Improving perception accuracy in bar charts with internal contrast and framing enhancements

Bar charts are among the most commonly used visualization graphs. Their main goal is to communicate quantities that can be visually compared. Since they are easy to produce and interpret, they are found in any situation where quantitative data needs to be conveyed (websites, newspapers, etc.). However, depending on the layout, the perceived values can vary substantially. For instance, previous research has shown that the positioning of bars (e.g. stacked vs separate) may influence the accuracy in bar ratio length estimation. Other works have studied the effects of embellishments on the perception of encoded quantities. However, to the best of the authors’ knowledge, the effect of perceptual elements used to reinforce the quantity depicted within the bars, such as contrast and inner lines, has not been studied in depth. In this research we present a study that analyzes the effect of several internal contrast and framing enhancements with respect to the use of basic solid bars. Our results show that the addition of minimal visual elements that are easy to implement with current technology can help users to better recognize the amounts depicted by the bar charts.Peer ReviewedPostprint (author's final draft

Visualizing Harmony Using Chordal Glyphs and Color Mapping

Musical scores are frequently annotated with harmonic information, but widely used text-based methods rely on a limited number of visual channels. Though glyph-based methods exploit more channels, existing systems often violate perceptual design principles when employing color and rarely capture the frequency of chordal changes or their harmonic function. In this work, we introduce a new design idiom for augmenting sheet music through chordal glyphs embedded directly within musical staves. Harmonic concepts, weighted by saliency and categorized by data type, are mapped to visual channels ranked by discriminability. Preattentive processing is leveraged to support various user tasks, alongside redundant encodings of foundational harmonic elements to improve overall perceptual effectiveness. Key names and chord roots are displayed using parallel hue-based 12-step categorical colormaps. We then distill several design implications inherent in assigning colors to musical pitches regarding perceptual and linguistic effectiveness. Following this discussion, we outline open research directions

Artifact-Based Rendering: Harnessing Natural and Traditional Visual Media for More Expressive and Engaging 3D Visualizations

We introduce Artifact-Based Rendering (ABR), a framework of tools, algorithms, and processes that makes it possible to produce real, data-driven 3D scientific visualizations with a visual language derived entirely from colors, lines, textures, and forms created using traditional physical media or found in nature. A theory and process for ABR is presented to address three current needs: (i) designing better visualizations by making it possible for non-programmers to rapidly design and critique many alternative data-to-visual mappings; (ii) expanding the visual vocabulary used in scientific visualizations to depict increasingly complex multivariate data; (iii) bringing a more engaging, natural, and human-relatable handcrafted aesthetic to data visualization. New tools and algorithms to support ABR include front-end applets for constructing artifact-based colormaps, optimizing 3D scanned meshes for use in data visualization, and synthesizing textures from artifacts. These are complemented by an interactive rendering engine with custom algorithms and interfaces that demonstrate multiple new visual styles for depicting point, line, surface, and volume data. A within-the-research-team design study provides early evidence of the shift in visualization design processes that ABR is believed to enable when compared to traditional scientific visualization systems. Qualitative user feedback on applications to climate science and brain imaging support the utility of ABR for scientific discovery and public communication.Comment: Published in IEEE VIS 2019, 9 pages of content with 2 pages of references, 12 figure

Towards more effective visualisations in climate services: good practices and recommendations

Visualisations are often the entry point to information that supports stakeholders’ decision- and policy-making processes. Visual displays can employ either static, dynamic or interactive formats as well as various types of representations and visual encodings, which differently affect the attention, recognition and working memory of users. Despite being well-suited for expert audiences, current climate data visualisations need to be further improved to make communication of climate information more inclusive for broader audiences, including people with disabilities. However, the lack of evidence-based guidelines and tools makes the creation of accessible visualisations challenging, potentially leading to misunderstanding and misuse of climate information by users. Taking stock of visualisation challenges identified in a workshop by climate service providers, we review good practices commonly applied by other visualisation-related disciplines strongly based on users’ needs that could be applied to the climate services context. We show how lessons learned in the fields of user experience, data visualisation, graphic design and psychology make useful recommendations for the development of more effective climate service visualisations. This includes applying a user-centred design approach, using interaction in a suitable way in visualisations, paying attention to information architecture or selecting the right type of representation and visual encoding. The recommendations proposed here can help climate service providers reduce users’ cognitive load and improve their overall experience when using a service. These recommendations can be useful for the development of the next generation of climate services, increasing their usability while ensuring that their visual components are inclusive and do not leave anyone behind.The research leading to these results received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements no. 689029 (Climateurope), 776787 (S2S4E), 776467 (MED-GOLD) and 869565 (VitiGEOSS).Peer ReviewedPostprint (published version

An Exploratory Study of Word-Scale Graphics in Data-Rich Text Documents

International audienceWe contribute an investigation of the design and function of word-scale graphics and visualizations embedded in text documents. Word-scale graphics include both data-driven representations such as word-scale visualizations and sparklines, and non-data-driven visual marks. Their design, function, and use has so far received little research attention. We present the results of an open ended exploratory study with 9 graphic designers. The study resulted in a rich collection of different types of graphics, data provenance, and relationships between text, graphics, and data. Based on this corpus, we present a systematic overview of word-scale graphic designs, and examine how designers used them. We also discuss the designers’ goals in creating their graphics, and characterize how they used word-scale graphics to visualize data, add emphasis, and create alternative narratives. Building on these examples, we discuss implications for the design of authoring tools for word-scale graphics and visualizations, and explore how new authoring environments could make it easier for designers to integrate them into documents