Our discussion of Big Data at SemTechBiz, begun here, continues:

The Enterprise Linked Data Cloud Needs Semantics, And More

Another exploration of Big Data’s intersection with semantic technology will take place at this session, where Dr. Giovanni Tummarello, senior research fellow at DERI and CTO of SindiceTech, will talk about the former becoming an enabler for the latter to be really useful in enterprises. “A lot of people say it’s via Big Data that semantic technologies like RDF will see a coming of age and clear applications in certain industries,” he says. There’s value to adding data first and understanding it later, and to that end, “semantic technologies give you the most agile tool to deal with data you don’t know, where there’s a lot of diversity, and you don’t know what of it particularly will be useful.”

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Photo courtesy: Flickr/rvaphotodude

Last month at its MarkLogic World 2013 conference, the enterprise NoSQL database platform provider talked semantics as it related to its MarkLogic Server technology that ingests, manages and searches structured, semi-structured, and unstructured data (see our story here). The vendor late last week was scheduled to provide an early access release of MarkLogic 7, formally due by year’s end, to some dozens of initial users.

“People see a convergence of search and semantics,” Stephen Buxton, Director, Product Management, recently told The Semantic Web Blog. To that end, a lot of the vendor’s customers have deployed MarkLogic technology as well as specialized triple stores, but what they really want, he says, is an integrated approach, “a single database that does both individually and both together,” he says. “We see the future of search as semantics and the future of semantics as search, and they are very much converging.” At its recent conference, Buxton says the company demonstrated a MarkLogic app it built to function like Google’s Knowledge Graph to provide an idea of the kinds of things the enterprise might do with both search and semantics together.

Following up on the comments made by MarkLogic CEO Gary Bloom at his keynote address at the conference, Buxton explained that, “the function in MarkLogic we are working on in engineering is a way to store and manage triples in the MarkLogic database natively, right alongside structured and unstructured information – a specialized triples index so queries are very fast, and so you can do SPARQL queries in MarkLogic. So, with MarkLogic 7 we will have a world-class triple store and world-beating information store – no one else does documents, values and triples in combination the way MarkLogic 7 will.”

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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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Pete Swabey of Information Age recently discussed UNIT4, “the Dutch-owned ERP vendor that acquired UK accounting software provider Coda in 2008. The company collaborated with UK semantic web consultancy Epimorphics to develop a platform that allowed customers to expose their data online as SPARQL endpoints, meaning it could be retrieved using SPARQL, the querying language for RDF. The platform was developed with local authorities in mind, facing as they are growing pressure to be transparent. ‘We were hoping we would have an audience of armchair auditors,’ recalls Pete Brown, chief technology officer of UNIT4 UK.” Read more

Courtesy: Flickr/ clbean

IT leaders keeping an eye on Gartner’s top tech trends list know that early in March semantic technologies made the cut (see our original story here, and our follow-up with one of the authors of the Gartner report here). The big question for many enterprise IT pros, though, is what should they be doing with that knowledge – how can they start leveraging semantic technology to their own organizations’ benefit?

Help is on the way. Three experts in semantic web technologies and Linked Data weigh in with their advice on heading down that road:

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The Semantic Web Blog reported last year about a relationship formed between the Digital Enterprise Research Institute (DERI) and Fujitsu Laboratories Ltd. in Japan, focused on a project to build a large-scale RDF store in the cloud capable of processing hundreds of billions of triples. At the time, Dr. Michael Hausenblas, who was then a DERI research fellow, discussed Fujitsu Lab’s research efforts related to the cloud, its huge cloud infrastructure, and its identification of Big Data as an important trend, noting that “Linked Data is involved with answering at least two of the three Big Data questions” – that is, how to deal with volume and variety (velocity is the third).

This week, the DERI and Fujitsu Lab partners have announced a new data storage technology that stores and queries interconnected Linked Open Data, to be available this year, free of charge, on a cloud-based platform. According to a press release about the announcement, the data store technology collects and stores Linked Open Data that is published across the globe, and facilitates search processing through the development of a caching structure that is specifically adapted to LOD.

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This week Dandelion, which bills itself as the one-stop shop for smart, high-quality Geo and Linked Data from trusted sources, starts its private beta. The service, which promises end users quality, normalized, linked and enriched data for their apps and reports; developers a simple API for any kind of language on any kind of platform; and corporate and government entities a way to publish and profit from their data, comes from SpazioDati.

That company is the creation of four Italian entrepreneurs – CEO Michele Barbera, president Gabriele Antonelli, partnerships director Andrea Di Benedetto, and Luca Pieraccini – who lived first-hand the frustrating experience of trying to find and leverage useful data for the custom web and mobile apps they were developing while running and working in small IT consulting companies. In an attempt to reverse the ratio of finding and cleaning data to actually building apps, says Barbera, the founders began participating in several EU-funded research projects and in the Open Data movement in Europe and Italy, including founding the non-profit Linked Open Data Italy. They also started experimenting with Semantic Web technologies.

“Open Data helps us to find valuable data and to build value-added web and mobile apps,” says Barbera. “So, let’s say that we solved partly the first problem of finding data, but not the second one, normalizing and cleaning data, since it is still very difficult to merge different data sources to put data in context.” Read more

The W3C has announced that eleven specifications of SPARQL 1.1 have been published as recommendations. SPARQL is the Semantic Web query language.  We caught up with Lee Feigenbaum, VP Marketing & Technology at Cambridge Semantics Inc. to discuss the significance of this announcement. Feigenbaum is a SPARQL expert who currently serves as the Co-Chair of the W3C’s SPARQL Working Group, leading the design of SPARQL.

Feigenbaum says, “SPARQL 1.1 is a huge leap forward in providing a standard way to access and update Semantic Web data. By reaching W3C Recommendation status, Semantic Web developers, vendors, publishers and consumers have a stable, well-vetted, and interoperable set of standards they can rely on for the foreseeable future.”

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Seevl, the free music discovery service that leverages semantic technology to help users conduct searches across a world of facts-in-combination to find new musical experiences and artist information, has launched an app for Deezer that will formally go live Monday.  (See our in-depth look at Seevl here, and a screencast of how the service works here.) Deezer is a music streaming service available in more than 150 countries – not the U.S. yet, though – that claims more than 20 million users.

Seevl, which late last year updated its YouTube plug-in with more music discovery features and better integration with the YouTube user interface, models its data in RDF. In a blog post earlier this year, founder and CEO Alexandre Passant explained how the Seevl service uses Redis for simple key-value queries and SPARQL for some more complex operations, like recommendations or social network analysis, as well as provenance. As for the new Deezer app, it provides the same features as the YouTube app for easily navigating and discovering music among millions of tracks, Passant tells the Semantic Web Blog.

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Algebraix Data Corporation today announced its SPARQL Server(TM) RDF database successfully executed all 17 of its queries on the SP2 benchmark up to one billion triples on one computer node. The SP2 benchmark is the most computationally complex for testing SPARQL performance and no other vendor has reported results for all queries on data sizes above five million triples. Read more