If you’ve always wanted to try your hand at scientific data visualization, but don’t have a data science or computer programming background, try out NodeBox. It’s a tool suite from Experimental Media Research Group in Antwerp, Belgium and offers 2D and 3D visualizations (with animations and interactivity) via a nice and simple drag-and-drop interface.
Using our open-source tools we enable designers to automate boring production challenges, visualize large sets of data and access the raw power of the computer without thinking in ones and zeroes. Our tools integrate with traditional design applications and run on many platforms.
Another entry in the growing HPC Remote Visualization space comes from “NICE” software, who has just announced a new version of their EnginFrame2013 product that offers tools for creating and managing remote visualization resources.
Designed for technical computing users in a broad range of markets (Oil&Gas, Automotive, Aerospace, Medical, Finance, Research, and more), EnginFrame simplifies engineers’ and scientists’ workflows through its intuitive, self-documenting interfaces, increasing productivity and streamlining data and resource management.
Leveraging all the major HPC job schedulers and remote visualization technologies, EnginFrame translates user clicks into the appropriate actions to submit HPC jobs, create remote visualization sessions, monitor workloads on distributed resources, manage data and many more.
Princeton University is having a new “Art of Science” competition, allowing students and researchs to contribute scientific visualizations of their work in art-gallery form, competing for (rather meager, unfortunately) prizes.
The three prize-winners will share $500, divided into shares of $250, $154.51 and $95.49 in accordance with the aesthetically pleasing golden ratio. Another 40 images are included in Princeton’s Art of Science 2013 exhibit, which opened on Friday in the atrium of Princeton’s Friend Center. The works were chosen from 170 images submitted from 24 different departments across campus.
The theme was of “Connections”, focusing on cross-disciplinary research. Follow the link to the full gallery of some of the best work.
Robert Kosara has a nice writeup on a scatterplot visualization in The New York Times back in 2010, and a modern recreation of it from Nathan Yau in D3.
The scatterplot shows men’s wages on the horizontal axis, women’s on the vertical. There is a dot for each type of job, like nurses, programmers, physicians, etc. The coloring groups them into larger occupation categories. If men and women made the same amount of money in one particular job, that point would sit on the main diagonal. That diagonal is clearly pointed out by the heavy black line. For jobs where men make more, the point moves to the right of the diagonal, and thus ends up below it.
If you like the graphic, make sure you also check out Nathan’s followup where he addresses a bit of a flub afterwards where it got picked up by CNN without proper attribution.
In a startling piece of data exposure and transparency, Stephen Wolfram (of Mathematica and WolframAlpha fame) has published a load of visualizations of data automatically collected about his life going all the way back to 1990. The result is several graphs like the one above analysing keystrokes, email, calendaring, and more.
Again, there are some life trends visible. The gradual decrease in the early 1990s reflects me reducing my involvement in day-to-day management of our company to concentrate on basic science. The increase in the 2000s is me jumping back in, and driving more and more company projects. And the peak in early 2009 reflects with the final preparations for the launch of Wolfram|Alpha. (The individual spikes, including the all-time winner August 27, 2006, are mostly weekend or travel days specifically spent “grinding down” email backlogs.)
One of the winners at this summer’s SciDAC Visualization Night was an impressive visualization of a massive 8.0 earthquake on the San Andreas fault.
The simulation follows the rapid expansion of an earthquake wave front on the San Andreas fault as it approaches the city of San Diego. The strongest motions correspond to a white color and the weakest, a red color, with the ground motion magnitude represented as a height field.
The simulation took almost a quarter-million cores of Jaguar and Kraken (both NSF machines at ORNL), and shows the leading edge of the shock front.
TACC’s Kelly Gaither gave a nice presentation in the Dell booth at SC on the trials and tribulations of performing data analysis and visualization “At scale”. In her context, “at scale” means on large HPC-scale datasets.
Visualization is one of the most important and commonly used methods of analyzing and interpreting digital assets. For many types of computational research, it is the only viable means of extracting information and developing understanding from data. However, non-visual data analysis techniques—statistical analysis, data mining, data reduction, etc.—also play integral roles in many areas of knowledge discovery.
TACC is using technology that I’ve begun deploying at my employer combining dedicated visualization resources with large-shared filesystems (eliminating file transfers) and client-server tools. Her talk focuses on their software (Longhorn Portal) & hardware (Longhorn & Stallion) deployments, unfortunately lacking much detail on Impact of the system beyond fuzzy “works great” remarks. It’s a good talk if you’re unfamiliar with the problems of interactive visualization at the tera/petascale, and Kelly is always fun to listen to.
The current issue of Popular Science, the November 2011 issue, is all about the incredible quantities and capabilities of data and visualization. With several articles from big names like Seth Loyd, and visualizations from guys like Jan Willem Tulp and Jer Thorp, it’s sure to be a winner.
One of US President Obama’s platforms during the election battle was to add several degrees of transparency to government, embracing open standards and visualization. Last week at the Tech@State event there was lots of discussion on the topic, and an article on NextGov recaps their progress and some of the attempts underway.
Several projects have recently been launched, including a map of sexual orientation and gender identity issues in South and Central Asia and another map charting specific incidents of anti-Semitism in Europe by country. Since the site is part of the Open Government Initiative, all data is in the public domain and made embeddable for easier sharing.
I still remember my old Geocities account.. My first experiments with HTML, full of frames, tables, and blink tags. And I wasn’t alone, millions of people cut their teeth on the web via Geocities pages that broke every design rule and tricked browsers into going far beyond their design intent. Sadly (thankfully?) Geocities is gone, replaced by MySpace, FaceBook, and Twitter, but before it disappeared one group decided to mine it. This video is the result of their massive 650Gig dataset, visualized as a City.
In an heroic effort to preserve 10 years of collaborative work by 35 million people, the Archive Team made a backup of the site just before it shut down. The resulting 650 Gigabyte bittorrent file is the digital Pompeii that is the subject of an interactive excavation that allows you to wander through an episode of recent online history.
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