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Despite the recent explosion of web based cartography tools, making effective maps for data visualization remains a challenge. While tools like Google Maps are great for helping navigate the world they are often poorly suited for thematic mapping, as many features like roads and cities only get in the way of telling compelling stories with data. In fact, even the distance between places can be a distraction – who cares how far away Alaska is when the goal is to make a simple comparison between US states? To help overcome some of the limitations with existing mapping tools Sunlight Lab is releasing ClearMaps, an ActionScript framework for interactive cartographic visualization. In addition to giving designers and developers more control over presentation the project aims to address some of the common technical challenges faced when building interactive, data driven maps for the web. ClearMaps is designed as a lightweight, flexible set of tools for building complex data visualizations. It is a framework not a plug-and-play component (though it could be a starting point for those wishing to make reusable tools).

Despite the recent explosion of web based cartography tools, making effective maps for data visualization remains a challenge. While tools like Google Maps are great for helping navigate the world they are often poorly suited for thematic mapping, as many features like roads and cities only get in the way of telling compelling stories with data. In fact, even the distance between places can be a distraction – who cares how far away Alaska is when the goal is to make a simple comparison between US states? To help overcome some of the limitations with existing mapping tools Sunlight Lab is releasing ClearMaps, an ActionScript framework for interactive cartographic visualization. In addition to giving designers and developers more control over presentation the project aims to address some of the common technical challenges faced when building interactive, data driven maps for the web. ClearMaps is designed as a lightweight, flexible set of tools for building complex data visualizations. It is a framework not a plug-and-play component (though it could be a starting point for those wishing to make reusable tools).

Despite the recent explosion of web based cartography tools, making effective maps for data visualization remains a challenge. While tools like Google Maps are great for helping navigate the world they are often poorly suited for thematic mapping, as many features like roads and cities only get in the way of telling compelling stories with data. In fact, even the distance between places can be a distraction – who cares how far away Alaska is when the goal is to make a simple comparison between US states? To help overcome some of the limitations with existing mapping tools Sunlight Lab is releasing ClearMaps, an ActionScript framework for interactive cartographic visualization. In addition to giving designers and developers more control over presentation the project aims to address some of the common technical challenges faced when building interactive, data driven maps for the web. ClearMaps is designed as a lightweight, flexible set of tools for building complex data visualizations. It is a framework not a plug-and-play component (though it could be a starting point for those wishing to make reusable tools).

Over the past few years, one of the most important shifts in the digital world has been the move from the wide-open Web to semiclosed platforms that use the Internet for transport but not the browser for display. It’s driven primarily by the rise of the iPhone model of mobile computing, and it’s a world Google can’t crawl, one where HTML doesn’t rule. And it’s the world that consumers are increasingly choosing, not because they’re rejecting the idea of the Web but because these dedicated platforms often just work better or fit better into their lives (the screen comes to them, they don’t have to go to the screen).

What made me fall of my chair is the methodology/architecture part of this statement. It’s hard enough (but doable) to use RDF to map philosophically similar APIs. It’s a non-starter to use it to bridge architectural and methodological differences. I have spent a fair amount of time looking at Semantic Web technologies in the context of modeling IT systems (see the “semantic tech” category of this blog). While I think they would be a great foundation I don’t see them ever coming anywhere near what Reuven describes.

Microsoft Research who brought us some wonderful technologies such as the incredible Photosynth continue to impress with a much improved web mapping application integrated with the company's new Bing search engine. During the TED 2010 conference, Microsoft engineer Blaise Aguera y Arcas demoed the new Bing augmented reality maps showing real-time registration of video taken with a smart phone and street-view type maps. He showed how the live video can be overlayed over the static images and additional information about the area can be accessed via a Web interface. Much of this is made possible because of the advanced computer vision technology that has been developed in the past decade at Microsoft Research. The Seadragon technology is the back-end that makes it possible to manipulate such vast amounts of data in real-time. Microsoft has also integrated Photosynth and Worldwide telescope into their maps product. You are probably wondering what does this have to do with robotics other than the fact that it is a very impressive application? I can imagine robots using Bing maps to keep localized within a city. One of the most difficult and important problem in robotics is that of Simultaneous Localization and Mapping. Bing maps solve the mapping problem and the new vision techniques (with a bit of help from GPS) can be used to solve the localization problem. The registered video can be used by a robot to localized itself when it goes out to buy your weekly groceries.  You can watch the 10-minute demo below; I bet that it won't be long before Microsoft makes these new features available to us all for free.

