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Objective The Australian Cancer Atlas (ACA) aims to provide small-area estimates of cancer incidence and survival in Australia to help identify and address geographical health disparities. We report on the 21-month user-centered design study to visualize the data, in particular, the visualization of the estimate uncertainty for multiple audiences. Materials and Methods The preliminary phases included a scoping study, literature review, and target audience focus groups. Several methods were used to reach the wide target audience. The design and development stage included digital prototyping in parallel with Bayesian model development. Feedback was sought from multiple workshops, audience focus groups, and regular meetings throughout with an expert external advisory group. Results The initial scoping identified 4 target audience groups: the general public, researchers, health practitioners, and policy makers. These target groups were consulted throughout the project to ensure the developed model and uncertainty visualizations were effective for communication. In this paper, we detail ACA features and design iterations, including the 3 complementary ways in which uncertainty is communicated: the wave plot, the v-plot, and color transparency. Discussion We reflect on the methods, design iterations, decision-making process, and document lessons learned for future atlases. Conclusion The ACA has been hugely successful since launching in 2018. It has received over 62 000 individual users from over 100 countries and across all target audiences. It has been replicated in other countries and the second version of the ACA was launched in May 2024. This paper provides rich documentation for future projects. [ABSTRACT FROM AUTHOR]

Virtual prototyping is increasingly used by businesses to streamline operations, cut costs, and enhance daily operations. This often includes a variety of modeling techniques among which, complex, black-box models. The path from model development to utilization in applied contexts is yet long. Domain experts need to be convinced of the validity of the models and to trust their predictions. To be used in the field, model capabilities need to be affordable, that is, allow rapid and interactive scenario building, even for non-experts. Complex relations governed by statistical interactions must be unveiled for users to understand unexpected predictions. We propose Interact, a model-agnostic, visual what-if tool for regression problems, supporting (1) the visualization of statistical interactions between features, (2) the creation of interactive what-if scenarios using predictive models, (3) the evaluation of model quality and building trust, and (4) the externalization of knowledge through model explainability. While the approach applies in various industrial contexts, we validate the application purpose and design with a detailed case study and a qualitative user study with engineers in the tire industry. By unraveling statistical interactions between features, the INTERACT tool proves to be useful to increase the transparency of black-box machine learning models. We also reflect on lessons learned concerning the development of visual what-if tools for virtual product development and beyond. [ABSTRACT FROM AUTHOR]

Soil compaction is one of the major problems facing agriculture today because it increases soil strength and decreases fertility. Modifications to soil decompaction equipment, active bodies and management systems have been shown to provide opportunities to significantly reduce the incidence of compaction. The topic addressed in this paper represents a method of computer-aided design (CAD) combined with computer-aided engineering (CAE) used in the analysis of the choice of the optimal constructive variant to reduce the forward resistance forces of a chisel-type active body intended for soil work equipment without turning the furrow, in order to eliminate hardpan as well as deep compaction. Based on the resulting data, mass/drag coefficient ratios were determined for three analysed configurations. The comparison of these indicators led to the choice of the optimal constructive variant in the sense of the most performing, in order to reduce production costs with maximum efficiency. [ABSTRACT FROM AUTHOR]

Understanding and consuming public budget data is a key issue, helping citizens in gaining insight into their democratic and political systems. The goal of this work is to present Waffster, a user-friendly representation supporting the understanding of such data. The proposed representation enables the browsing, searching, comparing, and presenting of the hierarchically arranged components and quantities in budgets. In this paper, we first conduct a thorough survey of online public budget visualizations. Then, in collaboration with Le Devoir, a Canadian daily newspaper, we propose a novel unit-based hierarchical design based on waffle charts. We evaluate this design using a controlled user study to compare it to a tree-map based layout, and a case study conducted with Le Devoir during the provincial election campaign in Québec of 2018. [ABSTRACT FROM AUTHOR]

