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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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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“The way to think about this is that when we look at semantics, we didn’t … say we just want to check a box on semantics,” Bloom said, by working with partners on some low-hanging fruit – although it will be collaborating with them on various semantic enrichment capabilities. “We think semantics is critical technology, and more interesting I believe is that it is a critical technology that is both a search technology as well as a database technology.” Others in the marketplace will focus on changing their search engines to do semantics, but optimum results won’t come if all that’s being done is layering in semantics at the search level, he said.

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That’s the word from Emil Eifrem, CEO of Neo Technology, which makes the open-source Neo4j NoSQL graph database. He’s not talking in terms of RDF-centric solutions, even though he says he’s 100 percent in agreement with the vision of the semantic web and machine readability. “The world is a graph,” Eifrem says, “and RDF is a great way of connecting things. I’m all in agreement there.” The problem, in his opinion, is that execution on the software end there has been lacking.

“This comes down to usability,” he says, and the average developer, he believes, finds the semantic web-oriented tools largely incomprehensible. Eifrem says he’s speaking from real-world experiences, having worked directly with RDF and taught classes on the semantic web layers. Where it took a week to get students up to speed on things like Jena and Sesame, they ‘get’ the property graph and graph databases in half-a-day, he says. Neo4j stores data in nodes connected by directed, typed relationships with properties on both – also known as a property graph.

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The research firm yesterday released the list of nine trends that it says will play key roles in modernizing information management and in making the role of information governance increasingly important. Semantic technologies come in at No.3 on the list – right behind closely-tied-to trends Big Data and modern information infrastructure.

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A key feature of many triplestores is the ability to do inference. It is important to note that a DBMS typically offers the capacity to deal with concurrency, security, logging, recovery, and updates, in addition to loading and storing data. Not all Triplestores offer all these capabilities (yet).

Triplestore Implementations

Triplestores can be broadly classified in three types categories: Native triplestores, RDBMS-backed triplestores and NoSQL triplestores. continued…

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Rutrell Yasin recently wrote that a convergence of growing technologies, including semantic web technologies, will spur exciting Big Data projects in 2013. Yasin writes, “The maturity and convergence of four technologies will help government decision-makers derive more value from their big data projects in 2013, predicts Chris Biow, public sector CTO at MarkLogic, a developer of databases for big data applications. ‘Cloud computing, Hadoop and NoSQL databases are the three game-changing technologies that are being applied to big data,’ Biow said. ‘I think this is the year that government agencies get their hands around what each of them can and cannot do.’ Semantic technology is the fourth discipline to add to the equation, which can be used to extract facts from structured and unstructured data as well as handle relationships between data in a more flexible way than traditional relational databases, Biow said during an interview with GCN.” continued…

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As we close out 2012, we’ve asked some semantic tech experts to give us their take on the year that was. Was Big Data a boon for the semantic web, or is the opportunity to capitalize on the connection still pending? Is structured data on the web not just the future but the present? What sector is taking a strong lead in the semantic web space?

We begin with Part 1, with our experts listed in alphabetical order:

John Breslin, lecturer at NUI Galway, researcher and unit leader at DERI, creator of SIOC, and co-founder of Technology Voice and StreamGlider:
I think the schema.org initiative really gaining community support and a broader range of terms has been fantastic. It’s been great to see an easily understandable set of terms for describing the objects in web pages, but also leveraging the experience of work like GoodRelations rather than ignoring what has gone before. It’s also been encouraging to see the growth of Drupal 7 (which produces RDFa data) in the government sector: Estimates are that 24 percent of .gov CMS sites are now powered by Drupal.

Martin Böhringer, CEO & Co-Founder Hojoki:

For us it was very important to see Jena, our Semantic Web framework, becoming an Apache top-level project in April 2012. We see a lot of development pace in this project recently and see a chance to build an open source Semantic Web foundation which can handle cutting-edge requirements.

