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The Science of Visual Data Communication: What Works.
Franconeri, Steven L; Padilla, Lace M; Shah, Priti; Zacks, Jeffrey M; Hullman, Jessica.
Afiliação
  • Franconeri SL; Department of Psychology, Northwestern University.
  • Padilla LM; Department of Cognitive and Information Sciences, University of California, Merced.
  • Shah P; Department of Psychology, University of Michigan.
  • Zacks JM; Department of Psychological & Brain Sciences, Washington University in St. Louis.
  • Hullman J; Department of Computer Science, Northwestern University.
Psychol Sci Public Interest ; 22(3): 110-161, 2021 Dec.
Article em En | MEDLINE | ID: mdl-34907835
ABSTRACT
Effectively designed data visualizations allow viewers to use their powerful visual systems to understand patterns in data across science, education, health, and public policy. But ineffectively designed visualizations can cause confusion, misunderstanding, or even distrust-especially among viewers with low graphical literacy. We review research-backed guidelines for creating effective and intuitive visualizations oriented toward communicating data to students, coworkers, and the general public. We describe how the visual system can quickly extract broad statistics from a display, whereas poorly designed displays can lead to misperceptions and illusions. Extracting global statistics is fast, but comparing between subsets of values is slow. Effective graphics avoid taxing working memory, guide attention, and respect familiar conventions. Data visualizations can play a critical role in teaching and communication, provided that designers tailor those visualizations to their audience.
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Texto completo: 1 Eixos temáticos: Difusao_do_conhecimento_cientifico Base de dados: MEDLINE Assunto principal: Comunicação / Visualização de Dados Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Eixos temáticos: Difusao_do_conhecimento_cientifico Base de dados: MEDLINE Assunto principal: Comunicação / Visualização de Dados Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article