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Walrus - Graph Visualization Tool

Walrus - Graph Visualization Tool
Source Code Available The source code to Walrus is now available under the GNU GPL. You may download the source code below. Description Walrus is a tool for interactively visualizing large directed graphs in three-dimensional space. It is technically possible to display graphs containing a million nodes or more, but visual clutter, occlusion, and other factors can diminish the effectiveness of Walrus as the number of nodes, or the degree of their connectivity, increases. Walrus computes its layout based on a user-supplied spanning tree. Walrus uses 3D hyperbolic geometry to display graphs under a fisheye-like distortion. Walrus is being developed by Young Hyun at CAIDA. Applicability Please note that Walrus currently has the following requirements, restrictions, or limitations which may render it unsuitable for a given problem domain or dataset: Only directed graphs are supported.Only connected graphs with reachable nodes are supported. Galleries Implemented Features Requirements Download

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SoNIA - Social Network Image Animator Social Network Image Animator What is it? SoNIA is a Java-based package for visualizing dynamic or longitudinal "network" data. Revised Graphic Organizers Make Mapping Out Ideas Easy—and Savable! Join us on Facebook to get the latest news and updates. Become a Fan ReadWriteThink couldn't publish all of this great content without literacy experts to write and review for us. Sample Workflows — Kepler Kepler comes with a number of demo workflows that can be found in your KeplerData/workflows/module/outreach/demos directory. Highlighted here are two workflows from the demos/getting-started directory. Lotka-Volterra Workflow Author: Rich Williams, NCEAS The Lotka-Volterra workflow solves the classic Lotka-Volterra predator prey dynamics model, which describes the relative populations of a predator and its prey over time using two coupled differential equations: one that describes how predator population changes (dn2/dt = -d*n2 + b*n1*n2); and one that describes how prey population changes (dn1/dt = r*n1 - a*n1*n2).

Treemaps for space-constrained visualization of hierarchies Started Dec. 26th, 1998 by Later updates by Ben Shneiderman and Catherine Plaisant - Last update Sept 2014 Our treemap products: Treemap 4.0: General treemap tool (Free demo version, plus licensing information for full package) PhotoMesa: Zoomable image library browser (Free demo version, plus licensing information for full package) Treemap Algorithms and Algorithm Animations (Open source Java code) A History of Treemap Research at the Social Network Analysis: A Systematic Approach for Investigating Social network analysis (SNA) is often confused with social networking sites, such as Facebook, when in fact, SNA is an analytical tool that can be used to map and measure social relations. Through quantitative metrics and robust visual displays, police can use SNA to discover, analyze, and visualize the social networks of criminal suspects. SNA, a social science methodology, serves as a valuable tool for law enforcement. While technologically sophisticated, SNA proves easy to employ. Using available data, police departments structure the examination of an offender’s social network in ways not previously possible.

Information design Information design is the practice of presenting information in a way that fosters efficient and effective understanding of it. The term has come to be used specifically for graphic design for displaying information effectively, rather than just attractively or for artistic expression. Information design is closely related to the field of data visualization and is often taught as part of graphic design courses.[1] Etymology[edit] The term 'information design' emerged as a multidisciplinary area of study in the 1970s.

Evernote Corporation Plan your next trip Keep all of your itineraries, confirmations, scanned travel documents, maps, and plans in Evernote, so you’ll have them when you need them. Jigsaw - Visual Analytics for Investigative Analysis Summary Investigative analysts and researchers acquire clues and connect small bits of evidence to uncover larger plans, stories, or narratives, and to simply gain a better understanding of the information. Often, the individual bits of evidence are short text documents or spreadsheets, and analysts must examine large collections of such documents in order to "put the pieces together" and formulate a well-supported hypothesis about actions that may occur in the future. As the number of documents to examine rises, it becomes more and more challenging for analysts to understand the data and make judgments about it.