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Cluster separation is a task typically tackled by widely used clustering techniques, such as k‐means or DBSCAN. However, these algorithms are based on non‐perceptual metrics, and our experiments demonstrate that their output does not reflect human cluster perception. To bridge the gap between human cluster perception and machine‐computed clusters, we propose HPSCAN, a learning strategy that operates directly on scattered data. To learn perceptual cluster separation on such data, we crowdsourced the labeling of 7320$\hskip.001pt 7320$ bivariate (scatterplot) datasets to 384 human participants. We train our HPSCAN model on these human‐annotated data. Instead of rendering these data as scatterplot images, we used their x and y point coordinates as input to a modified PointNet++ architecture, enabling direct inference on point clouds. In this work, we provide details on how we collected our dataset, report statistics of the resulting annotations, and investigate the perceptual agreement of cluster separation for real‐world data. We also report the training and evaluation protocol for HPSCAN and introduce a novel metric, that measures the accuracy between a clustering technique and a group of human annotators. We explore predicting point‐wise human agreement to detect ambiguities. Finally, we compare our approach to 10 established clustering techniques and demonstrate that HPSCAN is capable of generalizing to unseen and out‐of‐scope data. [ABSTRACT FROM AUTHOR]

Three-dimensional information visualizations are widely used in various fields for their aesthetic appeal. However, using them can sometimes lead to occlusion and distortion, which raises questions about when and why to use them. In this study, we aimed to investigate the effects of three-dimensional visualizations on human gaze and user understanding and analyze the perception process in detail. Our empirical research consisted of a two-part experimental study that involved both subjective and objective evaluation. We specifically focused on bar charts as they are among the most frequently used types of information visualizations. The results suggest that, for bar chart visualizations with varying gap dimensions, there is no statistically significant difference in user understanding between the two-dimensional and three-dimensional versions. Our findings indicate that, in general, three-dimensional bar chart visualizations are as comprehensible as their two-dimensional counterparts for the gap dimensions examined in this research. This study provides empirical insights demonstrating that both 3D and 2D bar charts are equally understandable, particularly when a specific gap depth is used in 3D visualizations. These findings contribute to the ongoing discussion about the effective use of three-dimensional visualizations and highlight areas for further research. [ABSTRACT FROM AUTHOR]

Three-dimensional information visualizations are widely used in various fields for their aesthetic appeal. However, using them can sometimes lead to occlusion and distortion, which raises questions about when and why to use them. In this study, we aimed to investigate the effects of three-dimensional visualizations on human gaze and user understanding and analyze the perception process in detail. Our empirical research consisted of a two-part experimental study that involved both subjective and objective evaluation. We specifically focused on bar charts as they are among the most frequently used types of information visualizations. The results suggest that, for bar chart visualizations with varying gap dimensions, there is no statistically significant difference in user understanding between the two-dimensional and three-dimensional versions. Our findings indicate that, in general, three-dimensional bar chart visualizations are as comprehensible as their two-dimensional counterparts for the gap dimensions examined in this research. This study provides empirical insights demonstrating that both 3D and 2D bar charts are equally understandable, particularly when a specific gap depth is used in 3D visualizations. These findings contribute to the ongoing discussion about the effective use of three-dimensional visualizations and highlight areas for further research.

Objectives Visual hierarchy underlies all visual design decisions related to information presentation. This manuscript describes the experience of a multidisciplinary health data visualization and software design team in using visual hierarchy to redesign a hereditary colorectal cancer lab report. Materials and Methods A series of interviews with representative users were conducted to identify target user groups and determine information hierarchy for each user type. Visual elements (eg, size, color, contrast, etc.) were then assigned to mirror the information hierarchy and workflow for each user type. Results User research identified 2 distinct user groups as consumers of the redesigned lab report. An interactive design employing a 2-level page hierarchy was developed, which stratified the content to support the needs of each user type. Conclusions The challenges related to displaying the complex nature of digital and personal health data can be addressed by applying foundational design methods such as visual hierarchy. Discussion Visual hierarchy, a foundational design principle, can be used by visualization teams to clearly and efficiently present complex datasets associated with healthcare. [ABSTRACT FROM AUTHOR]

Natural language and visualization are two complementary modalities of human communication that play a crucial role in conveying information effectively. While visualizations help people discover trends, patterns and anomalies in data, natural language descriptions help explain these insights. Thus, combining text with visualizations is a prevalent technique for effectively delivering the core message of the data. Given the rise of natural language generation (NLG), there is a growing interest in automatically creating natural language descriptions for visualizations, which can be used as chart captions, answering questions about charts or telling data‐driven stories. In this survey, we systematically review the state of the art on NLG for visualizations and introduce a taxonomy of the problem. The NLG tasks fall within the domain of natural language interfaces (NLIs) for visualization, an area that has garnered significant attention from both the research community and industry. To narrow down the scope of the survey, we primarily concentrate on the research works that focus on text generation for visualizations. To characterize the NLG problem and the design space of proposed solutions, we pose five Wh‐questions, why and how NLG tasks are performed for visualizations, what the task inputs and outputs are, as well as where and when the generated texts are integrated with visualizations. We categorize the solutions used in the surveyed papers based on these ‘five Wh‐questions’. Finally, we discuss the key challenges and potential avenues for future research in this domain. [ABSTRACT FROM AUTHOR]

