Data visualization is the process of presenting large amounts of data in a visual form that helps to reveal meaningful patterns in the data. Traditional data visualization tools, such as paper-based graphs, are essentially limited to presenting two dimensions of data; however, some online data visualization tools can present up to five dimensions of data simultaneously. A three-minute video that provides an overview of data visualization is here.
In the past ten years, thanks to the advent of Web 2.0 and specialized online tools, it's possible for any individual to make and share effective data visualizations. David McCandless talks about the importance of data visualization in this 18-minute presentation. Hans Rosling's 5-minute video about data visualizations is also enlightening.
Incidentally, it's also possible to render data into sound. Consider this transformation of the digits of the irrational number Tau into sound.
- "The effectiveness of data visualizations can be largely attributed to the powerful processing mechanisms of human vision, with the most effective visualizations mapping data to perceptual mechanisms in such a way that the important patterns are easily perceived." -- Data visualization optimization via computational modeling of perception, IEEE Transactions on Visualization and Computer Graphics, 2012
- "Data visualization is effective because it shifts the balance between perception and cognition to take fuller advantage of the brain's abilities. Seeing (i.e visual perception) which is handled by the visual cortex located in the rear of the brain, is extremely fast and efficient. We see immediately, with little effort. Thinking (i.e. cognition), which is handled primarily by the cerebral cortex in the front of the brain, is much slower and less efficient. Traditional data sense-making and presentation methods require conscious thinking for almost all of the work. Data visualization shifts the balance toward greater use of visual perception, taking advantage of our powerful eyes whenever possible." -- Data visualization for human perception, Interaction-Design.org Foundation, 2010.
- Make the design of your data visualization fit the data, not the other way around; that is, data has priority over design.
- If you're using a data visualization in a presentation, it's probably better to convey a fact or idea with a visual rather than with digits; for example, a bar chart that shows the relative amounts of various items is usually better than just giving the bare numbers (34, 56, 98, 22, etc).
- Don't manipulate the data in order to make it fit your argument.
- Cite the sources of your data.
- Don't try to cram all of your data into a visualization; streamline it, so that the important patterns and trends emerge.
- Your data (and visualization) will have most impact on your audience if you can show how it tells a story.
Two tools that are especially relevant to data visualizations are Gapminder and Google Motion Charts, both of which allow you to analyze your own data sets.
An essential difference between Gapminder and Google Motion Charts is that the former comes pre-loaded with quality data from international organizations; a user cannot upload his or her own data into Gapminder. Google Motion Charts, in contrast, does not come pre-loaded with any data, but a user can upload his or her own data.
Resources for Gapminder
- The first eight minutes of this video demonstrate how to use GapMinder.
- A quick overview of the various features of GapMinder (PDF).
- 7 Things you should know about data visualization.
- Some ideas about how to use Gapminder in teaching.
Resources for Google Motion Charts
- The last 14 minutes of this video demonstrate how to use Google Motion Charts.
- A quick guide to Google Motion Charts.
Timeline tools and text analysis tools are also related, albeit more distantly, to data visualizations.
If you would like support applying these tips to your own teaching, CTE staff members are here to help. View the CTE Support page to find the most relevant staff member to contact.
- Teaching and Learning Data Visualization: Ideas and Assignments
- Formalizing students’ informal statistical reasoning on real data: Using Gapminder to follow the cycle of inquiry and visual analyses
- Innovative Pedagogy for Teaching and Learning Data Visualization
- Data visualization for human perception.
- Information is beautiful.
- Data Visualization: Resources for Teaching, Learning, and Research. Academic Technology, Harvard University.
Contact Mark Morton.
This Creative Commons license lets others remix, tweak, and build upon our work non-commercially, as long as they credit us and indicate if changes were made. Use this citation format: Data Visualization. Centre for Teaching Excellence, University of Waterloo.