PDF Research report can be found here:
What is data visualization?
“A representation of data that helps you see what you otherwise would have been blind to if you looked only at the naked source. It enables you to see trends, patterns, and outliers that tell you about yourself and what surrounds you. – Nathan Yau, has written several books on data viz.
“Data graphics visually display measured quantities by means of the combined use of points, lines, a coordinate system, numbers, symbols, words, shading and color.” – Edward Tufte, considered the ‘father’ of data viz.
Data viz makes data relatable, informative and human. It helps you find the underlying narratives in a set of numbers on a spreadsheet, and then it helps you to communicate that story. The mark of a good data vis project is how fast you can read and interpret what you’re seeing, and also what it enables you to see what you could not before.
Key components of data visualization:
- Data mining: searching for sources of data, combing through that data to choose what you want to use
- Programming: putting that data in a format the computer program like Processing or others can read. Then putting it into a form that makes sense.
- Designing: making it look nice, which may seem frivolous but I think is really important because if something looks ugly or confusing, people will look away. You need to get their attention, and then keep that attention with your coding you did in step 2.
Data viz vs. Info viz
- Data viz: visualization of a set of information, reliant on programming.
- can be changed or added to as new data comes to light
- often takes the form of graphs, charts, tables
- allows the user to find patterns they otherwise would not have seen
Data viz examples
- A history of the world in 100 seconds.
- They used coordinates from four-hundred and twenty four thousand Wikipedia articles with thiry-five thousand references to events. They combined the two and came up with over fifteen thousand events with locations. Then they mapped it over time and created this.
- Obama’s 2013 Budget proposal http://www.nytimes.com/interactive/2012/02/13/us/politics/2013-budget-proposal-graphic.html?_r=0
- Flight patterns to/from US http://www.aaronkoblin.com/work/flightpatterns/
- Visual explanations of a set of data to tell a specific story.
- Data can’t be changed or added to in any way once it’s done – otherwise you have to start all over again.
“I realized that in some cases, no matter what I did with words, I absolutely could not explain some things without visual help. You can have many, many words and not get across what you can get across in an instant with an infographic.” – Gareth Cook, Pulitzer-prize winning journalist, worked with Boston Globe, NYT, Wired, Scientific American, etc.
- Intellectual power, aesthetic sophistication and emotional impact = what Cook says a good infographic must have
- NYC’s greenhouse gas emissions – new ways of doing infographics
- Mother Nature’s pop science guide to cycling http://www.mnn.com/green-tech/transportation/stories/mother-natures-pop-science-guide-to-cycling-infographic
- Hybrid infographic/data viz: Where Twisters touch down http://www.flickr.com/photos/idvsolutions/7157010997/sizes/o/in/photostream. It shows 56 years of tornado tracks in the US. The line shows the tornado’s path, and the brightness shows the severity, based on the F scale, which is used to measure tornadoes
How are they made?
- Processing – Jer Thorp walks us through it in Processing http://blog.blprnt.com/blog/blprnt/your-random-numbers-getting-started-with-processing-and-data-visualization
- Lynda.com tutorial for Processing http://www.lynda.com/Processing-tutorials/Interactive-Data-Visualization-Processing/97578-2.html
- D3.js http://d3js.org/ – pretty popular, Ex: http://www.nytimes.com/interactive/2012/02/13/us/politics/2013-budget-proposal-graphic.html?_r=0
- No coding required, but less flexibility: Many Eyes, Visual.ly, Infogr.am
Why should we care?
- Wide application: Can be used in a variety of situations where you need or want to present data
- Journalism: NYT Data Visualization Lab, launched in 2008, based on Many Eyes, crowdsourcing. The Toronto Star, Globe and Mail, CBC News – are all expanding their digital desks.
- Nest thermostat system https://nest.com/
- Nike’s Move app http://www.engadget.com/2013/11/05/nike-plus-move-available-now-iphone-5s-app-store-m7-motion-co-processor/
And lastly… bad examples are everywhere. Here is an article featuring the best of the worst.