Urban blue-green infrastructure (BGI) not only serves an ecological purpose but also contributes to the physical and psychological well-being of residents by providing cultural ecosystem services (CES), which are the nonmaterial benefits people obtain from ecosystems through spiritual enrichment, cognitive development, reflection, recreation, and aesthetic experiences. CES is a rising BGI research and management subject, with a growing number of papers in recent years. To identify and differentiate the latest research on the development of features based on cultural ecosystem services within blue-green infrastructure, we employed CiteSpace bibliometric methodologies to analyze pertinent papers for focusing on the developmental processes and key research areas. The publishing trend, research clusters, highly cited literature, research history, research frontiers and hot areas, and high-frequency and emerging keywords were studied and assessed after reviewing 14,344 relevant papers by CiteSpace software 6.3.1 from Web of Science. The standard domains concerned, according to the keyword visualization and high-value references, are implemented cultural ecosystem services assessment combined with natural-based solutions in green spaces, urban regions, residential areas, and sustainable development. In conclusion, the following recommendations are made: (1) When urban decision-makers incorporate the perspective of cultural ecosystem services into the strategic formulation of BGI, a broader spectrum of urban BGI types should be taken into account; (2) all categories of CES should be considered; (3) research on the application of cultural ecosystem services in urban blue-green infrastructure should be more effectively and flexibly integrated into urban governance; and (4) CES should be strategically employed to improve the physical health and psychological well-being of urban residents. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Experimental economics is an important branch of economics to study human behaviours in a controlled laboratory setting or out in the field. Scientific experiments are conducted in experimental economics to collect what decisions people make in specific circumstances and verify economic theories. As a significant couple of variables in the virtual experimental environment, decisions and outcomes change with the subjective factors of participants and objective circumstances, making it a difficult task to capture human behaviour patterns and establish correlations to verify economic theories. In this paper, we present a visual analytics system, EBPVis, which enables economists to visually explore human behaviour patterns and faithfully verify economic theories, e.g. the vicious cycle of poverty and poverty trap. We utilize a Doc2Vec model to transform the economic behaviours of participants into a vectorized space according to their sequential decisions, where frequent sequences can be easily perceived and extracted to represent human behaviour patterns. To explore the correlation between decisions and outcomes, an Outcome View is designed to display the outcome variables for behaviour patterns. We also provide a Comparison View to support an efficient comparison between multiple behaviour patterns by revealing their differences in terms of decision combinations and time‐varying profits. Moreover, an Individual View is designed to illustrate the outcome accumulation and behaviour patterns of subjects. Case studies, expert feedback and user studies based on a real‐world dataset have demonstrated the effectiveness and practicability of EBPVis in the representation of economic behaviour patterns and certification of economic theories. [ABSTRACT FROM AUTHOR]

We present a visual computing framework for analysing moral rhetoric on social media around controversial topics. Using Moral Foundation Theory, we propose a methodology for deconstructing and visualizing the when, where and who behind each of these moral dimensions as expressed in microblog data. We characterize the design of this framework, developed in collaboration with experts from language processing, communications and causal inference. Our approach integrates microblog data with multiple sources of geospatial and temporal data, and leverages unsupervised machine learning (generalized additive models) to support collaborative hypothesis discovery and testing. We implement this approach in a system named MOTIV. We illustrate this approach on two problems, one related to Stay‐at‐home policies during the COVID‐19 pandemic, and the other related to the Black Lives Matter movement. Through detailed case studies and discussions with collaborators, we identify several insights discovered regarding the different drivers of moral sentiment in social media. Our results indicate that this visual approach supports rapid, collaborative hypothesis testing, and can help give insights into the underlying moral values behind controversial political issues. Supplemental Material: https://osf.io/ygkzn/?view_only=6310c0886938415391d977b8aae8b749 [ABSTRACT FROM AUTHOR]

The benefits of teacher-facing dashboards are incontestable, yet their evidence is finite in terms of long-term use, meaningful usability, and maturity level. Thus, this paper uses design science research and critical theory to design and develop TEADASH to support teachers in making decisions on teaching and learning. Three cycles of design science research and multiple small loops were implemented to develop the dashboard. The tool was then deployed and evaluated in real time with the authentic courses. Five courses from two Swedish universities were included in this study. The co-design with teachers is crucial to the applicability of this dashboard, while letting teachers use the tool during their courses is more important to help them to recognize the features they actually use and the tool's usefulness for their teaching practices. TEADASH can address the prior matters, align with the learning design, and meet teachers' needs. The technical and co-design aspects, as well as the advantages and challenges of applying TEADASH in practice, are also discussed here. [ABSTRACT FROM AUTHOR]

