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Title: Spanning the Boundaries of Data Visualization Work: An Exploration of Functional Affordances and Disciplinary Values
Creating data visualizations requires diverse skills including computer programming, statistics, and graphic design. Visualization practitioners, often formally trained in one but not all of these areas, increasingly face the challenge of reconciling, integrating and prioritizing competing disciplinary values, norms and priorities. To inform multidisciplinary visualization pedagogy, we analyze the negotiation of values in the rhetoric and affordances of two common tools for creating visual representations of data: R and Adobe Illustrator. Features of, and discourse around, these standard visualization tools illustrate both a convergence of values and priorities (clear, attractive, and communicative data-driven graphics) side-by-side with a retention of rhetorical divisions between disciplinary communities (statistical analysis in contrast to creative expression). We discuss implications for data-driven work and data science curricula within the current environment where data visualization practice is converging while values in rhetoric remain divided.
Authors:
;
Award ID(s):
1704369
Publication Date:
NSF-PAR ID:
10108908
Journal Name:
Lecture notes in computer science
Volume:
14
Page Range or eLocation-ID:
pp 63-75
ISSN:
0302-9743
Sponsoring Org:
National Science Foundation
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