The cloud’s role in processing big semantic data sets was recently highlighted in early April when DERI and Fujitsu Laboratories announced a new data storage technology for storing and querying Linked Open Data that resides on a cloud-based platform (see our story here).

The cloud conversation, with storage as one key discussion point, will continue to be an active one in Big Data circles, whether users are working with massive, connected Linked Data sets or trying to run NLP across the Twitter firehose. CloudSigma, for example, recently publicly disclosed that it is using an all solid-state drive (SSD) solution for its public cloud offering that lets users purchase CPU, RAM, storage and bandwidth independently. The use of SSD, says CEO Robert Jenkins, avoids the problem that spinning disks have with the randomized, multi-tenant access of a public cloud that leads to storage bottlenecks and curbs performance.

That, combined with the company’s approach of letting customers size virtual machine resources as they like, as well as leverage exposed advanced hypervisor settings to optimize for their particular applications, he says, brings the use of the public cloud infrastructure closer to what companies can get out of private cloud environments, and at a price-performance win.

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Enterprise NoSQL database platform provider MarkLogic has come into some cash: a $25 million round of growth capital from investors including Sequoia Capital, Tenaya Capital, Northgate Capital, CEO Gary Bloom and other corporate executives. Yesterday, at the company’s MarkLogic World 2013 conference, Bloom also prepared the audience to hear more today from company executives about MarkLogic’s next steps in semantics for its MarkLogic Server technology that ingests, manages and searches structured, semi-structured, and unstructured data.

“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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Image Courtesy Flickr/ Sean MacEntee

It’s April Fool’s Day on the Web, and we’re sensing some semantic allusions and downright sentiment analytics assertions in today’s pranks. Have a look:

• Head over to your Google search engine and you’ll be teased to find out what that smell is with Google Nose. or, as they describe it, the new scentsation in search.  Go beyond type, talk, and touch for a new notation of sensation, it promises. The Internet sommelier, Google explains, comes with an expertly curated Knowledge Panels to pair images, descriptions, and aromas. While it credits new technologies such as StreetSense (responsible for Google inhaling and indexing millions of atmospheric miles), and Android Ambient Odor Detection (which collects smells via the mobile OS), it seems to me that the Knowledge Graph had to have a hand in this one.

Whisk, the U.K.-based service for matching online recipes with online ingredients-shopping, went live in a big way at year’s end, with a partnership with TV channel and recipe publisher Food Network. As its iOS and Android apps rolled out to accompany its browser plug-in, Food Network in the U.K. featured a button on its recipe search engine for a widget that taps into the service, which is underpinned by semantic technology and a cloud infrastructure. A recent second round of angel funding also has taken the service’s total investment to more than £500,000.

Whisk co-founder Craig Edmunds reports about 12,000 app downloads so far, and about a 1.5 percent steady click-through from the button on the publisher’s site – right where it expected to be at this point, he says. Getting the big-name Food Network signed on actually changed plans a bit for the service, which The Semantic Web Blog covered earlier here, and whose co-founder Nick Holzherr was a keynote speaker at the London SemTech event.

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Courtesy: Flickr/zoetnet

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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Early in the summer, The Semantic Web Blog introduced readers to Nara, an advanced neural networking service to automate, personalize and curate web dining experiences for users. (See that story here.)

The service is moving ahead with the launch today of its mobile version, as well as in other respects. “We’re now doing a full-on consumer launch of a polished product on both the web and mobile [platforms],” says CTO Nathan Wilson. “People really are clamoring for the mobile component, especially for this [dining] use case.” Versions for both the iPhone’s iOS and Android operating systems are available.

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Recently, we published Yefim “Jeff” Zhuk’s article, “IT of the Future: Semantic Cloud Architecture.” The paper has been a very popular free download (available here).

One of the readers, Lev Gorodinski (CTO, EPaySpot), approached Jeff directly with some questions and the two engaged in a conversation filled with insights that they wanted to share with our readers. They are kindly allowing us to republish the thread in its entirety.