Aims: The main objective of this study is to determine whether exposure to Saharan dust causes airway inflammation and oxidative stress in patients with stable chronic heart failure (HF) and a left ventricular ejection fraction of less than 40%. Methods: A longitudinal study design is used, involving the inclusion of 40 patients with stable chronic HF and a left ventricular ejection fraction of less than 40%. Four sputum samplings will be taken from each patient, with one sampling taken each week over four consecutive weeks. The sputum samples will be used to analyze the degree of inflammation and oxidative stress. Air quality monitoring stations will be used to analyze the particulate matter (PM) exposure of each patient. The intrusion of desert dust will be identified using meteorological models. There will be 160 scheduled samplings in 40 patients with chronic HF. Mixed regression models will be used to assess the influence of the concentrations of PM (from the episodes of desert dust) upon the airway inflammation and oxidative stress markers. Conclusion: The results of this study will test the hypothesis that exposure to high concentrations of Saharan dust affects the normal function of the respiratory epithelium due to the imbalance between the production of free radicals and antioxidant enzymes, thus causing increased pulmonary inflammation and oxidative stress in patients with HF that in turn may facilitate decompensations of their background disease condition. [ABSTRACT FROM AUTHOR]

Public activities are mostly carried out in large public buildings, which are closely related to social management. At present, people's demand for public building facilities is increasing, its shape evolution is becoming more complex, and the scientific and technological content of construction-related technology is also increasing. The development trend of green public buildings is more and more strong. The traditional building design cannot effectively deal with the energy consumption of public buildings and people's demand for their performance. This paper introduces BIM and machine learning technology to study their practical application in the design of green public buildings and tests the perfect machine learning algorithm. According to the experimental test results, the building energy consumption decreased by 14.3%, the carbon emission decreased by 11.39%, and the absolute value of PMV thermal comfort decreased by 34.7%, which obviously achieved the optimization effect. BIM technology parametric design can enable the design model formed by conceptual design research to automatically draw construction drawings, detailed drawings and other drawings according to the drawing requirements and standards, thus saving the designer's time and enabling him to transfer the drawing time to the program design. Finally, through experiments, the economy, rationality and operability of using BIM technology to design green public buildings are confirmed. In this paper, machine learning and BIM technology are introduced, so as to carry out design research for green public building design. [ABSTRACT FROM AUTHOR]

The purpose of this developmental study is to elaborate the multidisciplinary studies of music education of class teacher education at the University of Turku into a level which will optimally strengthen the skills of students. The research is carried out by means of educational design research with a developmental extract. The focus in this research article explores the use of participatory future workshop activities as a tool for student teachers in curriculum development work. The aim of this research was to find out what kind of proposals the student teachers (n = 60) made during the eleven future workshops in the development of music education multidisciplinary studies in 2013-2017 and how their proposals and ideas were carried out in real life through the curriculum changes. Finally, we also sought to find out what the overall changes were in the curriculum of music multidisciplinary studies when the initial and final situation were compared after carrying out this part of the research project. All eleven future workshops were video recorded, and the material-based content analyzed. Development ideas raised by students in future workshops were considered and carried out when possible. There were many changes in the two curricula which were implemented during this research. The participatory future workshops for students proved to be very suitable for the development of teacher education curricula. [ABSTRACT FROM AUTHOR]

Introduction: Virtual human work regarding gender is widely based on binary gender despite recent understandings of gender extending beyond female and male. Additionally, gender stereotypes and biases may be present in virtual human design.Methods: This study evaluates how face gender cues are implemented in virtual humans by conducting an exploratory study where an undergraduate computing population (n = 67) designed three virtual human faces—female, male, and nonbinary.Results: Results showed that face gender cues were implemented in stereotypical ways to represent binary genders (female and male virtual humans). For nonbinary gender virtual humans, stereotypical face gender cues were expressed inconsistently (sometimes feminine, sometimes masculine), and conflicting gender cues (pairs of cues that signal opposing binary gender) occurred frequently. Finally, results revealed that not all face gender cues are leveraged equally to express gender.Discussion: Implications of these findings and future directions for inclusive and representative gender expression in virtual humans are discussed.

