Many trade-ofts are possible in the design of embedded visualizations in such dynamic scenarios, which we explore in-depth in this paper with a focus on user experience. We use video games as an example of an application context with a rich existing set of visualizations in motion. We begin our work with a systematic review of in-game visualizations in motion. Next, we conduct an empirical user study to investigate how different embedded visualizations in motion designs impact user experience. We conclude with a set of considerations and trade-offs for designing visualizations in motion more broadly as derived from what we learned about video games. All supplemental materials of this paper are available at osf.io/3v8wm/.

Toward Guidelines for Designing Holistic Integrated Information Visualizations for Time-Critical Contexts: Systematic Review

BACKGROUND

With the extensive volume of information from various and diverse data sources, it is essential to present information in a way that allows for quick understanding and interpretation. This is particularly crucial in health care, where timely insights into a patient's condition can be lifesaving. Holistic visualizations that integrate multiple data variables into a single visual representation can enhance rapid situational awareness and support informed decision-making. However, despite the existence of numerous guidelines for different types of visualizations, this study reveals that there are currently no specific guidelines or principles for designing holistic integrated information visualizations that enable quick processing and comprehensive understanding of multidimensional data in time-critical contexts. Addressing this gap is essential for enhancing decision-making in time-critical scenarios across various domains, particularly in health care.

OBJECTIVE

This study aims to establish a theoretical foundation supporting the argument that holistic integrated visualizations are a distinct type of visualization for time-critical contexts and identify applicable design principles and guidelines that can be used to design for such cases.

METHODS

We systematically searched the literature for peer-reviewed research on visualization strategies, guidelines, and taxonomies. The literature selection followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The search was conducted across 6 databases: ACM Digital Library, Google Scholar, IEEE Xplore, PubMed, Scopus, and Web of Science. The search was conducted up to August 2024 using the terms ("visualisations" OR "visualizations") AND ("guidelines" OR "taxonomy" OR "taxonomies"), with studies restricted to the English language.

RESULTS

Of 936 papers, 46 (4.9%) were included in the final review. In total, 48% (22/46) related to providing a holistic understanding and overview of multidimensional data; 28% (13/46) focused on integrated presentation, that is, integrating or combining multidimensional data into a single visual representation; and 35% (16/46) pertained to time and designing for rapid information processing. In total, 65% (30/46) of the papers presented general information visualization or visual communication guidelines and principles. No specific guidelines or principles were found that addressed all the characteristics of holistic, integrated visualizations in time-critical contexts. A summary of the key guidelines and principles from the 46 papers was extracted, collated, and categorized into 60 guidelines that could aid in designing holistic integrated visualizations. These were grouped according to different characteristics identified in the systematic review (eg, gestalt principles, reduction, organization, abstraction, and task complexity) and further condensed into 5 main proposed guidelines.

CONCLUSIONS

Holistic integrated information visualizations in time-critical domains are a unique use case requiring a unique set of design guidelines. Our proposed 5 main guidelines, derived from existing design theories and guidelines, can serve as a starting point to enable both holistic and rapid processing of information, facilitating better-informed decisions in time-critical contexts.

Semi-Automatic Layout Adaptation for Responsive Multiple-View Visualization Design

Multiple-view (MV) visualizations have become ubiquitous for visual communication and exploratory data visualization. However, most existing MV visualizations are designed for the desktop, which can be unsuitable for the continuously evolving displays of varying screen sizes. In this article, we present a two-stage adaptation framework that supports the automated retargeting and semi-automated tailoring of a desktop MV visualization for rendering on devices with displays of varying sizes. First, we cast layout retargeting as an optimization problem and propose a simulated annealing technique that can automatically preserve the layout of multiple views. Second, we enable fine-tuning for the visual appearance of each view, using a rule-based auto configuration method complemented with an interactive interface for chart-oriented encoding adjustment. To demonstrate the feasibility and expressivity of our proposed approach, we present a gallery of MV visualizations that have been adapted from the desktop to small displays. We also report the result of a user study comparing visualizations generated using our approach with those by existing methods. The outcome indicates that the participants generally prefer visualizations generated using our approach and find them to be easier to use.

Assessing the Design of Interactive Radial Data Visualizations for Mobile Devices

The growing use of mobile devices in daily life has led to an increased demand for the display of large amounts of data. In response, radial visualizations have emerged as a popular type of visualization in mobile applications due to their visual appeal. However, previous research has highlighted issues with these visualizations, namely misinterpretation due to their column length and angles. This study aims to provide guidelines for designing interactive visualizations on mobile devices and new evaluation methods based on the results of an empirical study. The perception of four types of circular visualizations on mobile devices was assessed through user interaction. All four types of circular visualizations were found to be suitable for use within mobile activity tracking applications, with no statistically significant difference in responses by type of visualization or interaction. However, distinguishing characteristics of each visualization type were revealed depending on the category that is in focus (memorability, readability, understanding, enjoyment, and engagement). The research outcomes provide guidelines for designing interactive radial visualizations on mobile devices, enhance the user experience, and introduce new evaluation methods. The study's results have significant implications for the design of visualizations on mobile devices, particularly in activity tracking applications.

