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Cartograms serve as representations of geographical and abstract data, employing a value-by-area mapping technique. As a variant of the Dorling cartogram, the Demers cartogram utilizes squares instead of circles to represent regions. This alternative approach allows for a more intuitive comparison of regions, utilizing screen space more efficiently. However, a drawback of the Dorling cartogram and its variants lies in the potential displacement of regions from their original positions, ultimately compromising legibility, readability, and accuracy. To tackle this limitation, we propose a novel hybrid cartogram layout algorithm that incorporates topological elements, such as rivers, into Demers cartograms. The presence of rivers significantly impacts both the layout and visual appearance of the cartograms. Through a user study conducted on an Electronic Health Records (EHR) dataset, we evaluate the efficacy of the proposed hybrid layout algorithm. The obtained results illustrate that this approach successfully retains key aspects of the original cartogram while enhancing legibility, readability, and overall accuracy.

Resonant high-order harmonics, which result in quasimonochromatic extreme ultraviolet light with coherent intensity enhancement involving autoionizing resonances, have been demonstrated from laser-ablated plumes in the tunnel-ionization regime. Here, we demonstrate resonant harmonics in the previously unexplored multiphoton-ionization regime. We demonstrate an intense resonant harmonic from gallium with an intensity enhancement ratio of 714 relative to the neighboring harmonics, achieved without the need for extreme ultraviolet filtering methods, thus preventing a typical photon flux loss of more than 70%. Three-dimensional time-dependent Schrödinger equation calculations reveal that this increase in the enhancement ratio is due to the lowelectron wave packet spreading in the multiphoton-ionization regime. These results reveal a method for increasing the intensity and monochromaticity of intense multimicrojoule femtosecond extreme ultraviolet light and will also facilitate understanding of the involvement of autoionizing resonances in generating resonant harmonics in the multiphoton-ionization regime.

The Parallel Coordinate Plot (PCP) is a complex visual design commonly used for the analysis of high-dimensional data. Increasing data size and complexity may make it challenging to decipher and uncover trends and outliers in a confined space. A dense PCP image resulting from overlapping edges may cause patterns to be covered. We develop techniques aimed at exploring the relationship between data dimensions to uncover trends in dense PCPs. We introduce correlation glyphs in the PCP view to reveal the strength of the correlation between adjacent axis pairs as well as an interactive glyph lens to uncover links between data dimensions by investigating dense areas of edge intersections. We also present a subtraction operator to identify differences between two similar multivariate data sets and relationship-guided dimensionality reduction by collapsing axis pairs. We finally present a case study of our techniques applied to ensemble data and provide feedback from a domain expert in epidemiology.

Visualization literacy, the ability to interpret and comprehend visual designs, is recognized as an essential skill by the visualization community. We identify and investigate barriers to comprehending parallel coordinates plots (PCPs), one of the advanced graphical representations for the display of multivariate and high-dimensional data. We develop a parallel coordinates literacy test with diverse images generated using popular PCP software tools. The test improves PCP literacy and evaluates the user’s literacy skills. We introduce an interactive educational tool that assists the teaching and learning of parallel coordinates by offering a more active learning experience. Using this pedagogical tool, we aim to advance novice users’ parallel coordinates literacy skills. Based on the hypothesis that an interactive tool that links traditional Cartesian Coordinates with PCPs interactively will enhance PCP literacy further than static slides, we compare the learning experience using traditional slides with our novel software tool and investigate the efficiency of the educational software with an online, crowdsourced user-study. User-study results show that our pedagogical tool positively impacts a user’s PCP comprehension.

Abstract Background Novartis and the University of Oxford’s Big Data Institute (BDI) have established a research alliance with the aim to improve health care and drug development by making it more efficient and targeted. Using a combination of the latest statistical machine learning technology with an innovative IT platform developed to manage large volumes of anonymised data from numerous data sources and types we plan to identify novel patterns with clinical relevance which cannot be detected by humans alone to identify phenotypes and early predictors of patient disease activity and progression. Method The collaboration focuses on highly complex autoimmune diseases and develops a computational framework to assemble a research-ready dataset across numerous modalities. For the Multiple Sclerosis (MS) project, the collaboration has anonymised and integrated phase II to phase IV clinical and imaging trial data from ≈35,000 patients across all clinical phenotypes and collected in more than 2200 centres worldwide. For the “IL-17” project, the collaboration has anonymised and integrated clinical and imaging data from over 30 phase II and III Cosentyx clinical trials including more than 15,000 patients, suffering from four autoimmune disorders (Psoriasis, Axial Spondyloarthritis, Psoriatic arthritis (PsA) and Rheumatoid arthritis (RA)). Results A fundamental component of successful data analysis and the collaborative development of novel machine learning methods on these rich data sets has been the construction of a research informatics framework that can capture the data at regular intervals where images could be anonymised and integrated with the de-identified clinical data, quality controlled and compiled into a research-ready relational database which would then be available to multi-disciplinary analysts. The collaborative development from a group of software developers, data wranglers, statisticians, clinicians, and domain scientists across both organisations has been key. This framework is innovative, as it facilitates collaborative data management and makes a complicated clinical trial data set from a pharmaceutical company available to academic researchers who become associated with the project. Conclusions An informatics framework has been developed to capture clinical trial data into a pipeline of anonymisation, quality control, data exploration, and subsequent integration into a database. Establishing this framework has been integral to the development of analytical tools.