Predator-prey models are often used in ecology to represent realistic encounters between species. Lotka-Volterra differential equations are famously used by ecologists to model the relationship between a predator and prey. Given ecological data collection is known to be time consuming and difficult, the purpose of this paper is to optimize the process and improve sampling efficiency. The method of sequential optimality is applied to a more complex population model with multiple basins of attraction, the Lotka-Volterra differential equations. In this application, various theoretical scenarios are simulated using varying sample sizes and timeframes to determine optimal designs. The first scenario uses a standard sample size and design window to represent a realistic budget for ecological data collection. The second scenario decreases the budget and extends the design window as a representation of a limited budget. The third scenario represents ample resources available for sampling. The three scenarios are used to then compare the optimal designs and help ecologists evaluate the method of sequential optimality. I, A and D optimal designs are compared in the simulation results. The I-optimality criterion tends to outperform the A and D criteria and is recommended as a primary selection when using the sequential optimality algorithm. This simulation study has further developed sequential optimality by predicting optimal sampling regimes according to the dynamics associated with the Lotka-Volterra differential equations. [ABSTRACT FROM AUTHOR]

Background: The older population needs solutions for independent living and reducing the burden on caregivers while maintaining the quality and dignity of life. Objective: The aim of this study was to design, develop, and evaluate an older adult health care app that supports trained caregivers (ie, formal caregivers) and relatives (ie, informal caregivers). We aimed to identify the factors that affect user acceptance of interfaces depending on the user's role. Methods: We designed and developed an app with 3 user interfaces that enable remote sensing of an older adult's daily activities and behaviors. We conducted user evaluations (N=25) with older adults and their formal and informal caregivers to obtain an overall impression of the health care monitoring app in terms of user experience and usability. In our design study, the participants had firsthand experience with our app, followed by a questionnaire and individual interview to express their opinions on the app. Through the interview, we also identified their views on each user interface and interaction modality to identify the relationship between the user's role and their acceptance of a particular interface. The questionnaire answers were statistically analyzed, and we coded the interview answers based on keywords related to a participant's experience, for example, ease of use and usefulness. Results: We obtained overall positive results in the user evaluation of our app regarding key aspects such as efficiency, perspicuity, dependability, stimulation, and novelty, with an average between 1.74 (SD 1.02) and 2.18 (SD 0.93) on a scale of -3.0 to 3.0. The overall impression of our app was favorable, and we identified that "simple" and "intuitive" were the main factors affecting older adults'and caregivers' preference for the user interface and interaction modality. We also identified a positive user acceptance of the use of augmented reality by 91% (10/11) of the older adults to share information with their formal and informal caregivers. Conclusions: To address the need for a study to evaluate the user experience and user acceptance by older adults as well as both formal and informal caregivers regarding the user interfaces with multimodal interaction in the context of health monitoring, we designed, developed, and conducted user evaluations with the target user groups. Our results through this design study show important implications for designing future health monitoring apps with multiple interaction modalities and intuitive user interfaces in the older adult health care domain. [ABSTRACT FROM AUTHOR]

Student engagement is a central concept for educational practitioners, researchers, and evaluators, especially working with learners historically minoritised in science developing their self-efficacy. Design-oriented projects in invention education show potential for promoting equitable engagement, partly by building upon learners' sociocultural backgrounds and experiences. However, the relationship between more social and more individual conceptions of student engagement is not yet well understood. We took a cultural psychology approach to design-based research for planning, implementing, and analysing a five-day camp in the Northeast US, wherein grades 6–8 students invented an electronic door and a free-choice invention. Our mixed-methods case study for convergence revealed some statistically significant changes in engagement and self-efficacy for inventing, which qualitative analyses suggest were related to campers' cognitive self-efficacy for ability with technology, campers' perceived agency for inter- and trans-disciplinary approaches to inventing, and the camp's social infrastructure for student participation. Further, we found evidence differentiating individual and social levels of affective/emotional, behavioural, and cognitive engagement, supporting a six-part model over previous three- and four-part models. We conclude with conjectures about the camp's enactment, learning processes, and outcomes, providing an educational model that could be useful in designing similar environments for user- or activity-centred design projects. [ABSTRACT FROM AUTHOR]

