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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 dis-moi où tu me plaîs Carte Graphe dis-moi où tu me plaîs exploration des annonces du site croisedanslemetro.com Pierre JdlF a mis tout ça sur Github avec des explications irrationnelles recherche Sélectionner une station 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 Lostalgic Lostalgic This project is based on the entire ABC's LOST TV show scripts, 115 episodes in 7 seasons, that I managed to parse from Lostpedia. I also parsed this page with additional information about hidden characters relations. My aim for this project is not (only) to visualize some properties and patterns out of the script but actually to allow to read and enjoy the series in a different way. I plan to add new views (will inform through twitter), more aimed to reveal global patterns in the script, and I will include cliffhangers and writing teams information. Find more information about Lostalgic in this great article and interview by Greg J. This project is dedicated to the Lost writers, to the open culture and, in particular, to the community that built Lostpedia. created by Santiago Ortiz

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.

Map your moves Data This map distills more than 4000 moves from over 1700 people, collected in an informal survey by WNYC, a New York based public radio station. For generating the geo–coordinates from the entered ZIP codes, I used the free bulk geocoder at gpsvisualizer.com. I did not check every single data row in detail, so a few of the moves might be misrepresented. Mapping As most moves occurred from, to or within the New York area, this area displayed enlarged in the white circle at the center of the graphic. Visual markers Each circle corresponds to one zip code area. Actually, it is consists of two overlaid circles: a red one for people moving out of the area, and a blue one for people moving to the area. Interaction Click one of the circles to inspect only moves to or from this area. Details On the right, you can find some statistics on why and when people moved to the selected areas.

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:

DATATELLING | Exploratory Data Analysis and Visualization 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.

Public/Private Public/Private is a game that explores the topic of privacy in our cities by focusing on where we find it. By choosing where in your city you seek privacy most often, you produce a visual graph representing those choices. Your graph is then combined with graphs generated by the rest of the global audience, creating a live data-visualization that illustrates how our experience of privacy changes at a local and global level. As more participants play Public/Private, more of the complexities of privacy in urban settings are illuminated. This game was created to accompany two ongoing research projects undertaken by the BMW Guggenheim Lab in Mumbai in cooperation with Partners for Urban Knowledge, Action & Research (PUKAR) and the Design Cell at the Kamla Raheja Vidyanidhi Institute for Architecture and Environmental Studies (KRVIA). The game experience for Public/Private was designed and developed by Collective Assembly and Tom van de Velde.

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

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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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