Piotr Zalewa has created a really great playground, jsFiddle, for testing sample code and playing with the Web. With an area for the holy trinity of the Web (HTML, CSS, JS) and an output region, you can get right to hacking. It goes beyond this though. You can also add resources, an Ajax echo backend, and auto load from a slew of JavaScript frameworks. You can also check out the examples and see great stuff such as Processing in action. And the finishing touch, share and embed. Piotr wrote all of this using CodeMirror and MooTools. Nice! Having worked on Bespin, and developed a playground like this (looking forward to show a new mobile one soon!) I appreciate the work!

In separate keynote addresses in Silicon Valley, two Internet pioneers gave different takes on the future of the network of networks Monday (May 24). Vint Cerf, co-developer of the Net's TCP/IP protocol, shared his thoughts with developers of the smart electric grid, seen as a massive embedded extension to the Internet. Larry Roberts, who helped launch the forerunner of the Internet, explained his ideas for remedying the growing congestion that plagues the Web today. Smart grid developers can learn from the lessons of the Internet, Cerf told attendees at Connectivity Week here. They should follow the model of the Net in creating a layered architecture with plenty of room for flexibility in areas that cannot be anticipated today, he said in a keynote at Connectivity Week.

“CMS” stands for Compact Muon Solenoid, a general-purpose particle physics detector built on the Large Hadron Collider. The CMS project posted a few comics which provide a nice, simple (if somewhat cheesy) explanation of what the CMS/LHC does. The LHC generates massive amounts of data of all different varieties, which is distributed across a worldwide grid. It sends status messages to some of the computers, job monitoring info to other computers, bookkeeping info still elsewhere, and so on. This means that each location has specialized queries it can do on the data it has, but up until now it’s been very difficult to query across the whole grid. Enter the Data Aggregation System, designed to allow anything to be queried across all of the machines.

As we reported last week, search engine Cuil was unceremoniously shut down on Thursday, and there were reports that employees were told to go home and forget about getting paid. New sources tells us that Cuil was in the final stages of an acquisition as of last Wednesday, and everything was in place except the final signatures. Then the deal fell apart for some reason. Or put another way, Cuil found one last way to fail.

WebP is a method of lossy compression that can be used on photographic images. WebP offers compression that has shown 39.8% more byte-size efficiency than JPEG for the same quality in a large scale study of 900,000 images on the Web. The degree of compression is adjustable so a user can choose the trade-off between file size and image quality.

The Control Gallery is a directory of over 900 controls and components to use in your own applications. You will find everything from simple controls to full e-commerce components.

Today I'm excited to share the project a small team of amazing people and I have been working on for the past two years; HipHop for PHP. With HipHop we've reduced the CPU usage on our Web servers on average by about fifty percent, depending on the page. Less CPU means fewer servers, which means less overhead. This project has had a tremendous impact on Facebook. We feel the Web at large can benefit from HipHop, so we are releasing it as open source this evening in hope that it brings a new focus toward scaling large complex websites with PHP. While HipHop has shown us incredible results, it's certainly not complete and you should be comfortable with beta software before trying it out. HipHop for PHP isn't technically a compiler itself. Rather it is a source code transformer. HipHop programmatically transforms your PHP source code into highly optimized C++ and then uses g++ to compile it. HipHop executes the source code in a semantically equivalent manner and sacrifices some rarely used features — such as eval() — in exchange for improved performance. HipHop includes a code transformer, a reimplementation of PHP's runtime system, and a rewrite of many common PHP Extensions to take advantage of these performance optimizations.

So after all that you are probably asking, “What is SimpleCV?” It is an open source computer vision framework that lowers the barriers to entry for people to learn, develop, and use it across the globe. Currently there are a few open source vision system libraries in existence, but the downside to these is you have to be quite the domain expert and knowledgeable with vision systems as well as know cryptic programming languages like C. Where SimpleCV is different, is it is “simple”. It has been designed with a web browser interface, which is familiar to Internet users everywhere. It will talk to your webcam (which most computers and smart phones have built in) automatically. It works cross platform (Windows, Mac, Linux, etc). It uses the programming language Python rather than C to greatly lower the learning curve of the software. It sacrifices some complexity for simplicity, which is needed for mass adoption of any type of new technology.