While we know that the visualization of quantifiable uncertainty impacts the confidence in insights, little is known about whether the same is true for uncertainty that originates from aspects so inherent to the data that they can only be accounted for qualitatively. Being embedded within an archaeological project, we realized how assessing such qualitative uncertainty is crucial in gaining a holistic and accurate understanding of regional spatio-temporal patterns of human settlements over millennia. We therefore investigated the impact of visualizing qualitative implicit errors on the sense-making process via a probe that deliberately represented three distinct implicit errors, i.e., differing collection methods, subjectivity of data interpretations and assumptions on temporal continuity. By analyzing the interactions of 14 archaeologists with different levels of domain expertise, we discovered that novices became more actively aware of typically overlooked data issues and domain experts became more confident of the visualization itself. We observed how participants quoted social factors to alleviate some uncertainty, while in order to minimize it they requested additional contextual breadth or depth of the data. While our visualization did not alleviate all uncertainty, we recognized how it sparked reflective meta-insights regarding methodological directions of the data. We believe our findings inform future visualizations on how to handle the complexity of implicit errors for a range of user typologies and for highly data-critical application domains such as the digital humanities. [ABSTRACT FROM AUTHOR]

The Zones of Confidence (ZOC) is a composite data quality indicator used in Electronic Navigational Charts. Accident reports show that failing to account for chart data quality can result in maritime accidents and loss of life. ZOC overlays are intended to help mariners in identifying potential seafloor hazards and in plotting routes safe for the vessel, but a major concern with the ZOC concept has been the utilized symbology with glyphs consisting of stars. Due to its recognized deficiencies, star-symbology has been rejected for use with the successor of ZOC, the Quality of Bathymetric Data (QoBD). This work presents a research effort toward a new QoBD representation. We define the requirements for the new coding scheme to be effective and propose two texture schemes incorporating countable elements, one consisting of lines and one of dot clusters. For comparison, we developed three alternative, color-based, coding schemes based on ideas previously expressed in the maritime community. Lastly, we present the design, dissemination, and results of an online user survey carried out to evaluate the five coding schemes. The survey results demonstrate that the proposed textures are the most preferred coding schemes among survey respondents. [ABSTRACT FROM AUTHOR]

How could soccer player migration impact national team performance, or vice versa? The answer to this question could play an essential role in making appropriate decisions and policies regarding the international mobility of soccer players. However, answering such a question faces two main challenges, including the complex relationship between variables in multi-attribute temporal data describing migrated players and national team performance, and the interpretation of analysis results in policymaking scenarios. In this work, we have closely collaborated with domain experts and characterized the problems of soccer player migration analysis. To address the first challenge, we adapt a cross-lagged panel analysis model into the player migration analysis problem. This cross-lagged panel analysis model is effective to evaluate the impact strength between player migration and national team performance, and straightforward to reveal the causal relationship. To address the second challenge, we design and develop a visual analytics system, MIG-Viewer, to help the experts to interpret the results of the proposed model efficiently. With MIG-Viewer, the experts can navigate the countries of interest in accordance with migration strategy, conduct comprehensive analysis with the comparison of impact strength, and adjust player migration and inspect further details of a specific country. We present two case studies using global player migration data since 1992 with three soccer analysis experts to demonstrate the effectiveness and usefulness of the system.

Bio-inspired design (BID) has the potential to evolve the way engineers and designers solve problems. Several tools have been developed to assist one or multiple phases of the BID process. These tools, typically studied individually and through the performance of college students, have yielded interesting results for increasing the novelty of solutions. However, not much is known about the likelihood of the tools being integrated into the design and development process of established companies. The mixed-methods study presented in this paper seeks to address this gap by providing industry engineers and designers hands-on training with the BID process and four BID tools. Understanding which tools are valued and could be adopted in an industry context is the goal. The results indicate multiple encouraging outcomes including that industry practitioners highly valued the process framework tool (BID canvas) as it allows for flexibility in tool use, as well as valued learning with a suite of BID tools rather than a single one to accommodate different workflows and ways of thinking. [ABSTRACT FROM AUTHOR]

High Frequency Trading (HFT), mainly based on high speed infrastructure, is a significant element of the trading industry. However, trading machines generate enormous quantities of trading messages that are difficult to explore for financial researchers and traders. Visualization tools of financial data usually focus on portfolio management and the analysis of the relationships between risk and return. Beside risk-return relationship, there are other aspects that attract financial researchers like liquidity and moments of flash crashes in the market. HFT researchers can extract these aspects from HFT data since it shows every detail of the market movement. In this paper, we present HFTViz, a visualization tool designed to help financial researchers explore the HFT dataset provided by NASDAQ exchange. HFTViz provides a comprehensive dashboard aimed at facilitate HFT data exploration. HFTViz contains two sections. It first proposes an overview of the market on a specific date. After selecting desired stocks from overview visualization to investigate in detail, HFTViz also provides a detailed view of the trading messages, the trading volumes and the liquidity measures. In a case study gathering five domain experts, we illustrate the usefulness of HFTViz. [ABSTRACT FROM AUTHOR]

