Thomson Reuters, the world’s leading source of intelligent information for businesses and professionals, today revealed that 18 central banks and government organizations in Asia Pacific have recently rolled out the flagship Thomson Reuters Eikon platform for real-time financial data, analytics, news and commentary.

The central banks and government authorities that have signed up to use Thomson Reuters Eikon in recent months include the Hong Kong Monetary Authority, Reserve Bank of New Zealand, Reserve Bank of India, Nepal Rastra Bank, Central Bank of the Republic of China (Taiwan), State Bank of Vietnam, Bank of the Lao P.D.R and Royal Monetary Authority of Bhutan. Read more

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Dr. Carlo Trugenberger, co-founder and Chief Scientific Officer at InfoCodex Semantic Technologies AG, has co-authored a report reflecting the topic he discussed at last fall’s London SemTech event: An approach to drug research that relies on identifying relevant biochemical information using the company’s autonomous self-organizing semantic engines to text mine large repositories of biomedical research papers.

The model, says Trugenberger, is a departure from many other semantically-engineered approaches to streamlining drug research, which are based on natural language processing (NLP). That’s good for extracting information from documents, he says, but not as adept at discovering knowledge. “That’s what our InfoCodex software is designed for, to find new facts and hidden correlations” in repositories of unstructured information.

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Greg MacSweeney reports, “Thomson Reuters’ latest evolution of Eikon, its integrated market data platform, offers semantic search capabilities not found in other market data products currently on the market. Most notably the new version, called Eikon 3.0, applies free text search capabilities to financial data, similar to Google’s search functionality. ‘The latest version brings data into one place,’ says Philip Brittan, global head of the Eikon desktop platform at Thomson Reuters. Traditionally, market data platforms hold a wealth of data, but users need to know specific commands or follow certain workflows to find the information. ‘Often, getting to the data is a challenge,’ Brittan adds. ‘Eikon brings semantic search to financial information’.” Read more

Tom Groenfeldt of Forbes reports that Thomson Reuters is bringing semantic search to market information. He writes, “Looking up Cisco results on a Thomson Reuters Eikon terminal is as simple as typing in Cis. The name will autofill and you’re there.  Just like Google. Is nowhere safe from the consumerization of IT, not even trading rooms? ‘We want to change the way people interact with financial information,’ said Philip Brittan, global head of desktop platform at Thomson Reuters. ‘We are making it more like what modern search engines, such as Google, have done in the way you search the Web and interact with Web sites putting the search bar front and center allowing users to simply input what they are looking for’.” Read more

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Turmoil seems to be the default option for worldwide financial markets, but turns out there has been good news on the stocks front. According to a Bloomberg Businessweek article this week, U.S. stocks have had a solid 2012 so far, with the Standard & Poor’s 500 index up 9 percent this year, through Thursday, and Nasdaq up 15 percent. But the article also points out that hundreds of billions of dollars have fled the market here in the last three years.

It’s probably no surprise that skittishness reigns among average Americans, and institutional investors, too, given issues like the continuing economic volatility in Europe and more disappointing U.S. jobs data. But where many see problems, others see opportunities – including a new round of projects and vendors with semantic and sentiment analysis solutions aimed at helping investors ferret out what might be on the market’s minds.

The last couple of weeks alone saw the following unveiled:

• The EU FIRST (large scale inFormation extraction and Integration infrastructure for SupporTing financial decision making) consortium, which employs artificial intelligence to support financial decision making, launched its first running prototype of a technology that can extract and analyze sentiment about the financial domain from social media networks in near real-time. Read more

Thomson Reuters is looking for a Bioinformatics Analyst in Philadelphia, PA. The post states, “The role of Bioinformatics Analyst is to develop products and services that leverage internal and external ontologies, text mining and analytics to enhance the Life Sciences value propositions in core products and services engagements across the global organization. This highly motivated individual will be expected to take ownership of their workload; act independently & knowledgably as the key contact within the group for ontologies and text mining; work directly with internal and external customers to determine requirements and propose new offerings; work closely with Sales in customer engagements and work to deliver reusable components that answer specific business needs.” Read more

The financial services sector was in focus at this week’s Sentiment Analysis Symposium in New York City, which is organized and produced by Alta Plana Corp. and its founder, Seth Grimes.  Take, for example, the presentation by Rich Brown, head of Elektron Analytics at Thomson Reuters, who disclosed that the company is about to launch market response indicators in support of its Thomson Reuters News Analytics system for the financial community. That product this week also won The Technical Analyst’s 2012 award for best news analytics software.

