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Data Visualization Network of Resources

Data Visualization Network of Resources
Related:  sigma.js

ruby on rails - How to implement web-based graph editing for Neo4j A Carefully Selected List of Recommended Tools on Datavisualization When I meet with people and talk about our work, I get asked a lot what technology we use to create interactive and dynamic data visualizations. At Interactive Things, we have a set of preferred libraries, applications and services that we use regularly in our work. We will select the most fitting tool for the job depending on the requirements of the project. Sometimes a really simple tool is all you need to create something meaningful. On other occasions, a more multifaceted repertoire is needed. But how does one choose the right thing to use? That’s why we have put together a selection of tools that we use the most and that we enjoy working with. Let me answer the most likely questions right away: No, not everything find its’ way into this list, so you might not find your personal favorite.

* Datavisualization.ch Selected Tools The Work of Edward Tufte and Graphics Press Graphics Press LLC P.O. Box 430 Cheshire, CT 06410 800 822-2454 Edward Tufte is a statistician and artist, and Professor Emeritus of Political Science, Statistics, and Computer Science at Yale University. He wrote, designed, and self-published 4 classic books on data visualization. The New York Times described ET as the "Leonardo da Vinci of data," and Bloomberg as the "Galileo of graphics." He is now writing a book/film The Thinking Eye and constructing a 234-acre tree farm and sculpture park in northwest Connecticut, which will show his artworks and remain open space in perpetuity. Topics covered in this one-day course include: A new, widely-adopted method for presentations: meetings are smarter, more effective, 20% shorter. Fundamental design strategies for all information displays: sentences, tables, diagrams, maps, charts, images, video, data visualizations, and randomized displays for making graphical statistical inferences. New ideas on spectatorship, consuming reports.

How to Use Sigma.js with Neo4j I’ve done a few posts recently using D3.js and now I want to show you how to use two other great Javascript libraries to visualize your graphs. We’ll start with Sigma.js and soon I’ll do another post with Three.js. We’re going to create our graph and group our nodes into five clusters. You can see what a GEFX file looks like below. 01.<? 03. 04. 05. 06. 07. 08. 09. 10. 11. 12. 13. 14. 16. 17. 18. 19. 20. 22. 23. 24. In order to build this file, we will need to get the nodes and edges from the graph and create an XML file. 1.get '/graph.xml' do 2. 3. 4. builder :graph 5.end We’ll use Cypher to get our nodes and edges: 1.def nodes 2. neo = Neography::Rest.new 3. cypher_query = " START node = node:nodes_index(type='User')" 4. cypher_query << " RETURN ID(node), node" 5. neo.execute_query(cypher_query)["data"].collect{|n| {"id" => n[0]}.merge(n[1]["data"])} 6.end We need the node and relationship ids, so notice I’m using the ID() function in both cases. 01.def edges 02. neo = Neography::Rest.new 07. 08.

spaceengine - Home page Tools to Analyze Delicious Tags, Bookmarks and URLs Delicious is a widely used social bookmarking tools – it stores a wealth of information on people’s web preferences and on how useful they find each web page. There are a few tools that can retrieve that data and represent it to you in more or less comprehensible way. Analyze any site / URL Similicio.us shows which domains your site can be associated with based on the preferences of those who bookmarked it. Delicious URL search will trigger most popular tags the page was associated with as well as recent descriptions members used to bookmark it. Cloudalicious (warning: works very slow) is an interesting tool that will grab all tags associated with the URL and visualize them in a graph. Analyze tags: Delicious Tag Browser is meant to graphically represent relation between tags. Revealicious is a set of graphic visualization tools for your Delicious account that allow you to analyze your tags. TagsCloud is an interactive visualization inspired from del.icio.us own tags cloud. Track Delicious:

Civic Infographics By Giulio Frigieri The importance of perception for analysis and communication through infographics In his book “Graph design for the eye and mind”, Stephen Kosslyn asserts that “a good graph forces the reader to see the information the designer wanted to convey” and this would be the very “difference between graphics for data analysis and graphics for communication”[Kosslyn, 2006]. But are there any specific instances in which we can say that a data-based graphic is designed to describe, not to analyze? The fact that an explanatory text can be added – regardless of how concise or verbose it is – is not enough to imply that a chart’s nature is prevalently descriptive. In this line of thought, we must ask ourselves whether the two functional elements of analysis and communication can ever be separated, or even controlled. Line graphs – the most popular according to Edward Tufte [Tufte, 1983] – and bar charts, for example, are usually employed to describe. Sources: Kosslyn S.M. Fienberg S.