Cartographic representations are increasingly used to communicate sustainable mobility topics. Various formats of maps, such as static maps, mobile maps, map-based dashboards, story maps, and 3D map scenes, are created to illustrate mobility planning, traffic status, emissions, and travel behaviors. These maps are rich in cross-disciplinary information, target to diverse audiences, adopt various design technologies, and enable knowledge exchange among stakeholders of sustainable mobility. This paper examines how maps are used as communication tools for traffic and infrastructure to support decision-making and engage people to actively adapt their behavior towards green mobility. In this study, we (1) identified 48 maps that actively communicate sustainable mobility topics, (2) proposed a rigorous approach to assess maps that are created for communicating sustainable mobility topics, and (3) derived design recommendations for map makers to achieve more effective and efficient communication. [ABSTRACT FROM AUTHOR]

The design of healthcare systems has unintentionally contributed to a rise in medical errors, partly due to the integration of new technologies into outdated systems. By applying user-centred design, we can gain valuable insights from diverse perspectives, helping to develop and refine products and services that improve the healthcare process and enhance safety for all stakeholders. This paper explores the application of design thinking to analyse healthcare systems, with a specific focus on the pre-surgical process. It highlights three key design tools--ecosystem mapping, participatory workshops, and data visualizations--that were instrumental in identifying issues, proposing interventions, and communicating findings. User-centred design proves to be an effective approach for creating solutions that align with the needs of all users involved in the healthcare process. [ABSTRACT FROM AUTHOR]

Over the past five decades, onomastics has seen remarkable growth with fruitful publications and interdisciplinary collaborations. Despite the abundance of literature, a panoramic view of contribution networks and the evolutionary trajectory of this field has been lacking. To address this issue, this study presents a statistical assessment complemented by visualization clustering, rendering data from 768 journal articles and 28,357 references, to unfold impactful journals, influential scholars, foundational knowledge, and evolving frontiers. The outcomes of this research showcase the distribution of subtopics within each name category, depicting noteworthy contributors, focal trends, and cutting-edge subjects in the area. New themes that illuminate orientations include online naming, multi-identity construction, language processing, corpusassisted approaches, and neural-cognitive experiments. Further data-driven exploration of name-related themes is foreseen to yield valuable insights. Through this comprehensive assessment, this study elucidates the role of names as manifestations of human identity, social emotions, aesthetic ingenuity, and strategic communicative paradigms. The findings are poised to facilitate the discernment of human quality, societal stratification, interpretative nuances, and relationships underlying social issues. Additionally, this research exemplifies the efficacy of bibliometric analysis and proposes strategies to mitigate potential constraints, disclosing how quantitative data from onomastics can be applied in the digital era and beyond. This article is the corrected version of the original article. For more information on the changes made, see the erratum: http://dx.doi.org/10.5195/names.2024.2689. [ABSTRACT FROM AUTHOR]

In this research, a system-guided artificial intelligence vocal training system is designed and further simulated taking into account the speech spectrum visualization. Although the coefficients and cepstrum coefficients can then generally better represent the spectral envelope, at low frequencies, the spectral envelope is often not accurately expressed. Therefore, this paper adopts the information visualization and data analysis models to complete the computer-aided system. Two major contributions are reflected in the paper. First, we use past sample values to predict future sample values, and determine the set of prediction parameters by the error between the actual speech sample and the linear prediction, the statistical model is determined. Second, the system is designed and implemented using coding theory, we construct the robust and efficient vocal guidance system. The experiment compared with the recently published paper has shown the performance of our model. For the designed system, the visualization performance is validated by the massive test and the robustness is higher, which will be meaningful for the complex scenarios. [ABSTRACT FROM AUTHOR]

Copyright of Arcos: Design, Cultura e Visualidade is the property of Editora da Universidade do Estado do Rio de Janeiro (EdUERJ) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Brushing and linking is widely used for visual analytics in desktop environments. However, using this approach to link many data items between situated (e.g., a virtual screen with data) and embedded views (e.g., highlighted objects in the physical environment) is largely unexplored. To this end, we study the effectiveness of visual highlighting techniques in helping users identify and link physical referents to brushed data marks in a situated scatterplot. In an exploratory virtual reality user study (N=20), we evaluated four highlighting techniques under different physical layouts and tasks. We discuss the effectiveness of these techniques, as well as implications for the design of brushing and linking operations in situated analytics. [ABSTRACT FROM AUTHOR]

