Posts Tagged ‘SPARQL’

In Search Of Apps To Leverage Public BioMolecular Data In RDF Platform

rsz_rdfpfThe European Molecular Biology Laboratory (EMBL) and the European Bioinformatics Institute (EBI) that is part of Europe’s leading life sciences laboratory this fall launched a new RDF platform hosting data from six of the public database archives it maintains. That includes peer-reviewed and published data, submitted through large-scale experiments, from databases covering genes and gene expression, proteins (with SIB), pathways, samples, biomodels and molecules with drug-like properties. And next week, during a competition at SWAT4LS in Edinburgh, it’s hoping to draw developers with innovative use case ideas for life-sciences apps that can leverage that data to the benefit of bioinformaticians or bench biologists.

“We need developers to build apps on top of the platform, to build apps to pull in data from these and other sources,” explains Andy Jenkinson, Technical Project Manager at EMBL-EBI. “There is the potential using semantic technology to build those apps more rapidly,” he says, as it streamlines integrating biological data, which is a huge challenge given the data’s complexity and variety. And such apps will be a great help for lab scientists who don’t know anything about working directly with RDF data and SPARQL queries.

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HealthCare.Gov: Progress Made But BackEnd Struggles Continue

rsz_hcgovThe media has been reporting the last few hours on the Obama administration’s self-imposed deadline for fixing HealthCare.gov. According to these reports, the site is now working more than 90 percent of the time, up from 40 percent in October; that pages on the website are loading in less than a second, down from about eight; that 50,000 people can simultaneously use the site and that it supports 800,000 visitors a day; and page-load failures are down to under 1 percent.

There’s also word, however, that while the front-end may be improved, there are still problems on the back-end. Insurance companies continue to complain they aren’t getting information correctly to support signups. “The key question,” according to CBS News reporter John Dickerson this morning, “is whether that link between the information coming from the website getting to the insurance company – if that link is not strong, people are not getting what was originally promised in the entire process.” If insurance companies aren’t getting the right information for processing plan enrollments, individuals going to the doctor’s after January 1 may find that they aren’t, in fact, covered.

Jeffrey Zients, the man spearheading the website fix, at the end of November did point out that work remains to be done on the backend for tasks such as coordinating payments and application information with insurance companies. Plans are for that to be in effect by mid-January.

As it turns out, among components of its backend technology, according to this report in the NY Times, is the MarkLogic Enterprise NoSQL database, which in its recent Version 7 release also added the ability to store and query data in RDF format using SPARQL syntax.

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Linked Data: “The Gift That Keeps On Giving”

semtechnyclogoK. Krasnow Waterman started the New York Semantic Technology & Business Conference off on the right foot Wednesday, highlighting the highly practical virtues of the semantic web and Linked Data for all.

Krasnow Waterman pointed to four big benefits of a semantic web world, including easing the path to:

  • Analyzing data from multiple sources;
  • Understanding context, from the meaning of a particular term to the context of relationships;
  • Linking data; and
  • Applying rules in which there’s no limit about what can be said or linked to within program code that can be reasoned over as data flows through systems.

In her life as CEO of LawTechIntersect, which offers data/technology management and policy consulting, she noted that she’s now “talking to people about forestalling their platform upgrades, to go back instead and embed the tagging needed for semantic processing,” she told attendees at SemTech. “It’s the gift that keeps on giving. Do it and you can compute forevermore with that data.”

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YarcData Software Update Points Out That The Sphere Of Semantic Influence Is Growing

YarcDataRecent updates to YarcData’s software for its Urika analytics appliance reflect the fact that the enterprise is starting to understand the impact that semantic technology has on turning Big Data into actual insights.

The latest update includes integration with more enterprise data discovery tools, including the visualization and business intelligence tools Centrifuge Visual Network Analytics and TIBCO Spotfire, as well as those based on SPARQL and RDF, JDBC, JSON, and Apache Jena. The goal is to streamline the process of getting data in and then being able to provide connectivity to the tools analysts use every day.

As customers see the value of using the appliance to gain business insight, they want to be able to more tightly integrate this technology into wider enterprise workflows and infrastructures, says Ramesh Menon, YarcData vice president, solutions. “Not only do you want data from all different enterprise sources to flow into the appliance easily, but the value of results is enhanced tremendously if the insights and the ability to use those insights are more broadly distributed inside the enterprise,” he says. “Instead of having one analyst write queries on the appliance, 200 analysts can use the appliance without necessarily knowing a lot about the underlying, or semantic, technology. They are able to use the front end or discovery tools they use on daily basis, not have to leave that interface, and still get the benefit of the Ureka appliance.”

