On Friday, May 11, a group of Semantic Technology thought leaders from around the globe met with their host and colleague, Paul Miller, for the latest installment of the Semantic Link, a monthly podcast covering the world of Semantic Technologies. This episode includes a discussion about Semantics in the Financial Services Industry, and “the Linkers” were joined by special guest, Lee Feigenbaum, VP Marketing & Technology at Cambridge Semantics. Lee shared insights gained over many years working in the semantic technology field and with numerous customers in the financial services industry.
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SemTechBiz is Less Than 3 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 !

[Editor's Note: This guest post is by Tom Reamy, Chief Knowledge Architect and founder of KAPS Group, a group of knowledge architecture, taxonomy, and eLearning consultants. Tom has 20 years of experience in information architecture, intranet management and consulting, and education and training software.  Tom will be presenting a tutorial, Text Analytics for Semantic Applications and moderating a panel, Emotional Semantics - Beyond Sentiment at the upcoming SemTechBiz Conference in San Francisco.]

While sentiment analysis continues to generate a lot of press, it is not clear how much real value organizations are deriving from it.  One reason for that is that the standard approach to sentiment has been mostly statistical and/or long lists of sentiment terms.  However, if you add in other, advanced text analytics capabilities such as auto-categorization using advanced operators, you can not only develop more sophisticated sentiment analysis, you can also develop a whole new class of applications that either enhance and/or go beyond simple sentiment analysis.

These advanced operators include such commands as DEST_6 (count two words as a positive indicator only if they are with 6 words of each other) or SENT (only count words in the same sentence).

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NOTE: This post is provided by guest author, Mr. Dennis E. Wisnosky, Chief Technical Officer and Chief Architect, Business Mission Area, U.S. Department of Defense. Dennis will be delivering a Special Presentation, “The Enterprise Information Web: Analytics, Efficiency and Security” at the June SemTechBiz Conference.

Semantic Technology brings a number of unique capabilities to data stores and applications.  These capabilities evidence themselves both at the user interaction level, in what users can do with and expect from Semantic technologies; and at the system level, in terms of things applications can do internally without rework or recoding.  Semantic Technology, based upon W3C standards, provides capabilities significantly beyond those of proprietary approaches based on technologies that were founded a half century earlier.

1. User Interaction Capabilities

Access to Meaning

Semantic Technology is based upon the development of the ontology of a particular domain.   That is, “what do I need to know to have an unambiguous understanding of a particular thing, organization, subject, etc.?”  This knowing is based upon precise understanding of the meaning of words used in the domain.  A Semantic-Technology-based application depends on and provides a user with access to the defined meaning of the terms—the vocabulary, the words—used in the application.  This means access to a human-only readable definition, such as one found in a dictionary, and access to the formalized definition found in the ontology that frames the system which executes the application.  Such access should be presented in a human consumable form, and is one of the areas in which various formalisms such as Controlled Natural Language (CNL) are useful for translating technical forms of ontologies, such as the Web Ontology Language (OWL) , a W3C standard, to provide a human consumable form.

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On Friday, April 13, a group of Semantic thought leaders from around the globe met with their host and colleague, Paul Miller, for the latest installment of the Semantic Link, a monthly podcast covering the world of Semantic Technologies. This episode includes a discussion about various approaches to building semantic systems, and “the Linkers” were joined by special guest, Daniel Tunkelang, Principal Data Scientist, LinkedIn. Daniel — who will deliver a keynote address at the June Semantic Technology & Business Conference — shared insights gained over many years working at LinkedIn, Endeca, and Google, and IBM among others.
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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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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.

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In 2005, I started learning about the so-called Semantic Web. It wasn’t till 2008, the same year I started my PhD, that I finally understood what the Semantic Web was really about. At the time, I made a $1000 bet with 3 college buddies that the Semantic Web would be mainstream by the time I finished my PhD. I know I’m going to win! In this post, I will argue why.

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Semantic Web Community: I’m disappointed in us!  Or at least in our group marketing prowess.  We have been failing to capitalize on two major trends that everyone has been talking about and that are directly addressable by Semantic Web technologies!  For shame.

I’m talking of course about Big Data and NoSQL.  Given that I’ve already given my take on how Semantic Web technology can help with the Big Data problem on SemanticWeb.com, this time around I’ll tackle NoSQL and the Semantic Web.

After all, we gave up SQL more than a decade ago.  We should be part of the discussion.  Heck, even the XQuery guys got in on the action early!

Check out this Google Trends diagram.

NoSQL came out of nowhere in 2009, and now dominates much of the database conversation on the web.  Document stores like MongoDB and CouchDB, distributed, key-value stores such as Riak and Cassandra, and other weird stores like Hadoop-as-database (never understood that usage myself) now dominate the conversation as the alternative to traditional, SQL databases.

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I’m very happy to announce that the World Wide Web Consortium’s RDB2RDF Working Group, in which I participate as an Invited Expert,  has published two Candidate Recommendations: R2RML: RDB to RDF Mapping Language and A Direct Mapping of Relational Data to RDF. This has been a long road and we still have some ways to go. The standardization process goes back to the W3C Workshop on RDF Access to Relational Databases, which took place in October 2007. The W3C RDB2RDF Incubator Group followed afterwards. After almost 5 years, we are on track to have a standard. However, what is this standard bringing to the table?

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If you missed this excellent live webcast with Evren Sirin, CTO, Clark & Parsia, the recorded webcast is now available.  You also can meet Evren in Washington DC, November 29-December 1, 2011 for SemTechBiz DC. The customer mentioned in this case study, JP Morgan Chase, will be co-presenting and discussing how they are implementing Access Control using Semantic Technologies.

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Access control is an essential part of nearly every IT system; Read more