Edamam wants to be the one place where all the food knowledge of the world is organized. That’s the goal of co-founder and CEO Victor Penev, who launched the site in April, and recently updated the several hundred major recipe sites in its knowledge base to also include some smaller blog sites that add additional variety.

Semantic technology is helping the company reach its goal. “A big problem is that data about food is very messy,” says Penev. “It’s hard to find something, what you find often contradicts other information of what is good for you and what the calories are. So we set out to solve that problem. We played around with different approaches but settled on using semantic technology.”

The confusion arises in part from the fact that recipe sites themselves usually just hire services to calculate nutritional data. But that may lead to mistakes when calculations aren’t undertaken with exactitude — substituting white cream for heavy cream nutritional details changes the whole profile of the recipe, he says.

So, what is that right semantic stuff? One piece of it is that, in conjunction with Ontotext, Edamam built a food ontology. An ontology can be the foundation for a lot of things, such as extracting the knowledge of the chemical composition of a particular recipe and thus inferring its flavor and texture. And Edamam means to grow its own to include various datasets such as chemical data (for flavor and texture), geolocation (for local and seasonal recipes), product data (for e-commerce). and more.

But initially, it’s taken the simple approach, with the core of the ontology focused around classifying ingredients, nutrients and food. “We have started with the simplest ontology and focused on the most common use case — mobile recipe search,” he says.

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SemTechBiz is Less Than 2 Weeks Away

The Semantic Tech & Business Conference (SemTechBiz) is coming to San Francisco on June 3-7! Join us for case studies, innovative panels, tutorials, and keynotes that will provide you with practical advice, hands-on guidance, and breakthrough approaches to solving business problems with semantic technology. Passes go up $200 at the door. Sign up now and save !

Rob Gonzalez of Cambridge Semantics recently commented on a LinkedIn thread started by Michael Uschold. Uschold asked the question, “How is semantic technology more flexible than relational technology?” One commenter stated, “If you ‘mess up’ your choice of initial vocabulary, then semantic systems have similar sorts of problems to relational systems, in that you may have to restructure the vocabulary at a later date (just like you have to restructure relational schemas), and hence restructure the data. My experience suggests that such restructuring happens (far?) less often with semantic systems than with relational systems, and that the restructuring is easier, since you can always treat your data as one big list of triples.” Read more

While much of the publishing industry still is getting up to speed on what semantic technology can do for business, it’s already deep within the DNA of The Tribune Company – to the point where Keith DeWeese, Director, Information and Semantics Management, can comfortably use the word “ontology” in discussions with non-tech employees, and enjoy the fact that they’re equally comfortable using it themselves.

DeWeese has been with the company since 2007, putting in place a sophisticated semantic system for auto-tagging and indexing content using natural language processing and controlled vocabularies, and leveraging its taxonomy for projects such as providing advanced search functionality. Thanks to building a collaborative communication channel with Tribune executives, producers, and editors, “now I actually am in meetings with executives who say how exciting it is that we now can be part of a community of people applying semantic technologies to content,” he says. “The other day I was at a meeting where a top executive used the word ontology all the time. I kept smiling and later I thanked her.”

Closely engaging with his business customers also is helping make it possible to push the semantic vision further at the company.

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Q-Sensei Corporation has announced version 2.0 of Q-Sensei Enterprise, the company’s enterprise search platform. According to the company, the new version is “designed to rapidly and flexibly develop tailored search-based applications (SBAs) tapping the wealth of data from enterprise Intranets, social media, third parties and the Internet. The new platform features ontology-based data processing and configuration, and a new API to increase time-to-market, flexibility, scalability and efficiency in handling Big Data.” Read more

Back in March, The Semantic Web Blog wrote an article about FIBO, the Financial Industry Business Ontology that’s on its way to being an Object Management Group series of standards. There, we explored its value as an open semantic standard that can be used by financial institutions and industry regulators, both to support conformance to federal regulatory reporting requirements and for internal business processes and risk analysis.

To continue the discussion about the operational value of FIBO, we recently spoke with key participants developing the standard: David Newman, Strategic Planning Manager, Vice President, Enterprise Architecture, Wells Fargo Bank, who is lead of the industry team collaborating on semantics OTC (over-the-counter) derivatives proof-of-concept, and Mike Atkin, managing director at the Enterprise Data Management (EDM) Council, where FIBO was born and is included as content of EDM’s Semantics Repository.

