Colorbrewer: Color Advice for Maps. iWantHue. Graphical Bios. Stunning. Simple. Processing.js. Jsundram/streamgraph.js. World Bank Dataviz. The Overview Project » How Overview turns Documents into Pictures. Overview produces intricate visualizations of large document sets — beautiful, but what do they mean?
These visualizations are saying something about the documents, which you can interpret if you know a little about how they’re plotted. There are two visualizations in the current prototype version of Overview, and both are based on document clustering. The first is the items plot, which grew out of the proof-of-concept system we presented a year ago. Every document is a dot. Similar documents get pulled together to form visible groups, that is, clusters. Overview also has a “tree” view. The tree view and the items plot show the same thing, just in different ways. Extracting Key Words All of Overview’s clustering depends on grouping similar documents together, but what does that mean?
MALLET homepage. Livehoods. LUMAscapes. Easel.ly. Roambi Publisher. Infographics and social media activity reports - Brought to you by www.getabout.me. Infographics & Data Visualizations. Data Science Toolkit. Infochimps. ITO - Road Fatalities USA. This web site and the information it contains is provided as a public service by ITO World Ltd, using data supplied by the National Highway Traffic Safety Administration (NHTSA), U.S.
Department of Transportation (DOT). ITO World Ltd makes no claims, promises or guarantees about the accuracy, completeness, or adequacy of the contents of this web site and expressly disclaims liability for errors and omissions in the contents of this web site. No warranty of any kind, implied, expressed or statutory, including but not limited to the warranties of non-infringement of third party rights, title, merchantability, fitness for a particular purpose and freedom from computer virus, is given with respect to the contents of this web site or its links to other Internet resources. Users of the service should note that the NHTSA/DOT makes no claims, promises or guarantees about the accuracy, completeness, or adequacy of the road fatality data used within this web site.
Fast Analytics and Rapid-fire Business Intelligence from Tableau Software. d3.js. Visualizing Yahoo! Mail. About Google+ Ripples - Google+ Help. Google+ Ripples creates an interactive graphic of the public shares of any public post or URL on Google+ to show you how it has rippled through the network and help you discover new and interesting people to follow.
Ripples shows you: People who have reshared the link will be displayed with their own circle. Inside the circle will be people who have reshared the link from that person (and so on). Circles are roughly sized based on the relative influence of that person. The comments users added when they reshared a link are displayed in the sidebar of Ripples. At the bottom of the Ripples page, you can play an animated version of the visualization that shows how the link was shared over time. Beneath the timeline on the Ripples page statistics on the link. While Ripples displays a lot of cool information, you’re not actually seeing all the action that’s taken place. Not sure if a post is public? Blog » Hexbins! Binning is a general term for grouping a dataset of N values into less than N discrete groups.
These groups/bins may be spatial, temporal, or otherwise attribute-based. In this post I’m only talking about spatial (long-lat) and 2-dimensional attribute-based (scatterplot) bins. Such binnings may be thought of as 2D histograms. This may make more or less sense after what lies beneath. If you’re just after that sweet honey that is my code, bear down on my Github repository for this project — hexbin-js.
Migrations Map: Where are migrants coming from? Where have migrants left? World. APEXvj - Visualize your favourite tunes online. Google Correlate. Chart.io. The art of data visualization. Mam_news's Bookmarks (Data Visualizations) Axiis : Data Visualization Framework.
Protovis. Protovis composes custom views of data with simple marks such as bars and dots.