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The financial services industry is taking to semantic tech in an important way, and that’s in the form of the Financial Industry Business Ontology (FIBO), which aims to standardize the language used to precisely define the terms, conditions, and characteristics of financial instruments; the legal and relationship structure of business entities; the content and time dimensions of market data; and the legal obligations and process aspects of corporate actions. Attendees at SemTech Biz in San Francisco will get a deep dive on the how’s and why’s, at this session, while the FIBO Technology Summit invitation event will present an opportunity for working collaboratively to continue advancing the effort that has its roots in The Enterprise Data Management Council and communities of interests.

Leading that event will be Dennis E. Wisnosky, founder of Wizdom Systems, Inc. and former CTO and Chief Architect of the DoD Business Mission Area, who was recently named to provide technical strategy and operational guidance to help the Council finalize and implement FIBO standards, and David S. Newman, SVP & Strategic Planning Manager Enterprise Architecture at Wells Fargo, and Chair of the EDM Council’s Semantics Program. (Newman, with Enterprise Data Management Council Head of Semantics and Standards Mike Bennett, will also host the SemTech FIBO session.)  Speaking of the upcoming event, Wisnosky explains that a goal is to cast a wide net to find the new tech ideas and developments that both can bring benefits to FIBO in the short term and influence the longer-term research agenda to help the financial industry.

As FIBO stands now, in June the second draft of the FIBO Foundations ontology and the conceptual FIBO Business Entities ontology will be presented at a meeting of the Object Management Group in Berlin. By year’s end it is expected that the OMG will have ratified these as formal standards. “We are on the path to turn the corner from thinking of what FIBO will be to delivering it,” says Wisnosky. continued…

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IT leaders keeping an eye on Gartner’s top tech trends list know that early in March semantic technologies made the cut (see our original story here, and our follow-up with one of the authors of the Gartner report here). The big question for many enterprise IT pros, though, is what should they be doing with that knowledge – how can they start leveraging semantic technology to their own organizations’ benefit?

Help is on the way. Three experts in semantic web technologies and Linked Data weigh in with their advice on heading down that road:

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The research firm yesterday released the list of nine trends that it says will play key roles in modernizing information management and in making the role of information governance increasingly important. Semantic technologies come in at No.3 on the list – right behind closely-tied-to trends Big Data and modern information infrastructure.

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OWL evolved from several proposals and became a standard in 2004. This was subsequently extended in 2008 by a second standard version, OWL 2. With OWL, you have the possibility of expressing all kinds of knowledge. The basic building blocks of an ontology are concepts (a.k.a classes) and the relationships between the classes (a.k.a properties).  For example, if we were to create an ontology about a university, the classes would include Student, Professor, Courses while the properties would be isEnrolled, because a Student is enrolled in a Course, and isTaughtBy, because a Professor teaches a Course.

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“A study is not a study on its own,” says Forsberg. Today, the goal is  to do meta-analysis across many studies, so parties ranging from  pharmaceuticals companies to contract research organizations to government authorities all are ‘customers’ of clinical data, so to speak. Data from various studies must be shared among all these parties. “It puts a new context around clinical trial data, that it must be easy to link data together, to link across several different studies,” she says.

The case is there to use modern information standards, like semantic web standards and Linked Data principles, to address this need. It’s why Forsberg is one of the individuals spearheading a volunteer effort to create RDF and OWL representations of the standards published by the Clinical Data Interchange Standards Consortium (CDISC) an international, non-profit organization that develops and supports global data standards for medical research.

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In recent blogs we’ve discussed where semantic technologies have gone in 2012, and a bit about where they will go this year (see here, here and here).

Here are some final thoughts from our panel of semantic web experts on what to expect to see as the New Year rings in:

John Breslin,lecturer at NUI Galway, researcher and unit leader at DERI, creator of SIOC, and co-founder of Technology Voice and StreamGlider

Broader deployment of the schema.org terms is likely. In the study by Muehlisen and Bizer in July this year, we saw Open Graph Protocol, DC, FOAF, RSS, SIOC and Creative Commons still topping the ranks of top semantic vocabularies being used. In 2013 and beyond, I expect to see schema.org jump to the top of that list.

Christine Connors, Chief Ontologist, Knowledgent:

I think we will see an uptick in the job market for semantic technologists in the enterprise; primarily in the Fortune 2000. I expect to see some M&A activity as well from systems providers and integrators who recognize the desire to have a semantic component in their product suite. (No, I have no direct knowledge; it is my hunch!)

We will see increased competition from data analytics vendors who try to add RDF, OWL or graphstores to their existing platforms. I anticipate saying, at the end of 2013, that many of these immature deployments will leave some project teams disappointed. The mature vendors will need to put resources into sales and business development, with the right partners for consulting and systems integration, to be ready to respond to calls for proposals and assistance.

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Before we dive into SKOS, what is the difference between Controlled Vocabulary, Taxonomy and Thesaurus?

A controlled vocabulary is a list of terms which a community or organization has agreed upon. For example: Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday are the days of the week.

A taxonomy is a controlled vocabulary organized in a hierarchy. For example, we can have the terms Computer, Tablet and Laptop and the concepts Tablet and Laptop are subclasses of Computer because a Tablet and Laptop are types of Computers.

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McGlamery, who will be presenting a case study comparing her experiences in two publishing houses that took opposite approaches to the semantic web at the SemTech conference in NYC this month, says that the path most publishers are on now “hardly seems like the same beast” as the one she formerly knew. A few years back, the focus was on RDF, OWL, full-blown ontologies and inferencing engines, whereas today “it’s schema.org and we’re using microdata, not even RDFa.”

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RDF has several syntaxes (Turtle, N3, etc) and XML is one of those (known as RDF/XML). Actually, RDF/XML is the only W3C standard syntax for RDF (Currently, there is Last Call on Turtle, a new W3C standard syntax for RDF). Therefore, comparing XML and RDF is like comparing apples with oranges. What can be compared is their data models. The RDF data model is a graph while the XML data model is a tree.

Comparing RDF with XML

Joshua Tauberer has an excellent comparison between RDF and XML, which I recommend. Two advantages of RDF are highlighted: flexibility of the data model and use of URIs as global unique identifiers.

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“We wanted to where possible have it so the syntax was more closely mirrored with SQL than with SPARQL because people understand SQL,” says Martin Bradford, primary developer at the company. “If you build on that knowledge, that helps matters.”

EQL came about from the company’s work on a potential contract that involved semantic technology. Exposure to the world of semantic web technologies and SPARQL in particular led Antonia Bradford, who started the firm a couple of decades ago, to conclude that there had to be a better way of working with RDF data without sacrificing the power inherent in the semantic web.

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SPARQL 101: “SPARQL (pronounced “sparkle”) is the query language for the Semantic Web. Along with RDF and OWL, it is one of the three core technologies of the Semantic Web. This lesson introduces the SPARQL query language, starting with simple queries. Future lessons will build on this material with more advanced SPARQL concepts.” continued…

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First, a little bit about the bigger picture.  “What can happen when you go all the way to semantic, model-driven, knowledge computing [is that] … it changes the game for development,” says Mills Davis, managing director of Project 10X and one of the session’s presenters. “It enables new categories of capabilities and levels of user experience (think SIRI for the rest of us). It brings about quantum changes in all stages of lifecycle value. It enables cost-effective strategy-driven approaches to enterprise transformation. This last sentence is worth some reflection.”

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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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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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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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