The effort for combating the COVID-19 pandemic around the world has resulted in a huge amount of data, e.g., from testing, contact tracing, modelling, treatment, vaccine trials, and more. In addition to numerous challenges in epidemiology, healthcare, biosciences, and social sciences, there has been an urgent need to develop and provide visualisation and visual analytics (VIS) capacities to support emergency responses under difficult operational conditions. In this paper, we report the experience of a group of VIS volunteers who have been working in a large research and development consortium and providing VIS support to various observational, analytical, model-developmental, and disseminative tasks. In particular, we describe our approaches to the challenges that we have encountered in requirements analysis, data acquisition, visual design, software design, system development, team organisation, and resource planning. By reflecting on our experience, we propose a set of recommendations as the first step towards a methodology for developing and providing rapid VIS capacities to support emergency responses.

Purpose – This paper is a response to a frequently asked question from prospective industry partners searching for opportunities to collaborate with the Computer Science Department of Swansea University, UK. This paper seeks to provide structured guidance in the form of what is titled the Industry Engagement Ladder. Design/methodology/approach – The Industry Engagement Ladder presents a selection of collaboration opportunities, outlining the possible cooperation mechanisms between an industry partner and the academic institution. Findings – Opportunities are described and ranked according to the amount of investment required by the industrial partner, and therefore risk, from low to high. Originality/value – This concise paper provides a quick reference for perspective industry academia collaboration opportunities, the risks involved with each, the possible funding available to help foster these partnerships and the benefits to industry. These collaborative activities (and variations thereof) can be incorporated by any university department. The manuscript offers an ideal starting point for industry–university collaboration.

We report rf-penetration depth measurements of the quasi-2D organic superconductor β″-(BEDT-TTF)2[(H2O)(NH4)2Cr(C2O4)3]·18-crown-6, which has the largest separation between consecutive conduction layers of any 2D organic metal with a single packing motif. Using a contactless tunnel diode oscillator measurement technique, we show the zero-field cooling dependence and field sweeps up to 28 T oriented at various angles with respect to the crystal conduction planes. When oriented parallel to the layers, the upper critical field, Hc2=7.6 T, which is the calculated paramagnetic limit for this material. No signs of inhomogeneous superconductivity are seen, despite previous predictions. When oriented perpendicular to the layers, Shubnikov–de Haas oscillations are seen as low as 6 T, and from these we calculate Fermi surface parameters such as the superconducting coherence length and Dingle temperature. One remarkable result from our data is the high anisotropy of Hc2 in the parallel and perpendicular directions, due to an abnormally low Hc2⊥=0.4 T. Such high anisotropy is rare in other organics and the origin of the smaller Hc2⊥ may be a consequence of a lower effective mass.

The Full Law Analysis Scattering System Hub (FLASSH) is an advanced code which evaluates the thermal scattering law (i.e. TSL, S(α,β)) for thermal scattering cross sections and resonance Doppler broadening. The ability to accurately capture these two key cross section features is dependent on accurate, high fidelity TSL evaluations. FLASSH 1.0 provides advanced physics capabilities resulting in an improved, generalized TSL to most accurately represent the lattice dynamics within any material. This improved TSL will allow for consistent analysis in both the thermal and epithermal energy ranges. The features for TSL analysis are packaged within the FLASSH GUI for easy user interface along with data output in many file formats including ENDF File 7 and ACE files.

Extension educators are increasingly using social media for outreach and information delivery. But are the Facebook, Twitter, and YouTube channels of the world reaching across cultures to non-English speakers, recently resettled refugees or immigrants, migrant workers, or other underserved Extension audiences? After producing and screening over a dozen educational videos dubbed into various languages, we have found videos to be empowering educational tools for engaging nontraditional audiences, especially when screened offline in public workshops. This article outlines techniques for using videos to specifically target historically underserved audiences and non-English speakers by integrating culturally important themes and language voice-overs.

