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The planetary boundary (PB) concept has captured attention across academia and the public alike. Its unique visual representation has been key to the development of the concept and its dissemination. In this commentary, we outline three areas of concern to facilitate further enhancement in the PB concept's visualisation. First, the radial bar plot leads to a quadratic scaling of the effect sizes. Second, the colour gradations denoting the risk of each boundary transgression use complex non-linear patterns, which complicates interpretation. Third, non-linearly distorted colour scales and their fading make the visual perception for people suffering from colour-vision deficiency even more challenging or impossible. The conjunction of quadratic effect scaling and specific colour coding may unintentionally amplify the perception of high-risk areas. We recommend a careful revision of the visual language employed in PB communication. Addressing these concerns will make the PB visualisation a more accurate base for decision-makers. [ABSTRACT FROM AUTHOR]

Color is a central element to scientific communication, but its use comes with the responsibility to ensure universally accessible and accurate data presentation. This short Viewpoint Article aims to sensitize the chemical community to the importance of mindful color choices in scientific illustrations. [ABSTRACT FROM AUTHOR]

Farbe ist ein zentrales Element in der wissenschaftlichen Kommunikation, jedoch bringt ihre Verwendung die Verantwortung mit sich, eine allgemein zugängliche und akkurate Darstellung von Daten und Zusammenhängen zu gewährleisten. Dieser kurze Viewpoint soll dazu dienen, die chemische Gemeinschaft für die Bedeutung einer bewussten Farbwahl in wissenschaftlichen Illustrationen zu sensibilisieren. [ABSTRACT FROM AUTHOR]

Geodynamic modelling provides a powerful tool to investigate processes in the Earth's crust, mantle, and core that are not directly observable. However, numerical models are inherently subject to the assumptions and simplifications on which they are based. In order to use and review numerical modelling studies appropriately, one needs to be aware of the limitations of geodynamic modelling as well as its advantages. Here, we present a comprehensive, yet concise overview of the geodynamic modelling process applied to the solid Earth, from the choice of governing equations to numerical methods, model setup, model interpretation, and the eventual communication of the model results. We highlight best practices and discuss their implementations including code verification, model validation, internal consistency checks, and software and data management. Thus, with this perspective, we encourage high-quality modelling studies, fair external interpretation, and sensible use of published work. We provide ample examples from lithosphere and mantle dynamics and point out synergies with related fields such as seismology, tectonophysics, geology, mineral physics, and geodesy. We clarify and consolidate terminology across geodynamics and numerical modelling to set a standard for clear communication of modelling studies. All in all, this paper presents the basics of geodynamic modelling for first-time and experienced modellers, collaborators, and reviewers from diverse backgrounds to (re)gain a solid understanding of geodynamic modelling as a whole. [ABSTRACT FROM AUTHOR]

Today's geodynamic models can, often do and sometimes have to become very complex. Their underlying, increasingly elaborate numerical codes produce a growing amount of raw data. Post-processing such data is therefore becoming more and more important, but also more challenging and time-consuming. In addition, visualising processed data and results has, in times of coloured figures and a wealth of half-scientific software, become one of the weakest pillars of science, widely mistreated and ignored. Efficient and automated geodynamic diagnostics and sensible scientific visualisation preventing common pitfalls is thus more important than ever. Here, a collection of numerous diagnostics for plate tectonics and mantle dynamics is provided and a case for truly scientific visualisation is made. Amongst other diagnostics are a most accurate and robust plate-boundary identification, slab-polarity recognition, plate-bending derivation, surface-topography component splitting and mantle-plume detection. Thanks to powerful image processing tools and other elaborate algorithms, these and many other insightful diagnostics are conveniently derived from only a subset of the most basic parameter fields. A brand new set of scientific quality, perceptually uniform colour maps including devon, davos, oslo and broc is introduced and made freely available (http://www.fabiocrameri.ch/colourmaps, last access: 25 June 2018). These novel colour maps bring a significant advantage over misleading, non-scientific colour maps like rainbow, which is shown to introduce a visual error to the underlying data of up to 7.5 %. Finally, STAGLAB (http://www.fabiocrameri.ch/StagLab, last access: 25 June 2018) is introduced, a software package that incorporates the whole suite of automated geodynamic diagnostics and, on top of that, applies state-of-the-art scientific visualisation to produce publication-ready figures and movies, all in the blink of an eye and all fully reproducible. STAGLAB, a simple, flexible, efficient and reliable tool made freely available to everyone, is written in MATLAB and adjustable for use with geodynamic mantle convection codes. [ABSTRACT FROM AUTHOR]

The accurate representation of data is essential in science communication. However, colour maps that visually distort data through uneven colour gradients or are unreadable to those with colour-vision deficiency remain prevalent in science. These include, but are not limited to, rainbow-like and red–green colour maps. Here, we present a simple guide for the scientific use of colour. We show how scientifically derived colour maps report true data variations, reduce complexity, and are accessible for people with colour-vision deficiencies. We highlight ways for the scientific community to identify and prevent the misuse of colour in science, and call for a proactive step away from colour misuse among the community, publishers, and the press. The accurate representation of data is essential in science communication, however, colour maps that visually distort data through uneven colour gradients or are unreadable to those with colour vision deficiency remain prevalent. Here, the authors present a simple guide for the scientific use of colour and highlight ways for the scientific community to identify and prevent the misuse of colour in science. [ABSTRACT FROM AUTHOR]

A colour map is a virtual axis that displays a third dimension within a 2-D plot. Hence, the colour axis needs to fulfil the exact same conditions as the position axes (i.e., x and y axes) are generally subjected to: An equal change of data has to be equally represented all along the axes. Such an undistorted and error-free mapping of data to colour is only given if the colour palette is perceptually uniform.Nevertheless, non-scientific colour maps are dominant in the Geodynamics community today. In fact, the most-used colour map in presentations at the EGU general assembly in 2018 - including the Geodynamics sessions - was one of the most data-distorting (see https://betterfigures.org/2018/04/16/how-many-rainbows-at-egu-2018/). A common switch to non-data-distorting, perceptually uniform colour maps today would, therefore, likely be the most effective way to significantly reduce error across the whole Geodynamics community and beyond.Therefore, I present here the first large suite of scientific colour maps (Crameri 2018, GMD). The Scientific Colour Maps feature five crucial characteristics: They are (1) perceptually uniform (i.e., not distorting the data), (2) perceptually ordered (i.e., intuitively readable), (3) colour-vision deficiency (CVD) friendly (i.e., not excluding minorities), (4) readable in black-and-white prints (i.e., effective and useful), and (5) freely available in all major data formats (i.e., open accessible). [ABSTRACT FROM AUTHOR]

Presenting quantitative data using non-standardized color maps potentially results in unrecognized misinterpretation of data. Clinically meaningful color maps should intuitively and inclusively represent data without misleading interpretation. Uniformity of the color gradient for color maps is critically important. Maximal color and lightness contrast, readability for color vision-impaired individuals, and recognizability of the color scheme are highly desirable features. This article describes the use of color maps in five key quantitative MRI techniques: relaxometry, diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE)-MRI, MR elastography (MRE), and water-fat MRI. Current display practice of color maps is reviewed and shortcomings against desirable features are highlighted. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2., (© 2024 The Author(s). Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)