Acquired Codes of Meaning in Data Visualization and Infographics: Beyond Perceptual Primitives

PROJECT TITLE :

Acquired Codes of Meaning in Data Visualization and Infographics: Beyond Perceptual Primitives

ABSTRACT:

While data visualization frameworks and heuristics have historically been reluctant to incorporate acquired codes of which means, designers are creating use of them in a wide range of ways in which. Acquired codes leverage a user's expertise to understand the which means of a visualization. They range from figurative visualizations which rely on the reader's recognition of shapes, to traditional arrangements of graphic parts that represent particular subjects. During this study, we tend to used content analysis to codify acquired which means in visualization. We tend to applied the content analysis to a set of infographics and knowledge visualizations that are exemplars of innovative and effective design. eighty eight% of the infographics and seventy one% of information visualizations within the sample contain at least one use of figurative visualization. Conventions on the arrangement of graphics are also widespread in the sample. In specific, a comparison of representations of your time and different quantitative data showed that conventions will be specific to a subject. These results recommend that there's a need for data visualization analysis to expand its scope beyond perceptual channels, to incorporate social and culturally created which means. Our paper demonstrates a viable technique for identifying figurative techniques and graphic conventions and integrating them into heuristics for visualization design.

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