Education is an important component of every healthcare system. Patients need to be educated about their planned procedures; healthcare professionals need to be trained in their respective profession. Both patient education and the training of healthcare professionals are often completed in person, which requires resources and is bound to certain times and places. Virtual educational environments can potentially save human and monetary resources, increase learner engagement, and enable users to learn according to their own schedules. This design study describes proofs of concept for two augmented reality-enabled (AR) educational tools, utilizing a Microsoft HoloLens head-mounted display. In the first use case, we demonstrate an AR application which could be used to educate cancer patients about their radiotherapy treatment and potentially reduce patient anxiety. The second use case demonstrates an AR training environment, which could complement the practical training of undergraduate radiography students. Two prototypes—VIPER, for patient education, and ARTUR for the training of radiography students—were developed and tested for viability and usability, both based on individual user tests. Both patient and student education were evaluated as viable and usable additions to conventional educational methods, despite being limited in terms of accessibility, usability, and fidelity. Suitable hardware is becoming more accessible and capable, and higher-fidelity holograms, better utilization of real-world objects, and more intuitive input methods could increase user immersion and acceptance of the technology. [ABSTRACT FROM AUTHOR]

Puzzle-based training is a common type of hands-on activity accompanying formal and informal cybersecurity education, much like programming or other IT skills. However, there is a lack of tools to help the educators with the post-training data analysis. Through a visualization design study, we designed the Training Analysis Tool that supports learning analysis of a single hands-on session. It allows an in-depth trainee comparison and enables the identification of flaws in puzzle assignments. We also performed a qualitative evaluation with cybersecurity experts and students. The participants apprised the positive influence of the tool on their workflows. Our insights and recommendations could aid the design of future tools supporting educators, even beyond cyber security. [Display omitted] • The logs from serious games are available, still, there is a lack of tools to help analyze their content. • Through a design study with domain experts, we created an analytical tool for cybersecurity training. • An evaluation confirmed the tool's usefulness in analyzing players' behavior and game design issues. • The core design requirements are transferable to other domains with puzzle-based serious games. [ABSTRACT FROM AUTHOR]

Nonlinear programming is a complex methodology where a problem is mathematically expressed in terms of optimality while imposing constraints on feasibility. Such problems are formulated by humans and solved by optimization algorithms. We support domain experts in their challenging tasks of understanding and troubleshooting optimization runs of intricate and high-dimensional nonlinear programs through a visual analytics system. The system was designed for our collaborators' robot motion planning problems, but is domain agnostic in most parts of the visualizations. It allows for an exploration of the iterative solving process of a nonlinear program through several linked views of the computational process. We give insights into this design study, demonstrate our system for selected real-world cases, and discuss the extension of visualization and visual analytics methods for nonlinear programming. [ABSTRACT FROM AUTHOR]

In this design study, we present IRVINE, a Visual Analytics (VA) system, which facilitates the analysis of acoustic data to detect and understand previously unknown errors in the manufacturing of electrical engines. In serial manufacturing processes, signatures from acoustic data provide valuable information on how the relationship between multiple produced engines serves to detect and understand previously unknown errors. To analyze such signatures, IRVINE leverages interactive clustering and data labeling techniques, allowing users to analyze clusters of engines with similar signatures, drill down to groups of engines, and select an engine of interest. Furthermore, IRVINE allows to assign labels to engines and clusters and annotate the cause of an error in the acoustic raw measurement of an engine. Since labels and annotations represent valuable knowledge, they are conserved in a knowledge database to be available for other stakeholders. We contribute a design study, where we developed IRVINE in four main iterations with engineers from a company in the automotive sector. To validate IRVINE, we conducted a field study with six domain experts. Our results suggest a high usability and usefulness of IRVINE as part of the improvement of a real-world manufacturing process. Specifically, with IRVINE domain experts were able to label and annotate produced electrical engines more than 30% faster. [ABSTRACT FROM AUTHOR]

