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Data Visualization Resources

Resources from “Data Viz 101: Concepts and Tools” workshop 2015-10-14

Background

Charles Joseph Minard’s Map (1869)

Charles Joseph Minard’s Map (1869), from wikimedia. Edward Tufte says it’s “probably the best statistical graphic ever drawn”.

Different areas:

  • Data Visualization
  • Information Visualization
  • Visual Analytics

Books:

  • Matthew Ward, Georges G. Grinstein, and Daniel Keim. Interactive data visualization : foundations, techniques, and applications, Second edition (Boca Raton : CRC Press, 2015).
  • Colin Ware, Visual thinking for design (Burlington, MA : Morgan Kaufmann, 2008).
  • Colin Ware, Information Visualization Perception for Design, 3rd ed (Burlington : Elsevier Science, 2012).

Visual Analytics

“Visualization allows people to offload cognition to the perceptual system, using carefully designed images as a form of external memory. The human visual system is a very high-bandwidth channel to the brain, with a significant amount of processing occurring in parallel and at the pre-conscious level. We can thus use external images as a substitute for keeping track of things inside our own heads.”

Tamara Munzner, “Visualization,” in Fundamentals of Computer Graphics (3rd edition), ed. Peter Shirley, Michael Ashikhmin, and Steve Marschner (Natick, MA: A K Peters, 2009).

“Visual analytics solutions provide technology that combines the strengths of human and electronic data processing. Visualization becomes the medium of a semi-automated analytical process, where humans and machines cooperate using their respective distinct capabilities for the most effective results.”

Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, and Guy Melan, “Visual Analytics: Definition, Process, and Challenges”, in Information Visualization - Human-Centered Issues and Perspectives, LNCS, ed. Andreas Kerren, et al. (Springer, 2008), 154-175. Available at http://hal-lirmm.ccsd.cnrs.fr/lirmm-00272779/document

Shneiderman

Visual Information Seeking Mantra:

  • Overview first, zoom and filter, then details-on-demand.

Type by Task Taxonomy (TTT)

  • Seven data types: 1-, 2-, 3-dimensional data, temporal and multi-dimensional data, and tree and network data
  • Seven tasks: overview, zoom, filter, details-on-demand, relate, history, extract

Ben Shneiderman, “The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations”, Proceedings of the 1996 IEEE Symposium on Visual Languages (1996): 336. Available at http://www.interactiondesign.us/courses/2011_AD690/PDFs/Shneiderman_1996.pdf

Preattentive Features

Visualizations and Viz tools need to be designed with human visual abilities in mind. For example, check out this research about “Preattentive Features and Tasks” (on youtube):

Christopher G. Healey, “Perception in Visualization”, http://www.csc.ncsu.edu/faculty/healey/PP/

Visualization Examples

The best way to get ideas of good ways to visualize data is to look at lots of examples. Try some of these catalogs:

Negative Examples:

Viz Resources

Simple Web Based Tools

Libraries

Tableau

I rarely recommend non-opensource tools, but Tableau is fairly unique tool for visually exploring data in a flexible, powerful sandbox. They provide free licenses for academic use. If your data can be shared publicly, Tableau Public is a good option.

Academic program

Tableau Public

Tutorials: