Reaching Broader Audiences With Data Visualization

Lee, Bongshin; Choe, Eun Kyoung; Isenberg, Petra; Marriott, Kim; Stasko, John

doi:10.1109/mcg.2020.2968244

Cited by 74 publications

(40 citation statements)

References 19 publications

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“…Authors can also accompany their data analysis in a paper with an online available data dashboard such as Shiny apps (Chang et al, 2020) for further data exploration. Such efforts could be also beneficial for people with other limited (cognitive) capabilities (i.e., low visualization literacy or blind people) as there are possibilities of speech-or touch-based interaction with non-static visualizations (Lee et al, 2020).…”

Section: Avoid Color -Learning From Black and White Visualizationsmentioning

confidence: 99%

Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication

Stoelzle

Stein

2021

Hydrol. Earth Syst. Sci.

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Abstract. Nowadays color in scientific visualizations is standard and extensively used to group, highlight or delineate different parts of data in visualizations. The rainbow color map (also known as jet color map) is famous for its appealing use of the full visual spectrum with impressive changes in chroma and luminance. Besides attracting attention, science has for decades criticized the rainbow color map for its non-linear and erratic change of hue and luminance along the data variation. The missed uniformity causes a misrepresentation of data values and flaws in science communication. The rainbow color map is scientifically incorrect and hardly decodable for a considerable number of people due to color vision deficiency (CVD) or other vision impairments. Here we aim to raise awareness of how widely used the rainbow color map still is in hydrology. To this end, we perform a paper survey scanning for color issues in around 1000 scientific publications in three different journals including papers published between 2005 and 2020. In this survey, depending on the journal, 16 %–24 % of the publications have a rainbow color map and around the same ratio of papers (18 %–29 %) uses red–green elements often in a way that color is the only possibility to decode the visualized groups of data. Given these shares, there is a 99.6 % chance to pick at least one visual problematic publication in 10 randomly chosen papers from our survey. To overcome the use of the rainbow color maps in science, we propose some tools and techniques focusing on improvement of typical visualization types in hydrological science. We give guidance on how to avoid, improve and trust color in a proper and scientific way. Finally, we outline an approach how the rainbow color map flaws should be communicated across different status groups in science.

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Section: Avoid Color -Learning From Black and White Visualizationsmentioning

confidence: 99%

Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication

Stoelzle

Stein

2021

Hydrol. Earth Syst. Sci.

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“…A third dimension of inclusivity concerns readers' physical dis/abilities and differences. Several ways in which dis/abilities affect readers' interactions with visualizations have been documented (Lee et al, 2020; Lundgard et al, 2019). For example, color vision deficiency (CVD) or color blindness can affect readers' ability to interpret visualizations that rely on color to convey information (Relvas, 2018).…”

Section: Figurementioning

confidence: 99%

“…For best practices when using alt‐text where possible, see Gustafsdottir (2021) and Sollinger (2014). It is worth noting that the visualization community is also addressing accessibility and inclusivity for other challenges, such as blindness (Lee et al, 2020; Lundgard et al, 2019), but those considerations are largely outside the scope of the decision‐making of individual engineering education authors and are not limited to visualizations, which are the focus of this editorial.…”

Section: Figurementioning

confidence: 99%

Designing equitable and inclusive visualizations: An underexplored facet of best practices for research and publishing

Schimpf

Beddoes

2021

J of Engineering Edu

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Equitable and inclusive publishing practices for engineering education research have received increased attention in recent years. JEE editorials and guest editorials have raised awareness about multiple challenges, including the problematic Whiteness and maleness of much research and the need to make diversity the default condition (Pawley, 2017), racially biased citation patterns (Holly, 2020), and other general aspects of publishing ethics (Loui, 2016). There are also ongoing discussions in an engineering education journal editors' group about how to increase the inclusivity of our collective publishing practices. For instance, topics such as inclusive pronouns, positionality statements, and how to better involve scholars of color without overburdening them have been discussed. However, inclusive visualization practices have not yet received the same critical attention. Importantly, visualizations can play a number of key roles in manuscripts, such as synthesizing frameworks or literature (Eppler, 2006), showing relationships between core variables (Tufte, 1997), providing illustrative examples of focal phenomena (e.g., see Schimpf et al., 2020), or enabling comparisons of intervention outcomes (Gleicher et al., 2011). Thus, their influence has a wide reach. Just as other aspects of publishing can serve as mechanisms for either exclusion or inclusion, so too can our choices when designing visualizations.In this guest editorial, we highlight the heretofore unexamined topic of visualization to add to those ongoing efforts to increase the inclusivity of engineering education research publishing practices. The three inclusivity dimensions we discuss are (1) communicating to an interdisciplinary audience, (2) representation equity within visualizations, and (3) readers' physical dis/abilities and differences. In discussing these dimensions and how their associated design decisions can affect the inclusivity of engineering education research, we aim to raise awareness, provide reflective prompts for designing and reviewing visualizations, and ultimately decrease the unintentional use of exclusionary practices. These dimensions are not a definitive list but are intended to encourage a wider discussion within the community about inclusive visualization practices.Our first dimension of inclusivity involves communicating to an interdisciplinary audience. Engineering education is an interdisciplinary field that brings together scholars from engineering disciplines, education disciplines, and social science fields among others. While some types of complex visualizations (e.g., multivariate box plots or threedimensional bar graphs) may be standard or common in some of these fields, there are others that very rarely use any visualizations at all. Therefore, not all of the interdisciplinary contributors to engineering education research are equally familiar with all visualization approaches. As such, we need to ensure that visualizations are discernable to the full community so that they do not become inadvertent gatekeepers...

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“…Designing visual interfaces for exploring data on touch‐enabled devices is becoming an increasingly important topic within the information visualization community [LIRC12, LBI*18, CDIL19, LCI*20]. For example, PanoramicData [ZZD14], Vizdom [CGZ*15], and SketchInsight [LSR*15] featured a pen and touch interface for visual data exploration on large interactive displays.…”

Section: Background and Related Workmentioning

confidence: 99%

Orchard: Exploring Multivariate Heterogeneous Networks on Mobile Phones

Eichmann

Edge

Evans

et al. 2020

Computer Graphics Forum

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People are becoming increasingly sophisticated in their ability to navigate information spaces using search, hyperlinks, and visualization. But, mobile phones preclude the use of multiple coordinated views that have proven effective in the desktop environment (e.g., for business intelligence or visual analytics). In this work, we propose to model information as multivariate heterogeneous networks to enable greater analytic expression for a range of sensemaking tasks while suggesting a new, list‐based paradigm with gestural navigation of structured information spaces on mobile phones. We also present a mobile application, called Orchard, which combines ideas from both faceted search and interactive network exploration in a visual query language to allow users to collect facets of interest during exploratory navigation. Our study showed that users could collect and combine these facets with Orchard, specifying network queries and projections that would only have been possible previously using complex data tools or custom data science.

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Reaching Broader Audiences With Data Visualization

Cited by 74 publications

References 19 publications

Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication

Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication

Designing equitable and inclusive visualizations: An underexplored facet of best practices for research and publishing

Orchard: Exploring Multivariate Heterogeneous Networks on Mobile Phones

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