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The latest version of the StreamGlider iPad news reader app for providing consumers with topic-oriented streams of information debuted this week. It brought with it the capability to limit hashtag or keyword searches in a Twitter, YouTube, or Flickr frame to a local area and turn on geo-awareness at the user’s request. But the bigger and more semantic event will be StreamGlider’s upcoming move to the enterprise, with the consumer app serving as a showcase to those potential customers.

StreamGlider CEO Bill McDaniel – also CEO of SemantiStar, which developed the application that The Semantic Web Blog first covered here and here – says to expect in the enterprise edition a very interesting semantic search/semantic relations engine in the background for correlating up to three data sets of semi-structured, unstructured and structured data. The company already is working with one client on a specific application of the generic technology for its custom needs, and talking to a second customer about a pilot around the idea.

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How to help the bench biologist get value out of the wealth of life sciences Linked Data sets? Startup Metaome Science Informatics proposes to offer some help with its DistilBio semantic search and data integration technology, by streamlining the approach to posing user queries. The Distil in DistilBio stands for Data Integration using Semantic Technologies in the Life Sciences.

Metaome, which was founded by CEO Kalpana Krishnaswami and CTO Ramkumar Nandakumar as a bioinformatics services provider before transitioning to a product vendor, contains a few more than a dozen life sciences public data sets so far. Infomaticians in the life sciences space have the expertise to query such data across sets via SPARQL, but the front-line biologist isn’t necessarily an infomatician. So, DistilBio has created a query interface that makes it easier for them to ask large and complex questions in a simplified way across data sets while building a graph in the process.

“How does a user say what are the drugs used for Alzheimer’s disease and do have they have certain protein targets and are those protein targets implicated in other diseases?” says Krishnaswami. “To ask that in one shot right now is hard without working through a SPARQL endpoint using all the SPARQL syntax.”

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Just a little over a year ago The Semantic Web Blog introduced our readers to Gravity in this article. The project, spearheaded by former MySpace execs, is focused on building the Interest Graph. The team’s been pretty quiet about development efforts since that time — until just this month, when it announced Gravity Labs to let the public in on a little more about its underlying Interest Graph infrastructure and to showcase the platform. It also announced that it was open-sourcing some of the “plumbing” code it came up with during development, while understandably keeping its core IT, ontology and algorithms under wraps.

The announcement noted that the internally-named Gravity Interest Service for personalizing content at scale, in real-time, went live at production-scale 6 months ago. So far the technology has created over 400 million user interest graphs; served over 13 million pieces of personalized content per day; personalized the daily Internet experience of tens of millions of users per month; and processed over 25 million inbound interest signals per day, the company says. It expects that at this rate, that in under six months it will be handling 10X all of these numbers.

The Semantic Web Blog once again caught up with Gravity CTO Jim Benedetto to talk some more about the Interest Graph, a term he acknowledges gets thrown around quite a bit these days, with a lot of web sites claiming they’ve got the goods. But, he says, “what they effectively are saying is that buried deep within the data of our logs or deep in the data of how our users interact with our site, we know there are interest indicators there. But a lot of them are not doing much with their data.” Interest Graphs, he says, aren’t owned, but interest data resides in individual places and across the web at large — and they need the Gravity platform to help unlock that to create dynamic and personalized experiences for users, Benedetto says.

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Knarig Arabshian of Bell Labs, Alcatel-Lucent, recently wrote an article describing how semantic technologies can be used for programmable web API search. Arabshian explains, “Service discovery is not an easy task in today’s Web. Discovering an API requires searching through a large number of services on the Internet and then reading pages of documentation to figure out how to use the ones that may match your application. This is the case in Programmable Web as well. The API directory shows over 5000 APIs which are manually categorized in over 50 service categories. And that’s not all…there are around 80 APIs coming in per week and each of these are manually identified and categorized within a single service category. So how can we improve the search and classification?” Read more

Thinking about this past week’s Demystifying Financial Services Semantics conference in NYC, hosted by OMG and The EDM Council, and messages that kept coming across: Think about the business issues first, and be realistic in the way your particular organization can accommodate them – semantic technology may be a large, limited or perhaps even non-existent factor, depending on the challenge.

Some commentary on this point from the panelists:

• Citi chief data officer Eric Chacon discussed the challenges of not having a single source of master data that exists for businesses that grow  through acquisitions, as well as any organization highly decentralized in nature. Read more