Using Sigma.js with Neo4j I’ve done a few posts recently using D3.js and now I want to show you how to use two other great Javascript libraries to visualize your graphs. We’ll start with Sigma.js and soon I’ll do another post with Three.js. We’re going to create our graph and group our nodes into five clusters. You’ll notice later on that we’re going to give our clustered nodes colors using rgb values so we’ll be able to see them move around until they find their right place in our layout. We’ll be using two Sigma.js plugins, the GEFX (Graph Exchange XML Format) parser and the ForceAtlas2 layout. You can see what a GEFX file looks like below. In order to build this file, we will need to get the nodes and edges from the graph and create an XML file. We’ll use Cypher to get our nodes and edges: We need the node and relationship ids, so notice I’m using the ID() function in both cases. So far we have seen graphs represented as JSON, and we’ve built these manually. Credit goes out to Alexis Jacomy and Mathieu Jacomy.

Part 1: The essential collection of visualisation resources This is the first part of a multi-part series designed to share with readers an inspiring collection of the most important, effective, useful and practical data visualisation resources. The series will cover visualisation tools, resources for sourcing and handling data, online learning tutorials, visualisation blogs, visualisation books and academic papers. Your feedback is most welcome to help capture any additions or revisions so that this collection can live up to its claim as the essential list of resources. This first part presents the data visualisation tools associated with conducting analysis, creating effective graphs and implementing business intelligence operations. Please note, I may not have personally used all tools presented but have seen sufficient evidence of their value from other sources. Microsoft Excel Find out more information | Cost: Trial > under £100/$150 per license | Tags: Spreadsheet, Office, Graphing Status: Ongoing (July 7, 2011) Open Office Calc Tableau Desktop

Presenteren met Prezi | Blog rondom het nieuwe boek Presenteren met Prezi van Hedwyg van Groenendaal The Functional Art: An Introduction to Information Graphics and Visualization hairball/ Jun 25, 2012 Network visualization is a topic as complex as many of the hairballs it produces but Sigma.JS is designed to break through the clutter and graph networks that are more readable and user-friendly. It’s creator, Alexis Jacomy, has really pushed the practice of network visualization forward with this tool. He has combined elements of existing examples in new ways that seem to work better together. Especially worth noting are the ‘hide node‘ and ‘fish-eye‘ examples. His hard work really pays off in the speed and responsiveness of the tool. Interestingly, Santiago Ortiz developed a network visualization of data driven resources that uses a lot of the same principles.

22 free tools for data visualization and analysis You may not think you've got much in common with an investigative journalist or an academic medical researcher. But if you're trying to extract useful information from an ever-increasing inflow of data, you'll likely find visualization useful -- whether it's to show patterns or trends with graphics instead of mountains of text, or to try to explain complex issues to a nontechnical audience. There are many tools around to help turn data into graphics, but they can carry hefty price tags. The cost can make sense for professionals whose primary job is to find meaning in mountains of information, but you might not be able to justify such an expense if you or your users only need a graphics application from time to time, or if your budget for new tools is somewhat limited. If one of the higher-priced options is out of your reach, there are a surprising number of highly robust tools for data visualization and analysis that are available at no charge. Data cleaning DataWrangler

Visualização desenvolvida por Santiago Ortiz que agrega dados sobre visualização de dados, possibilitando acessar um vasto banco de dados de referências mundiais neste campo. by izabelgoudart Aug 25

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