With its software, originally discussed here, qualitative, unstructured information is turned into a quantitative data set allowing users – machines and humans – to quickly analyze thousands of news stories in less time than it takes to read a single headline, as Thomson Reuters describes it. It uses natural language processing technology to get to the end game, which is to forecast financial market response from news and social media sentiment. Some 82 fields of metadata come into play for automating the analysis of news content. That encompasses sentiment down through to the degree of positive, negative or neutral expressions and how individual companies mentioned in a piece fare in those respects – rather than just the tone of the piece at large. “The computational linguistics system measures the author’s tone as positive or negative on any given entity, which is important and the harder part of it,” Brown said. Other fields include, for example, relevance, genre, intensity of news flow, and more.

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Thomson Reuters is looking for a Consultant of Text Analytics in Philadelphia, PA. The post states, “The role of Consultant, Text Analytics is to develop products and services that leverage internal and external ontologies, text mining and analytics to enhance the Life Sciences value propositions in core products and services engagements across the global organisation. As a position this highly motivated individual will be expected to take ownership of their workload; act independently & knowledgeably as the key contact within the group for ontologies and text mining ; work directly with internal and external customers to determine requirements and propose new offerings; work closely with Sales in customer engagements and work to deliver reusable components that answer specific business needs.” Read more

The news of Facebook’s acquisition of mobile photo-sharing service Instagram for $1 billion this week may be fueling the dreams of tech start-ups of every stripe, including those in the semantic tech community. In fact, they may have even greater reason to be inspired: A recent  report has it that Instagram has been slowly rolling out an Open Graph integration for the app accomplished in collaboration with Facebook for seamlessly publishing photos to users’ Timelines in what may be the first of similar partner-deals down the road.

Other startups infused with semantic tech smarts may be on high lookout for funding opportunities as an important part of making those dreams come true. Thomson Reuters and The National Venture Capital Association this week released funding stats for the first quarter of 2012 that could put a bit of a damper on things: It found a 35 percent decrease by dollar commitments and a 9 percent decline by number of funds, compared to the first quarter of 2011. But, according to a statement by Mark Heesen, president of the NVCA, venture firms “appear to be more optimistic about the fundraising environment in 2012.”

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This article kicks off a series of interviews on Semantic Technologies in the MIT Entrepreneurship Review with industry thought leaders including Thomas Tague (Thomson Reuters), Chris Messina (Google), David Recordon (Facebook), Will Hunsinger (Evri) and Jamie Taylor (Metaweb).

At first sight, the answer is yes. I recently attended the Semantic Technology Conference in San Francisco. What had begun in 2005 as a 300-person conference has grown into a 5-day event with an amazing depth both of workshops and panels and over 1,300 participants this year. The conference is organized by Semantic Universe, an online platform with the goal of “educating the world about semantic technologies and applications”.

I have had the opportunity to talk to some of the key actors and innovators that have pushed semantic technologies and linked data forward over the past years since the term “Semantic Web” was first coined by Sir Tim Berners-Lee of the World Wide Web Consortium (W3C). The term takes on different meanings in different contexts: to some it is about representation of information in certain well-defined formats to make it machine-readable and easy to interpret; to others it is about web services and the aggregation of information to create valuable applications for users, while still others would highlight the artificial intelligence aspect and its use in tackling complex problems.

I have been personally drawn to the field of semantic technologies for some time, realizing the impact that these technologies will have on the way we consume information online as well as on the possibilities from an enterprise perspective. One thing I realized at the conference was that a lot of things that we take granted today, like online recommendations, are already powered by semantic technologies. In fact, a lot of the conversations happening in the hallways, between sessions, were not just around technical topics like how to best construct OWL ontologies or how to structure SPARQL queries, but rather about business issues like designing the right monetization models, improving e-commerce with semantic technologies, gauging the potential business impact of Facebook’s Open Graph, Twitter annotations or Google’s rich snippets. The New York Times, BBC, Newsweek, Tesco, Best Buy are some examples of companies that have been building and are relying on semantic technologies. To me, these are all strong indicators that semantic technologies have reached the tipping point.

Jamie Taylor, Minister of Information at Metaweb, the company behind Freebase, sees clear indications that semantic technologies have become more mainstream:  “Just the sheer size of the conference has increased pretty dramatically, as well as the diversity of people who actually have commercial offerings in terms of tools that matter to your typical webmaster, your typical content manager.” While there is still a strong academic track to semantic technologies, Taylor says, “it’s very interesting that sometimes semantic technologies have met the Web 2.0 lightweight user contribution-type model and as you add semantics into these types of systems – fairly lightweight semantics – all of a sudden they start getting much greater benefit.”

Managing one of the best-known semantic technology start-ups, Will Hunsinger, CEO of Evri, tells me that he has “seen a lot more activity in the last 12 month”. Naming Microsoft’s acquisition of Powerset and Apple’s acquisition of Siri as examples, he also points out that these “transactions have given validation that the technology is here and ready, but also that there is a path to liquidity.” One advice for startups and companies in the semantic technologies sector is to focus less on the technology itself and spend more time understanding consumers’ needs by asking themselves: “What does this technology do better than what’s out there such that you are going to solve a real problem”.  For example, at Evri, he adds “we create a better experience for the consumer applying the technology where it actually has a distinct advantage over keyword e.g. delivering precise results around general topics like “movies” or “reality tv”, understanding meaning and context (e.g. why is a particular entity popular right now) or even enabling consumers to follow topics over time”.

