Changing Minds to Changing the World

Mapping the Spectrum of Intent in Data Visualization and Data Arts
  • Scott Murray


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.


Data Visualization Data Design Specific Message Design Firm Default View 
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  1. Bertin J (2011) Semiology of Graphics: diagrams, networks, maps. Esri Press, RedlandsGoogle Scholar
  2. McCullough M (1996) Abstracting craft: the practiced digital hand. MIT Press, CambridgeGoogle Scholar
  3. Segel E, Heer J (2010) Narrative visualization: telling stories with data. IEEE Trans Visual Comput Graphics 16(6):1139–1148CrossRefGoogle Scholar
  4. Williamson C, Shneiderman B (1992) The dynamic HomeFinder: evaluating dynamic queries in a real-estate information exploration system. In Proceeding SIGIR’92, pp 338–346Google Scholar

Copyright information

© Springer-Verlag London 2015

Authors and Affiliations

  1. 1.University of San Francisco (USF)San FranciscoUSA

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