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Data Visualization: Modern Approaches

Data presentation can be beautiful, elegant and descriptive. There is a variety of conventional ways to visualize data - tables, histograms, pie charts and bar graphs are being used every day, in every project and on every possible occasion. However, to convey a message to your readers effectively, sometimes you need more than just a simple pie chart of your results. In fact, there are much better, profound, creative and absolutely fascinating ways to visualize data. Many of them might become ubiquitous in the next few years. Data presentation can be beautiful, elegant and descriptive. So what can we expect? Let’s take a look at the most interesting modern approaches to data visualization as well as related articles, resources and tools. 1. Trendmap 2007 Informationarchitects.jp presents the 200 most successful websites on the web, ordered by category, proximity, success, popularity and perspective in a mindmap. 2. Digg BigSpy arranges popular stories at the top when people digg them. 3.

Long Tail of user participation in Wikipedia (Ed H. Chi; joing work with Niki Kittur, Bryan Pendleton, and Bongwon Suh) As we were getting ready for the alt.CHI presentation last week at the CHI conference, I realized that the way we have been looking at the frequency of user edits in Wikipedia was not really getting at the root of the issue. What we really aspire to find out is "what processes are governing the users' participation in Wikipedia?" In the alt.CHI paper, we discovered that around 2003-2004, administrators in Wikipedia was making around 50% of edits! Moreover, when we analyzed the data using high-edit users (users with 10,000 edits or more), we got the same result. And when we computed the diff between all 58.5 million revisions of Wikipedia, we found that the number of words changed by admins (as a proportion of total words changed by everyone) was also waxing and waning from 10% to about 50% back down to near 10%. This clearly showed a very different picture.

Data Visualization: Modern Approaches Protovis Protovis composes custom views of data with simple marks such as bars and dots. Unlike low-level graphics libraries that quickly become tedious for visualization, Protovis defines marks through dynamic properties that encode data, allowing inheritance, scales and layouts to simplify construction. Protovis is free and open-source, provided under the BSD License. It uses JavaScript and SVG for web-native visualizations; no plugin required (though you will need a modern web browser)! Protovis is no longer under active development.The final release of Protovis was v3.3.1 (4.7 MB). This project was led by Mike Bostock and Jeff Heer of the Stanford Visualization Group, with significant help from Vadim Ogievetsky. Updates June 28, 2011 - Protovis is no longer under active development. September 17, 2010 - Release 3.3 is available on GitHub. May 28, 2010 - ZOMG! October 1, 2009 - Release 3.1 is available, including minor bug fixes. April 9, 2009 - First release on Google Code. Getting Started

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