Which drug is most promising for a cancer patient? A new microscopy-based approach for measuring the mass of individual cancer cells treated with different drugs promises to answer this question in only a few hours. However, the analysis pipeline for extracting data from these images is still far from complete automation: human intervention is necessary for quality control for preprocessing steps such as segmentation, adjusting filters, removing noise, and analyzing the result. To address this workflow, we developed Loon, a visualization tool for analyzing drug screening data based on quantitative phase microscopy imaging. Loon visualizes both derived data such as growth rates and imaging data. Since the images are collected automatically at a large scale, manual inspection of images and segmentations is infeasible. However, reviewing representative samples of cells is essential, both for quality control and for data analysis. We introduce a new approach for choosing and visualizing representative exemplar cells that retain a close connection to the low-level data. By tightly integrating the derived data visualization capabilities with the novel exemplar visualization and providing selection and filtering capabilities, Loon is well suited for making decisions about which drugs are suitable for a specific patient. [ABSTRACT FROM AUTHOR]

“Algebra-as-gatekeeper” is a powerful paradigm that structures students’ experiences within mathematics class, as well as their future educational trajectories. In this paper, I show how modeling—when conceived as a culturally relevant practice—can support students to make sense of the key ideas of algebra as well as develop positive mathematical identities. This requires two important facets: 1) that students see themselves reflected in the contexts that are mathematized and 2) that they are positioned to be creative, sense-making story builders and storytellers of this mathematics. Results from my semester-long design study with adolescent girls of color illustrate the potential of modeling, especially for students who often experience the greatest barriers to participation, engagement, and learning within the high school mathematics class.

One way to achieve an intuitive sound design are visual approaches for synthesis and sound collages. Therefore, during spectral synthesis and editing, the sound is designed in a visualization of the frequency domain. In order to create a coherent workflow between visuals and the resulting audio, the stimuli should be matched to each other. In this work, a qualitative user study is presented, which is supposed to show the intuitive understanding from the shape to the sound. The shape is hereby the spectral envelope. The general aim is to find out whether there is a connection between the visual shape and the subsequent auditory impression. [ABSTRACT FROM AUTHOR]

We present and report on Design Exposition Discussion Documents (DExDs), a new means of fostering collaboration between visualization designers and domain experts in applied visualization research. DExDs are a collection of semi-interactive web-based documents used to promote design discourse: to communicate new visualization designs, and their underlying rationale, and to elicit feedback and new design ideas. Developed and applied during a four-year visual data analysis project in criminal intelligence, these documents enabled a series of visualization re-designs to be explored by crime analysts remotely – in a flexible and authentic way. The DExDs were found to engender a level of engagement that is qualitatively distinct from more traditional methods of feedback elicitation, supporting the kind of informed, iterative and design-led feedback that is core to applied visualization research. They also offered a solution to limited and intermittent contact between analyst and visualization researcher and began to address more intractable deficiencies, such as social desirability-bias, common to applied visualization projects. Crucially, DExDs conferred to domain experts greater agency over the design process – collaborators proposed design suggestions, justified with design knowledge, that directly influenced the re-redesigns. We provide context that allows the contributions to be transferred to a range of settings. [ABSTRACT FROM AUTHOR]

The rise of open data in the cultural domain is democratizing access to complex datasets usually presented as large multivariate and multilayered graphs. However, the exploration of such datasets is challenging for laypersons. The objective of this work is to develop and evaluate a new method for exploring and understanding a specific type of multilayered graph that combines a large bipartite graph with a set of tree structures. This paper proposes MuzLink, an interactive visualization tool that allows the user to navigate, search, locate, and compare collaborative and influential relationships between musical artists through the exploration of musical adaptations. The proposed tool is based on a set of connected timelines visualizing how an artist's collaborations, inspirations, and influences evolved over time. This design study is conducted in close collaboration with BAnQ, the national library and archives agency of the Quebec government. A controlled user study, done with a group of BAnQ users, and two case studies, show how the proposed approach is capable of performing a considerable set of analytical and exploratory tasks. [ABSTRACT FROM AUTHOR]