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Hooray For Semantic Tech In The Film Industry

Image courtesy popturfdotcom/Flickr

Image courtesy popturfdotcom/Flickr

The story below features an interview with Kurt Cagle, Information Architect Avalon Consulting, LLC, who is speaking this week at the Semantic Technology And Business Conference in NYC. You can save $200 when you register for the event before October 2.

 

New York has a rich history in the film industry.  The city was the capital of film production from 1895 to 1910. In fact, a quick trip from Manhattan to Queens will take you to the former home of the Kaufman Astoria Studios, now the site of the American Museum of the Moving Image. Even after the industry moved shop to Hollywood, New York continued to hold its own, as evidenced by this Wikipedia list of films shot in the city.

 

semtechnyclogoThis week, at the Semantic Technology & Business Conference, a session entitled Semantics Goes Hollywood will offer a perspective on the technology’s applicability to the industry for both its East and West Coast practitioners (and anyone in between). For that matter, even people in industries of completely different stripes stand to gain value: As Kurt Cagle, Information Architect at Avalon Consulting, LLC, who works with many companies in the film space, explains, “A lot of what I see is not really a Hollywood-based problem at all – it’s a data integration problem.”

 

Here’s a spotlight on some of the points Cagle will discuss when he takes the stage:

 

  • Just like any enterprise, studios that have acquired other film companies face the challenge of ensuring that their systems can understand the information that’s stored in the systems of the companies they bought. Semantic technology can come to the fore here as it has for industries that might not have the same aura of glamour surrounding them. “Our data models may not be completely in sync but you can represent both and communicate both into a single composite data system, and a language like SPARQL can query against both sets to provide information without having to do a huge amount of re-engineering,” Cagle says.

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A Look Into Learning SPARQL With Author Bob DuCharme

Cover of Learning SPARQL - Second Edition, by Bob DuCharmeThe second edition of Bob DuCharme’s Learning SPARQL debuted this summer. The Semantic Web Blog connected with DuCharme – who is director of digital media solutions at TopQuadrant, the author of other works including XML: The Annotated Specification, and also a welcome speaker both at the Semantic Technology & Business Conference and our Semantic Web Blog podcasts – to learn more about the latest version of the book.

Semantic Web Blog: In what I believe has been two years since the first edition was published, what have been the most significant changes in the ‘SPARQL space’ – or the semantic web world at large — that make this the right time for an expanded edition of Learning SPARQL?

DuCharme: The key thing is that SPARQL 1.1 is now an actual W3C Recommendation. It was great to see it so widely implemented so early in its development process, which justified the release of the book’s first edition so long before 1.1 was set in stone, but now that it’s a Recommendation we can release an edition of the book that is no longer describing a moving target. Not much in SPARQL has changed since the first edition – the VALUES keyword replaced BINDINGS, with some tweaks, and some property path syntax details changed – but it’s good to know that nothing in 1.1 can change now.

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Fighting Global Hunger with Semantics, And How You Can Help

Hunger is a critical issue affecting approximately 870 million people worldwide. With new technologies, research, and telecommunication, we as a global population have the power to significantly reduce the levels of hunger around the world. But in order to accomplish this, the people who have control of the aforementioned research and technology will need to share their data and combine forces to create direct solutions to this global problem.

This is precisely what the good people at the International Food Policy Research Institute (IFPRI) are working toward. What the IFPRI has to offer is data–data on every country around the world, data about malnutrition, child mortality rates, ecology, rainfall, and much more. With the help of Web Portal Specialists like Soonho Kim, they are working on making that data open and easily accessible, but they are currently facing a number of challenges along the way. Soonho spoke to an intimate group of semantic technology experts at the recent Semantic Technology Conference, sharing the successes of the IFPRI thus far and the areas where they could use some help. Read more

Big Data Is Big Focus At SemTechBiz (Part 2)

LOGO: Semantic Technology & Business Conference; June 2-5, 2013, San Francisco, CaliforniaOur 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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MarkLogic 7 Vision: World-Class Triple Store and World-Beating Information Store

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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Helping Autism Researchers, And Others, With Some SPARQL Savvy

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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