Enhancing Color Scales for Active Data Physicalizations

Data Physicalization is the area that investigates how physical objects can encode data through their physical (geometry and materials) and visual features. In the information visualization field, color plays a fundamental role in communicating and encoding data, and it is no different for data physicalization. However, in the real world, color perception can be influenced by the material that composes the data physicalization, the environment’s brightness, and the characteristics of the light-emitting device. Thus, this article presents a process to evaluate and select colors to compose color palettes (categorical, sequential, and divergent) for data physicalizations, considering the perceptual distance between the chosen colors and the brightness of the light-emitting device for evaluating the influence of neighboring colors. Additionally, users perform Information Visualization tasks (identification, comparison, maximums, minimums, etc.) with different color palettes of the industry and literature in a physical 3D bar chart composed of LED strips. The initial results showed better performance by participants using the proposed color scales in Information Visualization tasks than those using traditional digital color scales. Finally, the steps carried out culminated in the proposition of a pipeline for evaluating and creating color scales for data physicalization, considering the features of the light-emitting device and the material used in the data physicalization..

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:14

Enthalten in:

Applied Sciences - 14(2023), 1, p 166

Sprache:

Englisch

Beteiligte Personen:

Cleyton Barbosa [VerfasserIn]
Thiago Sousa [VerfasserIn]
Walbert Monteiro [VerfasserIn]
Tiago Araújo [VerfasserIn]
Bianchi Meiguins [VerfasserIn]

Links:

doi.org [kostenfrei]
doaj.org [kostenfrei]
www.mdpi.com [kostenfrei]
Journal toc [kostenfrei]

Themen:

Assessment
Biology (General)
Chemistry
Color scale
Computer vision
Data physicalization
Engineering (General). Civil engineering (General)
Physics
T
Technology

doi:

10.3390/app14010166

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

DOAJ097813486