Visualization in Motion: A Research Agenda and Two Evaluations

We contribute a research agenda for visualization in motion and two experiments to understand how well viewers can read data from moving visualizations. We define visualizations in motion as visual data representations that are used in contexts that exhibit relative motion between a viewer and an entire visualization. Sports analytics, video games, wearable devices, or data physicalizations are example contexts that involve different types of relative motion between a viewer and a visualization. To analyze the opportunities and challenges for designing visualization in motion, we show example scenarios and outline a first research agenda. Motivated primarily by the prevalence of and opportunities for visualizations in sports and video games we started to investigate a small aspect of our research agenda: the impact of two important characteristics of motion-speed and trajectory on a stationary viewer's ability to read data from moving donut and bar charts. We found that increasing speed and trajectory complexity did negatively affect the accuracy of reading values from the charts and that bar charts were more negatively impacted. In practice, however, this impact was small: both charts were still read fairly accurately.

A Participatory Design Approach to Develop Visualization of Wearable Actigraphy Data for Health Care Professionals: Case Study in Qatar

Background

Several tools have been developed for health care professionals to monitor the physical activity of their patients, but most of these tools have been considering only the needs of users in North American and European countries and applicable for only specific analytic tasks. To our knowledge, no research study has utilized the participatory design (PD) approach in the Middle East region to develop such tools, involving all the stakeholders in the product development phases, and no clear use cases have been derived from such studies that could serve future development in the field.

Objective

This study aims to develop an interactive visualization tool (ActiVis) to support local health care professionals in monitoring the physical activity of their patients measured through wearable sensors, with the overall objective of improving the health of the Qatari population.

Methods

We used PD and user-centered design methodologies to develop ActiVis, including persona development, brainwriting, and heuristic walkthrough as part of user evaluation workshops; and use cases, heuristic walkthrough, interface walkthrough, and survey as part of expert evaluation sessions.

Results

We derived and validated 6 data analysis use cases targeted at specific health care professionals from a collaborative design workshop and an expert user study. These use cases led to improving the design of the ActiVis tool to support the monitoring of patients’ physical activity by nurses and family doctors. The ActiVis research prototype (RP) compared favorably with the Fitbit Dashboard, showing the importance of design tools specific to end users’ needs rather than relying on repurposing existing tools designed for other types of users. The use cases we derived happen to be culturally agnostic, despite our assumption that the local Muslim and Arabic culture could impact the design of such visualization tools. At last, taking a step back, we reflect on running collaborative design sessions in a multicultural environment and oil-based economy.

Conclusions

Beyond the development of the ActiVis tool, this study can serve other visualization and human–computer interaction designers in the region to prepare their design projects and encourage health care professionals to engage with designers and engineers to improve the tools they use for supporting their daily routine. The development of the ActiVis tool for nurses, and other visualization tools specific to family doctors and clinician researchers, is still ongoing and we plan to integrate them into an operational platform for health care professionals in Qatar in the near future.

An Automated Approach to Reasoning About Task-Oriented Insights in Responsive Visualization

Authors often transform a large screen visualization for smaller displays through rescaling, aggregation and other techniques when creating visualizations for both desktop and mobile devices (i.e., responsive visualization). However, transformations can alter relationships or patterns implied by the large screen view, requiring authors to reason carefully about what information to preserve while adjusting their design for the smaller display. We propose an automated approach to approximating the loss of support for task-oriented visualization insights (identification, comparison, and trend) in responsive transformation of a source visualization. We operationalize identification, comparison, and trend loss as objective functions calculated by comparing properties of the rendered source visualization to each realized target (small screen) visualization. To evaluate the utility of our approach, we train machine learning models on human ranked small screen alternative visualizations across a set of source visualizations. We find that our approach achieves an accuracy of 84% (random forest model) in ranking visualizations. We demonstrate this approach in a prototype responsive visualization recommender that enumerates responsive transformations using Answer Set Programming and evaluates the preservation of task-oriented insights using our loss measures. We discuss implications of our approach for the development of automated and semi-automated responsive visualization recommendation.

VIS30K: A Collection of Figures and Tables From IEEE Visualization Conference Publications

We present the VIS30K dataset, a collection of 29,689 images that represents 30 years of figures and tables from each track of the IEEE Visualization conference series (Vis, SciVis, InfoVis, VAST). VIS30K's comprehensive coverage of the scientific literature in visualization not only reflects the progress of the field but also enables researchers to study the evolution of the state-of-the-art and to find relevant work based on graphical content. We describe the dataset and our semi-automatic collection process, which couples convolutional neural networks (CNN) with curation. Extracting figures and tables semi-automatically allows us to verify that no images are overlooked or extracted erroneously. To improve quality further, we engaged in a peer-search process for high-quality figures from early IEEE Visualization papers. With the resulting data, we also contribute VISImageNavigator (VIN, visimagenavigator.github.io), a web-based tool that facilitates searching and exploring VIS30K by author names, paper keywords, title and abstract, and years.

