Rainbow Dash: Intuitiveness, Interpretability and Memorability of the Rainbow Color Scheme in Visualization

Gołębiowska, Izabela; Çöltekin, Arzu

doi:10.1109/tvcg.2020.3035823

Cited by 19 publications

(9 citation statements)

References 42 publications

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“…• OMC ∼ Viridis ∼ Rainbow OMC sl ColorCrafter In general, our study results confirm findings from Golebiowska and Coltekin [6] that multi-colored scales like OMC and Rainbow are more suitable for reading tasks while sequential scales like Viridis work better for comparing tasks.…”

Section: Discussionsupporting

confidence: 88%

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Color Coding of Large Value Ranges Applied to Meteorological Data

Braun¹,

Ebell²,

Schemann³

et al. 2022

Preprint

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Section: Discussionsupporting

confidence: 88%

“…Color Perception Golebiowska and Coltekin [6] explored the perceptual differences from rainbow to sequential color scales. Their study showed that the sequential colormaps performed better in comparing values and recognizing general patterns, whereas the rainbow scale supports the reading of specific details.…”

Section: Related Workmentioning

confidence: 99%

Color Coding of Large Value Ranges Applied to Meteorological Data

Braun¹,

Ebell²,

Schemann³

et al. 2022

Preprint

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“…Future research efforts might also investigate ways in which to include contextual factors of the map use environment, which we have not included in this study but are part of the context model by Griffin et al [5]. Since we measured the task success rates, comfort, and confidence ratings, it would also be interesting to include evaluation metrics such as learnability, memorability of spatial information, or decision-making accuracy [43][44][45].…”

Section: Discussionmentioning

confidence: 99%

Modeling Patterns in Map Use Contexts and Mobile Map Design Usability

Bartling

Havas

Wegenkittl

et al. 2021

IJGI

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Mobile map applications are increasingly used in various aspects of our lives, leading to an increase in different map use situations and, therefore, map use contexts. Several empirical usability studies have identified how map design is associated with and impacted by selected map use context attributes. This research seeks to expand on these studies and analyzes combinations of map use contexts to identify relevant contextual factors that influence mobile map design usability. In a study with 50 participants from Colombia, we assessed in an online survey the usability of 27 map design variations (consisting of three map-reading tasks, three base map styles, and three interactivity variants). We found that the overall map design is critical in supporting map-reading activities (e.g., identifying a location on a map was supported by a simplified base map, whereas selecting points on the map was supported by a more detailed base map). We then evaluated user patterns in the collected data with archetypal analysis. It was possible to create archetypal representations of the participants with a corresponding map design profile and establish a workflow for modeling patterns in usability and context data. We recommend that future research continues assessing archetypal analysis as it provides a means for context-based decision-making on map design adaptation and transferability.

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“…Yet, heat maps have rarely been used as study material in empirical cartographic user-centered research. Map types with smooth presentation of data are often the subject of color scheme studies [34][35][36][37]. So far, in terms of the usability of heat maps, only studies of the subjective metrics and scenario-based design methods have been conducted.…”

Section: Heat Maps and Generalization In Cartographymentioning

confidence: 99%

Heat Maps: Perfect Maps for Quick Reading? Comparing Usability of Heat Maps with Different Levels of Generalization

Słomska-Przech

Panecki

Pokojski

2021

IJGI

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Recently, due to Web 2.0 and neocartography, heat maps have become a popular map type for quick reading. Heat maps are graphical representations of geographic data density in the form of raster maps, elaborated by applying kernel density estimation with a given radius on point- or linear-input data. The aim of this study was to compare the usability of heat maps with different levels of generalization (defined by radii of 10, 20, 30, and 40 pixels) for basic map user tasks. A user study with 412 participants (16–20 years old, high school students) was carried out in order to compare heat maps that showed the same input data. The study was conducted in schools during geography or IT lessons. Objective (the correctness of the answer, response times) and subjective (response time self-assessment, task difficulty, preferences) metrics were measured. The results show that the smaller radius resulted in the higher correctness of the answers. A larger radius did not result in faster response times. The participants perceived the more generalized maps as easier to use, although this result did not match the performance metrics. Overall, we believe that heat maps, in given circumstances and appropriate design settings, can be considered an efficient method for spatial data presentation.

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Rainbow Dash: Intuitiveness, Interpretability and Memorability of the Rainbow Color Scheme in Visualization

Cited by 19 publications

References 42 publications

Color Coding of Large Value Ranges Applied to Meteorological Data

Color Coding of Large Value Ranges Applied to Meteorological Data

Modeling Patterns in Map Use Contexts and Mobile Map Design Usability

Heat Maps: Perfect Maps for Quick Reading? Comparing Usability of Heat Maps with Different Levels of Generalization

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