Semantic Scholar Open Access 2021 320 sitasi

The Science of Visual Data Communication: What Works

S. Franconeri Lace M. K. Padilla P. Shah Jeffrey M. Zacks J. Hullman

Abstrak

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.

Topik & Kata Kunci

Penulis (5)

S

S. Franconeri

L

Lace M. K. Padilla

P

P. Shah

J

Jeffrey M. Zacks

J

J. Hullman

Format Sitasi

Franconeri, S., Padilla, L.M.K., Shah, P., Zacks, J.M., Hullman, J. (2021). The Science of Visual Data Communication: What Works. https://doi.org/10.1177/15291006211051956

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Informasi Jurnal
Tahun Terbit
2021
Bahasa
en
Total Sitasi
320×
Sumber Database
Semantic Scholar
DOI
10.1177/15291006211051956
Akses
Open Access ✓