[Editor's Note: SemanticWeb.com was a co-sponsor of the Linked Data Platform proposal that led to the creation of the Linked Data Platform Working Group discussed here.]

Ian Jacobs reports, “Shortly after W3C announced the launch of the Linked Data Platform Working Group, I spoke with Arnaud Le Hors about IBM’s interest in linked data and their decision to co-chair the Working Group.” Asked why IBM became involved with organizing the Linked Enterprise Data Patterns Workshop and the Linked Data Platform Working Group, Le Hors responded, “IBM has been involved in Semantic Web activities from the beginning, but primarily from a research perspective. Until recently we had no products using the technology. Now we have IBM Rational, which develops a set of tools for application and product lifecycle management (requirements, bugs, etc.). Other parts of IBM are actively exploring it for complementary purposes. Customers typically use tools from more than one vendor and require integration; this is a problem IBM addresses.” Read more

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 !

Ivan Herman recently offered some insight into how Watson actually works. Herman reports, “I was at Chris Welty’s keynote yesterday at the WWW2012 Conference. His talk was on Jeopardy/Watson and, although this is not the first time I heard/saw something on Watson, some things really became clear only at his keynote. Namely: what is really the central paradigm that made the question answering mechanism so successful in the case of Watson? Well… query answering in Watson is not some sort of a deterministic algorithm that turns a natural language question into a query into a huge set of data. This approach does not work.” Read more

This year was the 5th version of the Linked Data on the Web Workshop co-located at the World Wide Web Conference going on in Lyon, France.

At this workshop, seven issues caught my attention:

1) Media: Yunja Li presented on Synote: Weaving Media Fragments and Linked Data. This is interesting for those who not only want to link to an entire video, but want to link to a part of a video at a specific interval of time, and also add metadata information about that.

2) NLP to Linked Data: How can we relate the results of different named entity extraction tools to Linked Data. Giuseppe Rizzo introduced their project, NERD, which is working on this area.

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We caught up with Bernie Spang, IBM’s Director, Strategy and Marketing, Database Software and Systems, to discuss the latest release of its enterprise data products DB2 and InfoSphere. Version 10 of both products have just been released. DB2 is used by thousands of organizations worldwide and comes in flavors ranging from a free version that maxes out at 2GB storage to systems that support large enterprises (Coca-Cola was an early adopter of DB2 version 10, and is already reporting cost-savings of over $1 Million).

The latest version of DB2 is the first in four years and represents a significant release, according to Spang, “This is a culmination of four years of effort by hundreds of engineers in IBM Research and Software Development Labs around the world; we also had more than 100 clients and over 200 business partners involved in the ‘early access program’ to help deliver this software. With the fundamental goal of delivering faster, easier, lower-cost data management.”

The early testing is showing positive results, with customers reporting “up to 10x faster data warehouse queries; freeing up to 90% of storage space using compression; and 98% code compatibility with Oracle Database, which makes it easier to migrate from Oracle to IBM software without changing data or retraining staff.”

For our readers, though, one of the more intriguing new features of DB2 is its built-in support for RDF. While semantics is not new to IBM — IBM Watson has gained particular fame — the appearance of RDF support in such a widely used, stable, enterprise database system is exciting.
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IBM is looking for a Research Staff Member – Semantic Analysis and Integration in Hawthorne, NY. According to the post, “The Semantic Analysis and Integration Department at the IBM T.J. Watson Research Center is seeking Research Staff Members on to work on research and applications of intelligent human language technologies. The project focuses on developing general and reusable Question Answering(QA) systems to achieve reproducible high-performing results for open-domain and specialized-domain question answering. This project offers the opportunity to work with more than 30 IBM researchers with backgrounds in NLP, IR, ML, KR&R, and DB across multiple IBM research labs, as well as the opportunity to collaborate with our university partners. Our lab has access to large compute resources and a large variety of NLP, IR and KR&R component technologies.” Read more

Joab Jackson of PC World reports, “IBM has updated its flagship DB2 relational database management software to handle a wider range of data processing duties. The company has also updated its InfoSphere data warehouse software, IBM announced Tuesday.” Bernie Spang, IBM’s director of strategy and marketing for database systems commented, “We believe we’re in a new era of data management. The answer to every data challenge today is not to use a relational database management system. It’s about using the right tool for the right job.” Read more

In December 2011, the World Wide Web Consortium held “The Linked Enterprise Data Patterns workshop,” and that workshop ended with unanimous agreement that “the W3C should create a Working Group to produce a W3C Recommendation which defines a Linked Data Platform.”

In response to that call, SemanticWeb.com has joined experts from fellow W3C member Organizations IBM, DERI, EMC, Oracle, Red Hat, and Tasktop in submitting the “Linked Data Basic Profile 1.0” specification as a W3C Member Submission.  This specification defines a set of best practices and a simple approach for a read-write Linked Data architecture, based on HTTP access to web resources that describe their state using RDF.  The specification builds on the four principles Tim Berners-Lee used to define “Linked Data” and provides some new rules as well as clarifications and extensions to achieve greater interoperability between Linked Data implementations.

Read more here

IBM is looking for a Research Intern – Semantic Modeling and Tools for Smarter Cities in Hawthorne, NY. The post states, “We currently have an internship opportunity available in the area of Smarter Cities modeling and semantic modeling tools, part of the Extensible Technologies department. In our department, we develop new approaches to modeling and managing linked, and semantically annotated data, and work on applications of the technology to the Smarter Cities domain. Over the years, our department has created some of the core XML and SOA standards, and has developed innovative runtime and tooling capabilities in support of those standards.” Read more

Earlier this month 16 out of 42 papers were accepted for the upcoming Linked Data on the Web (LDOW) 2012 Workshop in Lyon, France in April.

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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Watson’s gone into banking: Citi is evaluating ways that IBM’s Deep QA technology can help advance digital banking efforts, through analysis of customer needs and processing tons of up-to-the-minute financial, economic, product and client data, according to a press release.

“We are working to rethink and redesign the various ways in which our customers and clients interact with money. We will collaborate with IBM to explore how we can use the Watson technology to provide our customers with new, secure services designed around their increasingly digital and mobile lives,” said Don Callahan, Citi’s Chief Administrative Officer and Chief Operations & Technology Officer in the press statement. The plan is to use Watson’s NLP capabilities for analyzing human-language questions and drawing upon its interpretations of the query to derive potential answers that it then tests, validates, and scores, to help financial reps sort out options, opportunities and risks targeted to a consumer’s individual circumstances.

Earlier this year, IBM paired up with WellPoint in a strategic partnership in another vertical sector, health care, with the goal of using Watson’s DeepQA to help physicians improve treatment for oncology patients by assessing medical evidence and personal case data to deliver probability-based treatment options.

But financial services has always been discussed as an industry that could benefit from Watson’s brainpower, too. In a video here, Dr. Carl Abrams of IBM Research, Financial Services, says that, “The currency of financial services is information, and the ability to semantically analyze that, to extract from that what the meaning is, and then take that meaning and apply it to something is simply becoming a level playing field.”

Financial services executive Jay Dweck, formerly global head of strategy and technology at Morgan Stanly, notes in the video that data in the sector is growing about 70 percent a year, and that having this much data requires a large range and variety of tools to be able to extract real knowledge from it. “You could put together the logical connections among the disparate pieces of information,” he said.