A Comparative Evaluation of Animation and Small Multiples for Trend Visualization on Mobile Phones

We compare the efficacy of animated and small multiples variants of scatterplots on mobile phones for comparing trends in multivariate datasets. Visualization is increasingly prevalent in mobile applications and mobile-first websites, yet there is little prior visualization research dedicated to small displays. In this paper, we build upon previous experimental research carried out on larger displays that assessed animated and non-animated variants of scatterplots. Incorporating similar experimental stimuli and tasks, we conducted an experiment where 96 crowdworker participants performed nine trend comparison tasks using their mobile phones. We found that those using a small multiples design consistently completed tasks in less time, albeit with slightly less confidence than those using an animated design. The accuracy results were more task-dependent, and we further interpret our results according to the characteristics of the individual tasks, with a specific focus on the trajectories of target and distractor data items in each task. We identify cases that appear to favor either animation or small multiples, providing new questions for further experimental research and implications for visualization design on mobile devices. Lastly, we provide a reflection on our evaluation methodology.

Evaluating Perceptual Bias During Geometric Scaling of Scatterplots

Scatterplots are frequently scaled to fit display areas in multi-view and multi-device data analysis environments. A common method used for scaling is to enlarge or shrink the entire scatterplot together with the inside points synchronously and proportionally. This process is called geometric scaling. However, geometric scaling of scatterplots may cause a perceptual bias, that is, the perceived and physical values of visual features may be dissociated with respect to geometric scaling. For example, if a scatterplot is projected from a laptop to a large projector screen, then observers may feel that the scatterplot shown on the projector has fewer points than that viewed on the laptop. This paper presents an evaluation study on the perceptual bias of visual features in scatterplots caused by geometric scaling. The study focuses on three fundamental visual features (i.e., numerosity, correlation, and cluster separation) and three hypotheses that are formulated on the basis of our experience. We carefully design three controlled experiments by using well-prepared synthetic data and recruit participants to complete the experiments on the basis of their subjective experience. With a detailed analysis of the experimental results, we obtain a set of instructive findings. First, geometric scaling causes a bias that has a linear relationship with the scale ratio. Second, no significant difference exists between the biases measured from normally and uniformly distributed scatterplots. Third, changing the point radius can correct the bias to a certain extent. These findings can be used to inspire the design decisions of scatterplots in various scenarios.

A Comparison of Radial and Linear Charts for Visualizing Daily Patterns

Radial charts are generally considered less effective than linear charts. Perhaps the only exception is in visualizing periodical time-dependent data, which is believed to be naturally supported by the radial layout. It has been demonstrated that the drawbacks of radial charts outweigh the benefits of this natural mapping. Visualization of daily patterns, as a special case, has not been systematically evaluated using radial charts. In contrast to yearly or weekly recurrent trends, the analysis of daily patterns on a radial chart may benefit from our trained skill on reading radial clocks that are ubiquitous in our culture. In a crowd-sourced experiment with 92 non-expert users, we evaluated the accuracy, efficiency, and subjective ratings of radial and linear charts for visualizing daily traffic accident patterns. We systematically compared juxtaposed 12-hours variants and single 24-hours variants for both layouts in four low-level tasks and one high-level interpretation task. Our results show that over all tasks, the most elementary 24-hours linear bar chart is most accurate and efficient and is also preferred by the users. This provides strong evidence for the use of linear layouts - even for visualizing periodical daily patterns.

A Study on Visual Representations for Active Plant Wall Data Analysis

The indoor climate is closely related to human health, well-being, and comfort. Thus, an understanding of the indoor climate is vital. One way to improve the indoor climates is to place an aesthetically pleasing active plant wall in the environment. By collecting data using sensors placed in and around the plant wall both the indoor climate and the status of the plant wall can be monitored and analyzed. This manuscript presents a user study with domain experts in this field with a focus on the representation of such data. The experts explored this data with a Line graph, a Horizon graph, and a Stacked area graph to better understand the status of the active plant wall and the indoor climate. Qualitative measures were collected with Think-aloud protocol and semi-structured interviews. The study resulted in four categories of analysis tasks: Overview, Detail, Perception, and Complexity. The Line graph was found to be preferred for use in providing an overview, and the Horizon graph for detailed analysis, revealing patterns and showing discernible trends, while the Stacked area graph was generally not preferred. Based on these findings, directions for future research are discussed and formulated. The results and future directions of this research can facilitate the analysis of multivariate temporal data, both for domain users and visualization researchers.