Xiaoji Chen's Design Weblog » Health Infoscape Senseable City Lab partnered with GE to create new ways of understanding human health. Our team created a disease network by analyzing data from over 7.2 million anonymized electronic medical records, taken from between January 2005 and July 2010, across the United States. Barabasi’s lab has published their disease networks generated by genetic similarity in 2007. In our first attempt, diseases/disorders are considered associated if a patient has got them at the same time or sequentially. The resulting network gives us new insight as to how closely connected some seemingly un-related health conditions might be. I made this interactive map for the general public to browse the data. It is a huge network. The network vis was made with Flex and the visualization library Flare, and the user interface with Flash CS4. Team: (Senseable) Carlo Ratti, Eric Baczuk, Dominik Dahlem, Xiaoji Chen (General Electric) Camille Kubie, Aimee Atkinson Tools used: Flash, Flex, Flare, R Similar Posts
Xiaoji Chen's Design Weblog » Power Chart of Chinese Provinces Economist just posts an interactive visualization Chinese Equivalents on their website. It’s a very interesting approach. (Somehow I feel it has an psychological side-effect by saying one province is equivalent to France while it’s neighbor is equivalent to Kenya, though noted in terms of population.) I got curious how we can visualize how actually important the Chinese provinces are. Newman’s code on his website deals with raster image only. You can recognize in this map how unbalanced China is – the west is barely occupied due to challenging natural environment, and population keeps flowing from the middle towards the economic centers (Beijing and the southeast coast). What about looking at the provinces from a social network’s perspective? Tools used: Processing, Tulip, Illustrator Similar Posts
Graphical visualization of text similarities in essays in a book | munterbund.de The problem A collection of essays is collated for readers with visualizing graphics. The graphics should both serve as a thematic and structural overview of each text, and pose the essay in question in relation to the other essays in the book. They should be both an abbreviation of the text and the key to decoding the complex issues under discussion. The difficulty in developing appropriate graphics arises from the level of discussion of the key themes. The basis of visualization Detail view of graphic for Raphael Perret A data graphic – like a bar chart – depicts quantifiable data. Different ways of data selection A significant constraint in developing appropriate graphics arises from the manner of data collection. It is possible to divide data extracted from essays into two main groups: data that must be collected ”manually” (in our case, using human intelligence), and data that can be captured automatically by machine intelligence. Keywords Metadata Statistical data Structural data
Data Visualization Software | Tulip The Best Tools for Visualization Visualization is a technique to graphically represent sets of data. When data is large or abstract, visualization can help make the data easier to read or understand. There are visualization tools for search, music, networks, online communities, and almost anything else you can think of. Whether you want a desktop application or a web-based tool, there are many specific tools are available on the web that let you visualize all kinds of data. Here are some of the best: Visualize Social Networks Last.Forward: Thanks to Last.fm's new widget gallery, you can now explore a wide selection of extras to extend your Last.fm experience. Last Forward Friends Sociomap: Friends Sociomap is another Last.fm tools that generates a map of the music compatibility between you and your Last.fm friends. Fidg't:Fidg't is a desktop application that gives you a way to view your networks tagging habits. Fidg't The Digg Tools: One more: Digg Radar . YouTube: Visualize Music Musicovery Last.fm music visual tools: Amazon Data
Diagram Layout Software | Tom Sawyer Layout Tom Sawyer Layout is a Software Development Kit (SDK) that provides nested drawing data models and layout, labeling, and routing technology for applications that have their own graphical framework. Tom Sawyer Layout is intended for applications that already have graphics facilities in place, and that still need automatic layout capabilities. Tom Sawyer Layout provides a variety of high-quality layout algorithms with superior performance and scalability. Tom Sawyer Layout permits software developers to populate a nested drawing data model, set drawing specifications, choose a desired drawing style, and perform automatic drawing formatting. This drawing formatting sets node positions and sizes, adjusts line routing, and positions labels based on the software developer's precise specifications. The results can then be rendered in the application's graphical framework. Tom Sawyer Layout is available in several editions to accommodate development with your specific technologies and platforms.
D3.js - Data-Driven Documents Datasets - Gephi:Wiki Gephi sample datasets, in various format (GEXF, GDF, GML, NET, GraphML, DL, DOT). Feel free to add new datasets. Be sure you cite original authors. Supported graph formats are described here. Note that Gephi can open these files without the need to be unzipped. Web and Internet [GEXF] EuroSiS web mapping study: Mapping interactions between Science in Society actors on the Web of 12 European countries. [GML] Internet: a symmetrized snapshot of the structure of the Internet at the level of autonomous systems, reconstructed from BGP tables posted by the University of Oregon Route Views Project. Social networks [GML] Les Miserables: coappearance weighted network of characters in the novel Les Miserables. [GEXF] Hypertext 2009 dynamic contact network: contact network during the Hypertext 2009 conference. [GML] Zachary's karate club: social network of friendships between 34 members of a karate club at a US university in the 1970s. [TGZ] Github open source developers. Biological networks [GEXF] C.
How To Use Simple Excel Functions for Data Analysis In this series of video tutorials, ICIJ reporter Kate Willson demonstrates four basic yet essential Excel functions to assist with data analysis during investigative reporting. Want to see any other video tutorials about Computer-Assisted Reporting? Please let us know either in the comments below or at email@example.com. Interested in viewing more of our investigative reporting video tutorials? Subscribe to ICIJ's YouTube channel to be the first to know when they are released. Auto Fill We use Excel's "Auto Fill" function all the time when preparing data for analysis. Sorting and Filtering Sorting and Filtering are great and easy ways to look at your data. Concatenation Using Excel to join data from multiple cells is a powerful tool -- particularly if you're writing lengthy SQL queries. Pivot Tables You don't always need a complex SQL query to analyze data. Thanks for watching.
Features Gephi is a tool for data analysts and scientists keen to explore and understand graphs. Like Photoshop™ but for graph data, the user interacts with the representation, manipulate the structures, shapes and colors to reveal hidden patterns. The goal is to help data analysts to make hypothesis, intuitively discover patterns, isolate structure singularities or faults during data sourcing. It is a complementary tool to traditional statistics, as visual thinking with interactive interfaces is now recognized to facilitate reasoning. This is a software for Exploratory Data Analysis, a paradigm appeared in the Visual Analytics field of research. Real-time visualization Profit from the fastest graph visualization engine to speed-up understanding and pattern discovery in large graphs. Layout Layout algorithms give the shape to the graph. Metrics The statistics and metrics framework offer the most common metrics for social network analysis (SNA) and scale-free networks. Networks over time Input/Output