Chart Porn Ghost Counties on Datavisualization.ch Earlier this year, Visualizing.org and Eyeo made an open call for designers and developers to create an interactive portrait of America by visualizing the 2010 census data. Jan Willem Tulp, a freelance information visualizer based in The Netherlands has recently published his submission for the competition called Ghost Counties. The visualization, developed in Processing, analyzes the numbers of homes and vacant homes in proportion to the population of all counties in the United States of America. The data itself was not very complex, but rather big, and the biggest challenge was to find a creative approach to visualize this data, but without using a map (which would be rather obvious since it’s about locations). The counties are represented by two concentric circles and the size of the outer bubble represents the total number of homes, the size of the inner bubble represents the number of vacant homes. The visualization achieves to clearly show exceptional states of counties.
Meerkat | AICML Fact Sheet Meerkat is a social network analysis application under development by Dr. Osmar Zaiane and his lab. It offers facilities for automated community mining, various layout algorithms for helpful visualizations, and timeframe event analysis for dynamic networks that have been observed at multiple points in time. For Meerkat ED, click here. If links do not work, try a short time later, or contact us.Download Meerkat Lite (v1.002, 2011-11-04, for Windows, Ubuntu, OSX)RegistrationDownload Mailing (or request atmeerkat-join@mailman.srv.ualberta.ca) Questions and Comments? Demo Principal InvestigatorsDr. Note: Meerkat Lite has been developed to offer useful functionality, including many features not common to other SNA software. Social networks are ubiquitous. Features:
A Tour through the Visualisation Zoo Related Content Visualizing System Latency Heat maps are a unique and powerful way to visualize latency data. Explaining the results, however, is an ongoing challenge. Browse this Topic: Queue on Reddit Jeffrey Heer, Michael Bostock, and Vadim Ogievetsky, Stanford University Thanks to advances in sensing, networking, and data management, our society is producing digital information at an astonishing rate. The goal of visualization is to aid our understanding of data by leveraging the human visual system's highly tuned ability to see patterns, spot trends, and identify outliers. Creating a visualization requires a number of nuanced judgments. This article provides a brief tour through the "visualization zoo," showcasing techniques for visualizing and interacting with diverse data sets. Most of the visualizations shown here are accompanied by interactive examples. Time-Series Data Time-series data—sets of values changing over time—is one of the most common forms of recorded data. Index Charts
Unfolding Maps: Getting Started in Processing Download Library Download the latest version of the Unfolding library. Unzip the archive and put the extracted Unfolding folder into the libraries folder of your Processing sketches. To find the Processing sketches location on your computer, open the Preferences window of the Processing application and look for the “Sketchbook location” item at the top. You will need to create the “libraries” folder if this is your first contributed library. Restart Processing, start a new sketch and create your first simple map. Hello World To get started, you need to include the Unfolding library via Sketch » Import Library and put the import statements at the top of your code. Create a reference to a “Map” object, i.e. Initialize a new map object and add the default event function for basic interaction (double-click to zoom and drag to pan the map). (You can specify P2D or P3D as renderer as the third parameter of the size() function, and Unfolding will use the appropriate one.) That’s it. Tips & Tricks
6 Gorgeous Facebook Visualizations Like every complex network, Facebook offers unlimited possibilities of visual representation of the various connections between its users. We've chosen six beautiful visualizations that will awaken the (visual) geek within you. You don't have to stop at merely watching. Some of the visualizations on the list come with tools that you can use to create beautiful Facebook visualizations of your own with very little effort. Enjoy! Know of a beautiful Facebook visualization? 1. This project visualizes all the data Facebook receives, on a global scale. 2. This wonderful illustration, created by Lee Byron from the Facebook data team, shows how Facebook has evolved from being a social network for universities to the global social networking powerhouse it is today, with over 200 million users. 3. Friend Wheel is a simple Facebook application that creates a radial graph out of all your Facebook friends. 4. 5. Still images really don't do justice to this one. 6.
Les 50 plus beaux graphiques... Studyscape Patrick Vuarnoz Suitmen Life Map par ritwikdey Web Trend Map v4.0 par Information Architects Killer Earth par Andrew Blauvelt Visualization of iTunes Libraries par Caleb Larsen Chart Arcs par Martin Dittus par Peter Crnokrak Netdisco Max Baker Networkism par Tatiana Plakhova Mo Money Mo Problems par Nick Hardeman Twingly Screensaver Time Magazine par Joe Lertola DriftNet par Norimichi Hirakawa Glocal par Jer Thorp Visualizing The Bible par Chris Harrison Barcode Plantage par Daniel A. Fyre par David Trowbridge, Micah Dowty Disarticulate par Ben Fry Visual Poetry par Boris Muller MSN History Visualization par MSN History Visualization flowerGarden par Greg Judelman, Maria Lantin Maeve insatallation par University of Applied Sciences Potsdam AmoebaAbstracts 1-3 par Marius Watz Static Mouvements par Piero Zagami Visualizing information flow in science par Moritz Stefaner Dewey Circles par Syed Reza Ali Gcrawler Marcin “vorg” Ignac Blooming Numbers par Yuri Lee Nexus Looks Del.icio.us par Kunal Anand TuneGlue Air Lines par Mario Freese
Pack Layout · mbostock/d3 Wiki Wiki ▸ API Reference ▸ Layouts ▸ Hierarchy ▸ Pack Layout Enclosure diagrams use containment (nesting) to represent the hierarchy. The size of each leaf node’s circle reveals a quantitative dimension of each data point. The enclosing circles show the approximate cumulative size of each subtree, but note that because of wasted space there is some distortion between levels; only the leaf nodes can be compared accurately. By flattening the hierarchy, the pack layout can also be used to create bubble charts: Like other classes in D3, layouts follow the method chaining pattern where setter methods return the layout itself, allowing multiple setters to be invoked in a concise statement. # d3.layout.pack() Creates a new pack layout with the default settings: the default sort order is by ascending value; the default children accessor assumes each input data is an object with a children array; the default size is 1×1. # pack(root) # pack.nodes(root) # pack.links(nodes) # pack.children([children])
SocialAction SocialAction is a social network analysis tool that integrates visualization and statistics to improve the analytical process. A journal article about SocialAction was recently published in IEEE Computer Graphics and Applications. See the full details in the papers below. SocialAction won a VAST Mini-Challenge award for uncovering hidden structure in social networks over time. There are also two recent conference publications about SocialAction! Overview SocialAction aims to help researchers understand their social network data. Although both statistical methods and visualizations have been used by network analysts, exploratory data analysis remains a challenge. Users can For each operation, a stable node layout is maintained in the network visualization so users can make comparisons. Participants Adam Perer, Ph.D., Computer Science (primary contact) Ben Shneiderman, Professor, Computer Science SocialAction in Action SocialAction: Analyzing the Social Network of US Senators on Vimeo. new!
Polymaps