Abstract
The recent explosion in available data sources and data-processing tools has both scientists and artists diving into the world of data visualization. The result is a diverse, interdisciplinary field of practice, in which practitioners cultivate knowledge in other areas: Statisticians are learning about design, while designers are learning about statistics. All of these people are producing visualizations of data—objects of visual communication—but with widely varying intentions and goals for their creations. Several primary goals for visualization—exploratory, informational, and rhetorical—are well-established. But in a field where artists (seeking to produce aesthetic, yet “accurate” work) are learning about science, and scientists (seeking to produce informational, yet “aesthetically appealing” work) are learning about art, how can we delineate between the range of types of intended communications and can those delineations be made in any meaningful way? One of the most exciting aspects of visualization today is the ease with which practitioners from different backgrounds collaborate and engage with each other. By examining the discourse adopted by these practitioners, we can identify what processes they all have in common, and then map where practices overlap and where they diverge.
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Notes
- 1.
See Drought and Deluge in the Lower 48, Mike Bostock and Shan Carter, February 22, 2013. URL, November 14, 2014: http://www.nytimes.com/interactive/2012/08/11/sunday-review/drought-history.html.
- 2.
See Drought’s Footprint, Haeyoun Park and Kevin Quealy, July 19, 2012. URL, November 14, 2014: http://www.nytimes.com/interactive/2012/07/20/us/drought-footprint.html.
- 3.
See photo documentation of the IBM THINK Exhibit at Lincoln Center in New York City, URL, November 14, 2014: http://mirada.com/stories/ibm. Project developed by Mirada, opened September 23, 2011.
- 4.
See Shadow Monsters, Philip Worthington, 2004–ongoing. URL, November 14, 2014: http://moma.org/exhibitions/2008/elasticmind/#/229.
- 5.
Published on December 3, 2012. URL, November 14, 2014: http://www.economist.com/blogs/graphicdetail/2012/12/daily-chart
- 6.
For in-depth discussion of this issue, (see McCullough 1996).
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Murray, S. (2015). Changing Minds to Changing the World. In: Bihanic, D. (eds) New Challenges for Data Design. Springer, London. https://doi.org/10.1007/978-1-4471-6596-5_16
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