One in 50 American children have autism, according to the latest figures released by the Centers for Disease Control and Prevention in March. One of the winners of the YarcData Graph Analytics Challenge, announced in April, can make a difference in better understanding the causes of the disease.

Taking second place in the competition, the work of Adam Lugowski, Dr. John Gilbert, and Kevin Dewesse, of the University of California at Santa Barbara, leveraged a dataset created for the Mayo Clinic Smackdown project, that has the same structure and property types – and scale – as the medical organization’s actual Big Data sets around autism, but which uses publicly available data in place of the real thing. The team can’t use the real data because it includes private information about patients, diagnosis, prescriptions, and the like.

But the actual data deployed for the project doesn’t matter, says Lugowski . “The goal is to find relationships we have never thought of before, and this way it doesn’t prejudice the algorithm,” he says. Using YarcData’s uRIKA graph analytics appliance, the algorithm queries the Smackdown dataset – which in its smallest version has almost 40 million RDF triples and in its largest is about 100 times bigger, mirroring the size of all the Mayo Clinic’s actual autism data – to discover commonalities among the data, mimicking how the real data sets could be queried in search of common precursors among clusters of patients with the diagnosis.

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YarcData LLC, a Cray company dedicated to providing “Big Data” graph-analytic solutions to enterprises, today announced the winners of the YarcData Graph Analytics Challenge showcasing the increasing applicability and adoption of graph analytics in discovering unknown relationships in Big Data. Submissions included an innovative range of applications across a broad variety of sectors including crime prediction, social science, life science and sports performance. Read more

YarcData has announced the finalists of the company’s Graph Analytics Challenge: “The top six entries for the contest, which features $100,000 in prizes including a $70,000 grand prize for the first place winner, were determined to have entered the best submissions for un-partitionable, Big Data graph problems. The top six submissions span a number of diverse categories, such as healthcare, law enforcement, sports, life sciences and social media.” Read more

Cray is looking for Senior Semantic Web Engineer in Pleasanton, CA. According to the post, “The Knowledge Management Practice at Cray is developing solutions to meet the growing demand of large scale data analysis and mining. We are developing innovative solutions to meet the demands of next generation big data analysis. We have openings for a senior semantic applications developer for building the web 3.0 data mining application stack. The developer will be responsible for  the developing database application software stack.  This position entails: Developing, porting, testing and benchmarking the web 3.0 database application software. Building and maintaining working relationships with technical counterparts at the ISVs, partners, and customers. Sound understanding and experience with RDF.” Read more

Early in 2011, I wrote a piece here on SemanticWeb.com which explored the relationship between Semantic Technologies and super-computing’s venerable rock star, Cray. Then, earlier this year, Cray spun out a new division to focus upon exploring massive graph databases; something which should resonate with the semantic technology community. The new division — YarcData — differentiates itself quite clearly from its parent, leading with a data-led proposition and typically operating at quite a different pricepoint to its eye-wateringly expensive parent.

I sat down with YarcData President Arvind Parthasarathi during the Semantic Technology & Business Conference in San Francisco, to get an update on YarcData and to hear why the company is investing $100,000 in prizes for a new ‘Big Data Graph Analytics Challenge.’ Read more

In 2005, I started learning about the so-called Semantic Web. It wasn’t till 2008, the same year I started my PhD, that I finally understood what the Semantic Web was really about. At the time, I made a $1000 bet with 3 college buddies that the Semantic Web would be mainstream by the time I finished my PhD. I know I’m going to win! In this post, I will argue why.

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Timothy Prickett Morgan reports, “Supercomputer maker Cray has released an exotic appliance to help deep-pockets organizations find the relationships hidden in the torrent of information now being collected about, well, everything and everyone. Sometimes you want to Map and Reduce that big data to sift it for some golden nuggets of information, and sometimes you want to take data about people or objects and see how they are connected to each other – or, better still, to see how they might be related, even though there is not a relationship expressed in your data.”

Morgan continues, “The appliance, called Urika… is a combination of open source software to do graph analysis on big data coupled with the fourth generation of Cray’s ‘Threadstorm’ massively threaded processors that has been tuned to do relationship analytics, or what is sometimes called graph analytics. Read more

Cray is looking for a Senior Semantic Web Engineer in Pleasanton, CA. According to the post, “The Knowledge Management Practice at Cray is developing solutions to meet the growing demand of large scale data analysis and mining. We are developing innovative solutions to meet the demands of next generation big data analysis. We have openings for a senior semantic applications developer for building the web 3.0 data mining application stack. The developer will be responsible for the developing database application software stack.  This position entails: Developing, porting, testing and benchmarking the web 3.0 database application software; Building and maintaining working relationships with technical counterparts at the ISVs, partners, and customers; Collaborating with other functional groups within Cray on features related to supporting informatics applications and databases.” Read more

Steve Scott, CTO of Cray will be on hand at next week’s Semantic Technology Conference to discuss Cray’s Extreme Multithreaded Technology (XMT) System. According to the article, “The Cray XMT System is designed specifically to run challenging big data graph analytics workloads that bring traditional systems to their knees. Many problems in the semantic space are particularly well suited for this system and the Cray XMT holds the promise of advancing the application of semantic technologies to big data analysis. This talk will describe the motivation, architecture and potential application areas for this unique machine.” Read more

Cray. Despite everything that has happened over the years, from technological advances to organisational wobbles, bankruptcies and buy-outs, the name retains a certain cachet. They make super computers! Their computers come (came) with seats and bubbling coolant systems and everything! To someone growing up with early examples of rudimentary computing in the home, Cray was the stuff of Tomorrow’s World, Bond villains, and more. This was what real computers were all about.

Despite the growing power of ordinary computers, and the opportunities offered by parallelisation and the Cloud, those early memories of Cray superness were sufficient to pique my interest when a recent press release from semantic technology company Cambridge Semantics landed in my inbox. Digging a little further, it rapidly became apparent that Cambridge Semantics were not alone. Amongst eight ‘Solution Partners‘ listed for Cray’s XMT supercomputer, not one of them would look out of place presenting or exhibiting at a semantic technology event. For some reason, semantics appear to have replaced quirky styling, bubbling coolant and the circular seating of yesteryear. Read more