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Spanning the Boundaries of Data Visualization Work: An Exploration of Functional Affordances and Disciplinary Values

机译:跨越数据可视化工作的边界:功能支持和学科价值探究

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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.
机译:创建数据可视化需要多种技能,包括计算机编程,统计和图形设计。可视化从业人员通常在其中一个领域但并非所有领域都接受过正式培训,因此日益面临调和,整合和优先考虑相互竞争的学科价值,规范和优先事项的挑战。为了告知多学科的可视化教学方法,我们分析了两种用于创建数据的可视表示形式的常用工具的修辞和提供能力方面的价值协商:R和Adobe Illustrator。这些标准的可视化工具的功能和讨论方式并排说明了价值和优先级的融合(清晰,引人注目的和可沟通的数据驱动图形),并保留了学科界之间的修辞分野(对比统计分析创意表达)。我们讨论了在当前环境中数据可视化实践正在汇聚而言辞价值仍存在分歧的情况下,对数据驱动的工作和数据科学课程的意义。

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