Still disappointing is the missing link between Semantic Web and the “cool” technologies and buzzwords. From what we see Semantic Web gives answers to some of the industry’s most challenging problems, but it still doesn’t seem to really find its place in relation to the cloud or big data (Hadoop).

Christine Connors, Chief Ontologist, Knowledgent:

One trend that I have seen is increased interest in the broader spectrum of semantic technologies in the enterprise. Graph stores, NoSQL, schema-less and more flexible systems, ontologies (& ontologists!) and integration with legacy systems. I believe the Big Data movement has had a positive impact on this field. We are hearing more and more about “Big Data Analytics” from our clients, partners and friends. The analytical power brought to bear by the semantic technology stack is sparking curiosity – what is it really? How can these models help me mitigate risk, more accurately predict outcomes, identify hidden intellectual assets, and streamline business processes? Real questions, tough questions: fun challenges!

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David S. Read of Information Week recently discussed the benefits of semantic databases. He writes, “Don’t buy into the idea that semantic database technologies are just for consumer-facing services such as BBC Online or the semantic Web initiatives embraced by the likes of Best Buy and Cisco. In much the same way that consumerization drives innovation in end user computing, semantic database technologies deliver benefits that businesses of all stripes should be exploiting. At a high level, semantic databases offer five main benefits: They work with your existing relational databases. They align with Web technologies. Their underlying technology speeds integration of multiple databases. They’re based on data structures that are flexible by design. And thus they can help enterprises tackle big data challenges.” continued…

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Bob DuCharme has shared some interesting insights regarding SPARQL, RDF, and Big Data. He writes, “I think it’s obvious that SPARQL and other RDF-related technologies have plenty to offer to the overlapping worlds of Big Data and NoSQL, but this doesn’t seem as obvious to people who focus on those areas. For example, the program for this week’s Strata conference makes no mention of RDF or SPARQL. The more I look into it, the more I see that this flexible, standardized data model and query language align very well with what many of those people are trying to do.” continued…

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As SindiceTech founder and CEO Giovanni Tummarello explains, companies actually approached his team to help them make a reality of their visions to use RDF and SPARQL, as the best knowledge representation and querying technologies available, by providing the missing scalability and stability. Sindice.com was evidence that the technology the team had developed could answer these enterprises’ needs; currently there are about 700 million semantically marked-up web pages indexed in the Sindice.com search engine, with a live updated index of some 80 billion triples daily. Its database is over 5 terabytes.

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Andraz Tori is the Owner and Chief Technology Officer at Zemanta, a tool that uses natural language processing (NLP) to extract entities within the text of a blog and enrich it with related media and articles from Zemanta’s broad user base.    This interview was conducted for Part 3 of the series “Dynamic Semantic Publishing for Beginners.”

Q. Although the term “Dynamic Semantic Publishing” appears to have come out of the BBC’s coverage of the 2010 World Cup, it looks as though Zemanta has been applying many of the same principles on behalf of smaller publishers since 2008.  Would you characterize it this way, or do you think that Zemanta is a more limited service with specific and targeted uses, while the platform built by BBC is its own semantic ecosystem?  How broadly should we define Dynamic Semantic Publishing?

A. What Zemanta does is empower the writer through semantic technologies. It’s like having an exoskeleton that gives you superpowers as an author. But Zemanta does not affect the post after it was written.   On the other hand dynamic semantic publishing is based on the premise of bringing together web pages piece-meal from a semantic database, usually in real time.

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What might be discerned from the tenor of the submissions is something of a shift in focus in the Linked Data space, according to workshop chair Dr. Michael Hausenblas, Linked Data Research Centre, DERI, NUI Galway, Ireland. Other organizing committee members include Tim Berners-Lee, Christian Bizer and Tom Heath. “In 2008 to 2010 it was more like we were establishing the field, getting people to talk about what they do in terms of publishing and best practice around Linked Data, Open Linked Data and Linked Enterprise Data,” says Hausenblas. Now, with the web of Linked Data having grown to about 32 billion RDF triples last year, “we’re moving more towards the consumption – publishing is a necessary precondition but not an end in itself.”

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