A new network design that avoids the need to convert optical signals into electrical ones could boost capacity while reducing power consumption.

Researchers at MIT’s McGovern Institute for Brain Research are working on a new mathematical model to mimic the human brain's ability to identify objects. The model can predict human performance on certain visual-perception tasks suggesting it’s a good indication of what's actually happening in the brain. Researchers are hoping the new findings will make their way into future object-recognition systems for automation, mobile robotics, and other applications.

The R programming language was featured about a year ago in a New York Times article (http://bit.ly/iaqQ). I've been an R user since 2000, so I've collected some resources for people who want to get started with R.   The first place to start is the R Project web site at http://www.r-project.org/. Next, you'll actually want to install R itself. There are several options, depending on your environment.

The MATLAB team at MathWorks tested performance scaling of the backslash ("\") matrix division operator to solve for x in the equation A*x = b. In their testing, matrix A occupies far more memory (290 GB) than is available in a single high-end desktop machine—typically a quad core processor with 4-8 GB of RAM, supplying approximately 20 Gigaflops. Therefore, they spread the calculation across machines. In order to solve linear systems of equations they need to be able to access all of the elements of the array even when the array is spread across multiple machines. This problem requires significant amounts of network communication, memory access, and CPU power. They scaled up to a cluster in EC2, giving them the ability to work with larger arrays and to perform calculations at up to 1.3 Teraflops, a 60X improvement. They were able to do this without making any changes to the application code. Here's a graph showing the near-linear scalability of an EC2 cluster across a range of matrix sizes with corresponding increases in cluster size for MATLAB's parallel backslash operator:

We had to cover monads eventually, and there are many great monad tutorials out there (see, for example, here: http://www.haskell.org/haskellwiki/Tutorials#Using_monads). In fact, there are web resources concerned solely with organizing the many monad tutorials available in the wild, and developing new monad tutorials seems to be a popular sport in the Haskell community.Today, Ralf Lämmel's lecture goes back to the roots, essentially revisiting Wadler's "The essence of functional programming"—the 1992 paper that discovered monads and popularized their use in functional programming. Ralf Lämmel's lecture and accompanying code distribution show Wadler's seminal insight: those original scenarios and observations still make sense today. Indeed, Simon Marlow (a Haskell/GHC high priest @ MSR Cambridge) recently noted: "it's still the best monad tutorial" (see http://twitter.com/simonmar/status/21397398061).

Flare is an ActionScript library for creating visualizations that run in the Adobe Flash Player. From basic charts and graphs to complex interactive graphics, the toolkit supports data management, visual encoding, animation, and interaction techniques. Even better, flare features a modular design that lets developers create customized visualization techniques without having to reinvent the wheel. View the demos and sample applications to see a few of the visualizations that flare makes it easy to build. To begin making your own visualizations, download flare and work through the tutorial. You should also get familiar with the API documentation. Need more help? Visit the help forum (you'll need a SourceForge login to post). Flare is open-source software released under a BSD license, meaning it can be freely deployed and modified (and even sold for $$). Flare's design was adapted from its predecessor prefuse, a visualization toolkit for Java

At three separate industry events last week, engineers said they are gearing up to deliver in 2011 chips that can handle serial data streams running at 25 Gbits/second to drive next-generation 100 and 400 Gbit/second networks. But they say it's still a mystery how—or if—they can deliver follow-on components for the terabit networks today's Internet data centers are already demanding. The kinds of jobs required to run today's Web 2.0 services such as Google and Facebook can completely overwhelm current 10 Gbit/s Ethernet links in the warehouse-sized data centers those companies use. Such data centers could use hundreds of 100 Gbit/s Ethernet links today, although standards for such networks are still being completed.

A deluge of high-energy physics data is headed toward servers in Geneva, Switzerland, later this month. That's because the European Organization for Nuclear Research (CERN) now says it plans to restart its Large Hadron Collider (LHC) soon for a run that could last as long as two years at a collision energy of seven TeV (tera–electron volts, 3.5 TeV per beam). As CERN ramps up the world's most powerful particle accelerator to operate well beyond its previous best performance, the lab's computer systems must likewise be tuned so they can properly capture and analyze all of this new output.