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Data Visualization

Data Visualization. Joseph Ryan ITS Research Computing November 8, 2012. On the agenda. The “ magic ” hypothesis. Three common goals. How to get started. Visualization tools for the web. Goals. Successful visualizations depend on you. And your audience

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Data Visualization

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  1. Data Visualization Joseph Ryan ITS Research Computing November 8, 2012

  2. On the agenda. • The “magic” hypothesis. • Three common goals. • How to get started. • Visualization tools for the web.

  3. Goals

  4. Successful visualizations depend on you • And your audience • And your goal(s) for your visualization

  5. A Path

  6. Who? What? Should? • Who is my audience? • Experts? • Students? • General public? • What do I want to tell them? • Space or time relationship? • Multivariate system? • Does this message belong in a visualization?

  7. Ben Fry: How to Get Started • Get some data. • Organize and structure the data. • Remove unnecessary(!) data. • Use statistical methods to discover patterns. • Choose a visualization style. • http://www.visual-literacy.org/periodic_table/periodic_table.html • Refine. • Build interaction, if appropriate and possible.

  8. Tools

  9. Visualization Playgrounds • Many Eyes • http://www-958.ibm.com/software/data/cognos/manyeyes/ • OpenData • http://opendata.socrata.com/ • ChartsBin • http://chartsbin.com/graph

  10. Google Chart API • http://code.google.com/apis/chart/interactive/docs/gallery.html

  11. D3.js • http://d3js.org/

  12. Summing Up • Make sure data visualization is the right tool for the job • Define audience, information to communicate first • Choose a visualization • Existing examples in knowledge area? • Data to support this visualization? • Tools and expertise to create it? • Have fun • Try breaking some rules • Ask someone outside of your area for feedback!

  13. Thank you! Joseph Ryan ITS Research Computing ryanjd@email.unc.edu Ben Fry’s excellent Visualizing Data provided significant intellectual content to this presentation.

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