BackgroundLow health literacy compromises patient safety, quality health care, and desired health outcomes. Specifically, low health literacy is associated with decreased knowledge of one's medical condition, poor medication recall, nonadherence to treatment plans, poor self-care behaviors, compromised physical and mental health, greater risk of hospitalization, and increased mortality.MethodsThe health literacy literature was reviewed for: definitions, scope, risk factors, assessment, impact on health outcomes (cardiovascular disease and heart failure), and interventions. Implications for future research and for clinical practice to address health literacy in heart failure patients were summarized.ResultsGeneral health literacy principles should be applied to patients with heart failure, similar to others with chronic conditions. Clinicians treating patients with heart failure should address health literacy using five steps: recognize the consequences of low health literacy, screen patients at risk, document literacy levels and learning preferences, and integrate effective strategies to enhance patients' understanding into practice.ConclusionAlthough the literature specifically addressing low health literacy in patients with heart failure is limited, it is consistent with the larger body of health literacy evidence. Timely recognition of low health literacy combined with tailored interventions should be integrated into clinical practice.

Diversity and inclusion are currently very trendy themes in higher education in science, mainstream culture, and the visualization community. However, the study of diversity with respect to spatial cognition has a long and rich research history extending far beyond the birth of the visualization community. In this brief study, we present a short historical overview of research on the topic of gender diversity and spatial cognition that dates back to the 1940s. We follow this with a small investigation of gender bias in our own data visualization classroom for university students studying computer science. Finally, we round this overview up, with concise recommendations on how to make the visualization classroom more inclusive to support diversity. We believe this educational paper provides a convenient introduction and overview to the topic of diversity in the visualization classroom.

Liquid foams are used in areas such as mineral separation, oil recovery, food and beverage production, sanitation and fire fighting. To improve the quality of products and the efficiency of processes in these areas, foam scientists wish to understand and control foam behaviour. To this end, foam scientists have used foam simulations to model foam behaviour; however, analysing these simulations presents difficult challenges. We describe the main foam research challenges and present the design of FoamVis, the only existing visualization, exploration and analysis application created to address them. We describe FoamVis’ main features, together with relevant design and implementation notes. Our goal is to provide a global overview and individual feature implementation details that would allow a visualization scientist to extend the FoamVis system with new algorithms and adapt it to new requirements. The result is a detailed presentation of the software that is not provided in previous visualization research papers.

Research software often consists of individual, isolated prototype applications. Small proof of concept applications are usually enough for demonstrating new algorithms. However, the unification of new research algorithms into a cohesive software framework has advantages. Adding new features to an existing pipeline reduces implementation overhead. The researcher is more able to compare and contrast existing or previous work with new research. Utilizing previously implemented techniques, researchers are able to combine visualization options in new ways that typical research prototypes cannot. The software application can be made available to the domain expert for evaluation and future use. These goals are in part realized by utilizing recent advancements in game design technology and by leveraging features available with recent graphics hardware. Described is the design of a feature-rich flow visualization software framework in more detail than a typical research paper. In contrast to most research prototypes, the system we present handles real-world simulation datasets by interfacing directly with the commercial package called tecplot. We present a description of our system in detail, whereas previously published work focuses on the research contribution. The effectiveness and scalability of the approach is also discussed.

Maps are one of the most conventional types of visualization used when conveying information to both inexperienced users and advanced analysts. However, the multivariate representation of data on maps is still considered an unsolved problem. We present a multivariate map that uses geo-space to guide the position of multivariate glyphs and enable users to interact with the map and glyphs, conveying meaningful data at different levels of detail. We develop an algorithm pipeline for this process and demonstrate how the user can adjust the level-of-detail of the resulting imagery. The algorithm features a unique combination of guided glyph placement, level-of-detail, dynamic zooming, and smooth transitions. We present a selection of user options to facilitate the exploration process and provide case studies to support how the application can be used. We also compare our placement algorithm with previous geo-spatial glyph placement algorithms. The result is a novel glyph placement solution to support multi-variate maps.

The contact center industry represents a large proportion of many country’s economies. For example, 4% of the entire United States and UK’s working population is employed in this sector. As in most modern industries, contact centers generate gigabytes of operational data that require analysis to provide insight and to improve efficiency. Visualization is a valuable approach to data analysis, enabling trends and correlations to be discovered, particularly when using scatterplots. We present a feature-rich application that visualizes large call center data sets using scatterplots that support millions of points. The application features a scatterplot matrix to provide an overview of the call center data attributes, animation of call start and end times, and utilizes both the CPU and GPU acceleration for processing and filtering. We illustrate the use of the Open Computing Language (OpenCL) to utilize a commodity graphics card for the fast filtering of fields with multiple attributes. We demonstrate the use of the application with millions of call events from a month’s worth of real-world data and report domain expert feedback from our industry partner.

