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These will be useful to introduce students, journalists, or levitra drug to the concepts of data visualization. Bonus: There’s an interesting discussion on Quora about .
(1) (April 2, 2011): A 1,000-word article that covers a lot of non-journalism work in this field, including the marvelous .
(2) : This two-page PDF from EduCause provides a text-only explanation.
Representing large amounts of disparate information in a visual form often allows you to see patterns that would otherwise be buried in vast, unconnected data sets. … Visualizations allow you to understand and process enormous amounts of information quickly because it is all represented in a single image or animation.
(3) : This blog by Nathan Yau, a statistics scholar, is a wonderful resource, frequently updated with great examples from all kinds of sources.
(4) : Part of the “Many Eyes” site from IBM Research, this list links to examples of every kind of information chart and graphic you can create with the Many Eyes application. You get an illustration and a clear, levitra drug explanation — great for teaching. See an example: .
(5) : A great blog that’s focused on information graphics and journalism, published by Gert K. Nielsen, a longtime news graphics editor in Denmark.
(6) by Geoff McGhee: Interviews with data graphics experts, including journalists and non-journalists. The package includes a large collection of linked resources, cleverly keyed to the videos, which are split into manageable short chapters. Geoff has been a journalist at The New York Times, ABCNews.com, and Le Monde Interactif.
(7) : Another excellent blog devoted to the topic, and also a great source of recent examples. The authors are engineers and interaction designers at Interactive Things, a design and technology studio in Switzerland.
(8) : Time to get your hands dirty! This useful blog post (from October 2010) also offers advice on how to make an information graphic.
(9) This blog post at Information Aesthetics (yet another fine blog about data graphics) summarizes a groundbreaking article () written by two Stanford University researchers in 2010.
(10) : A new book by Brian Suda provides a gentle introduction — suitable for journalism students. It’s not high-end theory like the work of , but the explanations are really well suited to people without a background in statistics or graphic design.
Know about a good resource I missed? Please add it in the comments!
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