From a technological perspective, the recent developments around RDFa, a simpler version of RDF which allows users to add metadata to their content, will further accelerate the growth of the Semantic Web. Drupal 7, one of the biggest open source content management systems used on hundreds of thousands of websites, comes with major RDFa functionality. The latest HTML5 draft has RDFa support in it. Facebook’s Open Graph protocol is based on RDFa. Google Rich Snippets support RDFa. According to a recent GigaOM report, Twitter Annotations are looking to use it.

The benefits of semantic technologies with respect to making online search better are most obvious and to some extent already observable today. David Recordon, Senior Open Programs Manager at Facebook, sees some powerful applications in search, essentially “giving you a filter into the world based on your friends”. Thanks to semantic technologies built into the Facebook platform “developers [can] build on top of information which people have trusted Facebook with, whether that’s status updates or things they like, people they are connected to […]”. Google’s Open Web Advocate, Chris Messina, told me he agrees that social search will play a key role in the future: “we are starting to see Google integrating Twitter streams in search experience, hopefully providing users with more actionable information, providing a number of different opinions, more contextual data. It is certainly something Google is paying a lot of attention to – information that is contextual to the user, not just generic to the world.”

But what about exploiting the power of the semantic web by pulling in data from different sources, the premise of linked data? Thomas Tague, VP Platform Strategy at Thomson Reuters and in charge of the OpenCalais project, a free service to analyze and extract concepts from user-submitted texts or web sources, told me about the exciting opportunities he sees at the intersection of highly trusted monetized content and free web content. He says that “people are not going to make $100 million bets based on blog postings. But that blog posting may be an outlier, may be an initial indicator, maybe about a layoff at a factory or something like that, that the user can now immediately link back to Thomson Reuters data and gain insight and take action.” While Tague certainly shares the enthusiasm for the growth of semantic technologies and adoption of standards by industry participants, utilization of linked data remains low in his view. Therefore, his short-term outlook with respect to utilization of the linked data cloud, remains rather cautious: “There is a lot of talk about it, but with respect to our linked-data company information, people aren’t picking it up yet very much.”

So what can we expect in the near future? Jamie Taylor tells me that he thinks “the idea that you can aggregate is something very novel: all of a sudden my data is not limited to my data silo.” He distinguishes two types of data: core data, which must be managed by the organization to drive the core business, and context data–such as geo data. He believes that what “semantic technologies allow is in some sense to outsource [context data] to the community for maintenance.”

Overall, there seems to be consensus that as semantic technologies move out of the purely technical corner and beyond the innovators and early adopters in academia and government, content-heavy organizations and users like publishers or e-commerce sites will help these technologies cross the chasm as they see the largest benefit in applying the technology. As pointed out earlier, companies like The New York Times or Best Buy have already begun to build and rely on semantic technologies. As more and more companies start adopting linked data standards and share data in the linked data cloud, we will see more businesses created to derive value from aggregating data across different datasets to provide value to their users.

If this article has sparked your interest into semantic technologies, I can recommend a documentary by Kate Ray, a recent graduate from NYU with a major in Journalism/Psychology, who has contributed to the demystification of the Semantic Web through interviews with thought leaders, including Tim Berners-Lee, Clay Shirky, Chris Dixon, David Weinberger, Nova Spivack, Jason Shellen, Lee Feigenbaum, John Hebeler, Alon Halevy, David Karger and Abraham Bernstein. The clip has been viewed by more than 120,000 people so far. I asked Kate what motivated her to do the documentary: “My dad has been doing semantic web stuff for years, and my entire family never really knew what he was doing, so partly I was trying to make something that all these people here could show to their friends and family. I also had an academic interest in it.” Kate is now working on a company called Kommons, which she describes as a “Q&A forum built on top of Twitter; to let people ask questions to public figures – or anyone – and backing questions you agree with”.

MIT is at the forefront of exploring applications to commercialize linked data and semantic technologies, adding a new seminar, Linked Data Ventures, to the fall curriculum. The class will be taught by an all-star team consisting of Sir Tim Berners-Lee, Dr. Lalana Kagal, K. Krasnow Waterman, as well as Reed Sturtevant and Katie Rae. Computer science and business students will work in small teams to develop prototypes based on Semantic Web technologies.

About The Author

Rene Reinsberg is currently a member of the Entrepreneurship & Innovation program at MIT. His interests span Linked Data, Big Data, Open Data, and social graph analytics.

http://miter.mit.edu/article/have-semantic-technologies-crossed-chasm-yet