Text visualization is a rapidly growing sub-field of information visualization and visual analytics. There are many approaches and techniques introduced every year to address a wide range of challenges and analysis tasks, enabling researchers from different disciplines to obtain leading-edge knowledge from digitized collections of text. This can be challenging particularly when the data is massive. Additionally, the sources of digital text have spread substantially in the last decades in various forms, such as web pages, blogs, twitter, email, electronic publications, and digitized books. In response to the explosion of text visualization research literature, the first text visualization survey article was published in 2010. Furthermore, there are a growing number of surveys that review existing techniques and classify them based on text research methodology. In this work, we aim to present the first Survey of Surveys (SoS) that review all of the surveys and state-of-the-art papers on text visualization techniques and provide an SoS classification. We study and compare the 14 surveys, and categorize them into five groups: (1) Document-centered, (2) user task analysis, (3) cross-disciplinary, (4) multi-faceted, and (5) satellite-themed. We provide survey recommendations for researchers in the field of text visualization. The result is a very unique, valuable starting point and overview of the current state-of-the-art in text visualization research literature.

In winter of 2004, the Sociology Department at California State University-Bakersfield (CSUB) conducted a student assessment using an embedded assessment technique--a technique wherein a class assignment serves as an assessment tool. The authors conducted the embedded assessment for their Five-Year Program Review. Thus, similar to many departments, their decision to measure learning outcomes was motivated by an external force, namely the university administration. In the first part of this paper they describe their assessment instrument and report assessment outcomes. Next they report on a five-point "agenda for change" generated by faculty in response to the assessment outcome. Finally they present an in-depth discussion of faculty reaction to the assessment process.(Contains 5 tables and 1 footnote.)

A rapidly increasing number of businesses rely on visualisation solutions for their data management challenges. This demand stems from an industry-wide shift towards data-driven approaches to decision making and problem-solving. However, there is an overwhelming mass of heterogeneous data collected as a result. The analysis of these data become a critical and challenging part of the business process. Employing visual analysis increases data comprehension thus enabling a wider range of users to interpret the underlying behaviour, as opposed to skilled but expensive data analysts. Widening the reach to an audience with a broader range of backgrounds creates new opportunities for decision making, problem-solving, trend identification, and creative thinking. In this survey, we identify trends in business visualisation and visual analytic literature where visualisation is used to address data challenges and identify areas in which industries use visual design to develop their understanding of the business environment. Our novel classification of literature includes the topics of businesses intelligence, business ecosystem, customer-centric. This survey provides a valuable overview and insight into the business visualisation literature with a novel classification that highlights both mature and less developed research directions.

Throughout history, storytelling has been an effective way of conveying information and knowledge. In the field of visualization, storytelling is rapidly gaining momentum and evolving cutting-edge techniques that enhance understanding. Many communities have commented on the importance of storytelling in data visualization. Storytellers tend to be integrating complex visualizations into their narratives in growing numbers. In this paper, we present a survey of storytelling literature in visualization and present an overview of the common and important elements in storytelling visualization. We also describe the challenges in this field as well as a novel classification of the literature on storytelling in visualization. Our classification scheme highlights the open and unsolved problems in this field as well as the more mature storytelling sub-fields. The benefits offer a concise overview and a starting point into this rapidly evolving research trend and provide a deeper understanding of this topic.

Visualization, a vibrant field for researchers, practitioners, and higher educational institutions, is growing and evolving very rapidly. Tremendous progress has been made since 1987, the year often cited as the beginning of data visualization as a distinct field. As such, the number of visualization resources and the demand for those resources is increasing at a rapid pace. After a decades-equivalent long search process, we present a survey of open visualization resources for all those with an interest in interactive data visualization and visual analytics. Because the number of resources is so large, we focus on collections of resources, of which there are already many ranging from literature collections to collections of practitioner resources. Based on this, we develop a classification of visualization resource collections with a focus on the resource type, e.g. literature-based, web-based, developer focused and special topics. The result is an overview and details-on-demand of many useful resources. The collection offers a valuable jump-start for those seeking out data visualization resources from all backgrounds spanning from beginners such as students to teachers, practitioners, developers, and researchers wishing to create their own advanced or novel visual designs. This paper is a response to students and others who frequently ask for visualization resources available to them. [ABSTRACT FROM AUTHOR]

Examines racism on college campuses. Discusses group defamation and freedom of speech within that context. Concludes in this period of racial unrest and conflict, a reappraisal is in order of delicate balance between protection from group and class defamation on the one hand and free speech on other, using law as an important base from which to work. (ABL)