Processing.js 1.4.7 released! Since our last release, 1.4.1, Processing.js has been given a bit of a source code overhaul, culminating in a new release: 1.4.7! This release adds in new functionality that you might already know from Processing 2.0, but was missing in Processing.js such as new methods in PVector and XML.
According to the latest Food Price Watch, 1/4 to 1/3 of all food produced for human consumption is lost or wasted, annually. In regions such as Sub-Saharan Africa and South Asia, which are plagued with undernutrition, this translates into 400-500 calories lost per person, per day. Check out how much food is lost or wasted in your region. Source: Lipinski, et al., “Reducing Food Loss and Waste”; Gustavsson et al., “Global Food Losses and Food Waste.”
The Overview Project » How Overview turns Documents into Pictures Overview produces intricate visualizations of large document sets — beautiful, but what do they mean? These visualizations are saying something about the documents, which you can interpret if you know a little about how they’re plotted. There are two visualizations in the current prototype version of Overview, and both are based on document clustering. The first is the items plot, which grew out of the proof-of-concept system we presented a year ago. Every document is a dot.
MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text. MALLET includes sophisticated tools for document classification: efficient routines for converting text to "features", a wide variety of algorithms (including Naïve Bayes, Maximum Entropy, and Decision Trees), and code for evaluating classifier performance using several commonly used metrics. [Quick Start] [Developer's Guide] In addition to classification, MALLET includes tools for sequence tagging for applications such as named-entity extraction from text. Algorithms include Hidden Markov Models, Maximum Entropy Markov Models, and Conditional Random Fields. These methods are implemented in an extensible system for finite state transducers.
LUMA Partners » LUMAscapes LUMA Partners painstakingly compiles sector landscapes (“LUMAscapes”) to organize what can be a very confusing ecosystem. We have mapped each of the increasingly overlapping key sectors of digital media: DISPLAY, SEARCH, VIDEO, MOBILE, SOCIAL, COMMERCE, and GAMING. We have also mapped the leading suppliers of capital – the DIGITAL CAPITAL LUMAscape, and the strategic aquirors – the STRATEGIC BUYER LUMAscape. We understand these LUMAscapes are not perfect.
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Steal this server! Grab this entire site as a free, self-contained, ready-to-run VM Independence - Never worry about the provider going offline, or charging once you're hooked. Security - Run on your intranet, so customer information stays within the firewall. Scalability - No API limits. Run a cluster of as many instances as you need.
ITO - Road Fatalities USA This web site and the information it contains is provided as a public service by ITO World Ltd, using data supplied by the National Highway Traffic Safety Administration (NHTSA), U.S. Department of Transportation (DOT). ITO World Ltd makes no claims, promises or guarantees about the accuracy, completeness, or adequacy of the contents of this web site and expressly disclaims liability for errors and omissions in the contents of this web site. No warranty of any kind, implied, expressed or statutory, including but not limited to the warranties of non-infringement of third party rights, title, merchantability, fitness for a particular purpose and freedom from computer virus, is given with respect to the contents of this web site or its links to other Internet resources. Users of the service should note that the NHTSA/DOT makes no claims, promises or guarantees about the accuracy, completeness, or adequacy of the road fatality data used within this web site.
Google+ Ripples creates an interactive graphic of the public shares of any public post or URL on Google+ to show you how it has rippled through the network and help you discover new and interesting people to follow. Ripples shows you: People who have reshared the link will be displayed with their own circle. Inside the circle will be people who have reshared the link from that person (and so on). Circles are roughly sized based on the relative influence of that person.
blog » Hexbins! Binning is a general term for grouping a dataset of N values into less than N discrete groups. These groups/bins may be spatial, temporal, or otherwise attribute-based. In this post I’m only talking about spatial (long-lat) and 2-dimensional attribute-based (scatterplot) bins.
Migrations Map: Where are migrants coming from? Where have migrants left?
I often get cheers and good ideas from several people around me. You know who you are, thank you! Would also like to point out that all the rocks and the beautiful hand model where made by Jonny Ree. Jani Länsimäki made the basis for the APEXvj visual line where it could evolve to what we see today. A lot of it is still here. It's made for the love of music and realtime graphics.
The art of data visualization
mam_news's Bookmarks (Data Visualizations)
Axiis: Data Visualization Framework! open source data visualization Axiis is an open source data visualization framework designed for beginner and expert developers alike. Whether you are building elegant charts for executive briefings or exploring the boundaries of advanced data visualization research, Axiis has something for you.
Interactive Weather Charts