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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.

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.

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.

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.

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]

With the advent of novel visualization techniques to convey complex information, data visualization literacy is growing in importance. Two facets of literacy are user understanding and the discovery of visual patterns with the help of graphical representations. The research literature on visualization literacy provides useful guidance and important opportunities for further studies in this field. This survey examines and classifies prior research on visualization literacy that analyzes how well users understand novel data representations. To our knowledge, this is the first comprehensive survey paper with a focus on interactive visualization literacy. We categorize existing relevant research into unique subject groups that facilitate and inform comparisons of related literature and provide an overview of the same. Additionally, the survey/classification also provides an overview of the various evaluation techniques used in this field of research due to their challenging nature. Our novel classification enables researchers to find both mature and unexplored directions that may lead to future work. This survey serves as a valuable resource for both beginners and experienced researchers interested in the topic of visualization literacy. [ABSTRACT FROM AUTHOR]

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. • Enhancing epidemiological modelling workflows with a range of visualisation and visual analytics (VIS) support. • Supporting an emergency response with a large-scale VIS volunteering effort that is unprecedented in the field of VIS or previous emergency responses. • Demonstrating the feasibility for developing a VIS infrastructure as well as VIS software for supporting four-levels of visualisation. • Evidencing that VIS capabilities should be available to epidemiological modellers from the very beginning in future emergency responses. [ABSTRACT FROM AUTHOR]