Lev Gorodinski: I’ve read the article and have some bigger picture questions and comments which likely warrant several discussions. Overall, I am interested in methodologies which aim to bridge the gap between knowledge and its technical manifestation and am therefore interested in the subject matter.

The term “sandbox” in BASE may create the impression that it isn’t a production level system. I think that both the goal of BASE to “Decrease the number of manual operations required for business changes” and its notion of a “playground” are essential to making it ready for production. This will allow an agile and iterative development and exploration process.

Jeff Zhuk: The primary purpose is setting a common ground where business analysts and developers can collaborate on real business tasks. For some companies this ground can serve in production and other companies might feel more comfortable to use it as a playground for safe development and testing before copying to production. The role of the playground will be growing without growing maintenance cost.
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The health care industry is built on an awful lot of manual infrastructure, and the strain can grow even more with the adoption of standards such as the tenth revision of the World Health Organization’s International Statistical Classification of Diseases and Related Health Problems (ICD). In the U.S., the adoption deadline of ICD-10, which codes for diseases, signs and symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or diseases, is set for October of 2014.

“The way the country is trying to address quality improvement in health care is requiring more information to be captured electronically in a system so it can be processed and used to improve care,” explains Dr. Daniel Riskin, MD, MBA, FACS, and CEO and co-founder of Health Fidelity. Earlier this year the company released the REVEAL cloud-based service for healthcare IT application companies and their healthcare organization customers. “The first step is for doctors to use electronic health records. The next is to drive increasing capture of useable information,” Riskin concludes.

Typing medical narratives is just text – it’s not useable information. Making it useable for standards such as ICD-10 – which is some five times as detailed as ICD-9 – can lead to situations where doctors and nurses have to do twice as much work tagging items within narratives, and where coding departments can grow to be twice as big. The aim to improve health care via such efforts is sound, but so too is relying more on technology and less on manual labor to get value out of the unstructured data.

The clinical NLP (natural language processing) technology in Health Fidelity’s REVEAL platform steps into the picture here, transforming huge volumes of unstructured clinical data (Big Data if ever there was any) into information that healthcare IT application vendors and their hospital customers can then make use of to improve care quality, safety and efficiency.

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What do you get when you mix two parts natural language processing with a little personalization, and add in a dash of the cloud? The answer is Whisk, a U.K. company building a service that lets users purchase the ingredients for any recipe they find on the Internet.

“The crux of it is that you can take any recipe on the ‘Net and turn it into a transaction in on online market,” says co-founder Craig Edmunds. “There’s a machine translation problem from the recipe up through to our internal language, which is one NLP problem, and then another is from our internal language into online markets.” Another leg of the work is that the service seeks to not match to just one item at a market but as many as possible, and consider user preferences as to which is the optimal product, too.

At the upcoming Semantic Technology and Business Conference in the U.K., Edmunds will be considering how the issues of machine translation, manual intervention, personalization and the cloud intersect in creating a service that adds all the ingredients they need for dishes they find online straight into their online shopping basket.

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In July of 2011, we published a series of articles, “From Business as Usual to Knowledge-Driven Architecture” by Yefim “Jeff” Zhuk. The series outlined enterprise IT of the future with integrated software and knowledge engineering, further expanding on ideas originally described in the book “Integration-ready Architecture and Design.”

Today, we are pleased to offer Jeff’s latest article as a 27-page PDF file. In this new article, he focuses on the process of transitioning from IT architectures of today to Semantic Cloud Architecture with very practical “baby steps” — steps which require minimum upfront investment. The emphasis of this article is on collaborative work of business and enterprise architects with the Business Architecture Sandbox for Enterprise, (BASE) that was demonstrated at the 2012 Semantic Tech and Business Conference –San Francisco.

Zhuk says, “The discussed approach is gradually shifting the focus of IT from technology to information by standardizing business event processing, placing the seeds of semantic technology in the current business ground, and establishing a self-sustaining process of transformation to semantic cloud architecture. The article provides the context and speaks technical details for this transition.”

Read/Download the full paper (registration required)

As a teaser, here is the beginning of the article and Section Headings…

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