Analyzing the preference of route choice not only facilitates the understanding of individuals' decision‐making behavior, but also provides valuable information for improving traffic management strategies. As the layout of the road network, the variability of individual preferences and the spatial distribution of origins and destinations all play a role in route choice, it is a great challenge to reveal the interplay of such numerous complex factors. In this paper, we propose RouteVis, an interactive visual analytics system that enables traffic analysts to gain insight into what factors drive individuals to choose a specific route. To uncover the relationship between route choice and influencing factors, we design a quantitative analytical framework that supports analysts in conducting closed‐loop analysis of various factors, i.e., data preprocessing, route identification, and the quantification of influence and contribution. Furthermore, given the multidimensional and spatio‐temporal characteristics of the analysis results, we customize a set of coordinated views and visual designs to provide an intuitive presentation of the factors affecting people's travels, thus freeing analysts from tedious repetitive tasks and significantly enhancing work efficiency. Two typical usage scenarios and expert feedback on the system's functionality demonstrate that RouteVis can greatly enhance the capabilities of understanding the travel status. [ABSTRACT FROM AUTHOR]

Visualizing small‐world networks such as protein‐protein interaction networks or social networks often leads to visual clutter and limited interpretability. To overcome these problems, we present ProtEGOnist, a visualization approach designed to explore small‐world networks. ProtEGOnist visualizes networks using ego‐graphs that represent local neighborhoods. Ego‐graphs are visualized in an aggregated state as a glyph where the size encodes the size of the neighborhood and in a detailed version where the original network nodes can be explored. The ego‐graphs are arranged in an ego‐graph network, where edges encode similarity using the Jaccard index. Our design aims to reduce visual complexity and clutter while enabling detailed exploration and facilitating the discovery of meaningful patterns. To achieve this, our approach offers a network overview using ego‐graphs, a radar chart for a one‐to‐many ego‐graph comparison and meta‐data integration, and detailed ego‐graph subnetworks for interactive exploration. We demonstrate the applicability of our approach on a co‐author network and two different protein‐protein interaction networks. A web‐based prototype of ProtEGOnist can be accessed online at https://protegonist-tuevis.cs.uni-tuebingen.de/. [ABSTRACT FROM AUTHOR]

The term Design Intelligence System, Methodology, and Strategy indicates a new digital modality of architecturally constructed and visualized diagrammatic research framework and environment. Aiming to facilitate, articulate, and support any kind of documentary, scientific, and creative investigative practice with large amounts of data in a formalized way, DI system, methodology, and strategy have been proposed for consideration to be included into the fields of Design Research and Design Science. It has been argued that they can offer a specific response to various research requirements and make a contribution at the level of methodology, instrumentation, and research strategy. Beside the control and guidance of data-operations in line with research subjects and questions, the system preserves design research procedures and dynamics of problem-solving and decision-making as formal inscription, or information-architecture, enabling one to visualize maps and lines of inference and connectivity between different information and arguments, and to acknowledge main issues in delivering a proof and carrying out valid reasoning. Regarding the fact that, alongside extensive use as a means of artistic exploration, this kind of digital framework, formalization, and system has not been substantially questioned as a means of reliable and functional scientific research in the targeted Design Research and Design Science fields, the paper will address these issues through comments on the system's attributes, arguments, relevance, and contributions, and analysis of the performed test-studies, their development stages, and the system's determinants, which have led to its final eleven criteria-form. The field of Diagrammatics has been proposed as a broader context due to the Design Intelligence System's central diagrammatic properties and modes of operation. [ABSTRACT FROM AUTHOR]

Over the past five decades, onomastics has seen remarkable growth with fruitful publications and interdisciplinary collaborations. Despite the abundance of literature, a panoramic view of contribution networks and the evolutionary trajectory of this field has been lacking. To address this issue, this study presents a statistical assessment complemented by visualization clustering, rendering data from 768 journal articles and 28,357 references, to unfold impactful journals, influential scholars, foundational knowledge, and evolving frontiers. The outcomes of this research showcase the distribution of subtopics within each name category, depicting noteworthy contributors, focal trends, and cutting-edge subjects in the area. New themes that illuminate orientations include online naming, multi-identity construction, language processing, corpus-assisted approaches, and neural-cognitive experiments. Further data-driven exploration of name-related themes is foreseen to yield valuable insights. Through this comprehensive assessment, this study elucidates the role of names as manifestations of human identity, social emotions, aesthetic ingenuity, and strategic communicative paradigms. The findings are poised to facilitate the discernment of human quality, societal stratification, interpretative nuances, and relationships underlying social issues. Additionally, this research exemplifies the efficacy of bibliometric analysis and proposes strategies to mitigate potential constraints, disclosing how quantitative data from onomastics can be applied in the digital era and beyond.