Posts Tagged ‘OWL’

Semantic Web Job: Healthline

Healthline Networks LogoHealthline Networks is seeking an Informatics Sr. Java Software Engineer in San Francisco, California. This position offers the opportunity to “Work with dynamic Engineering and Medical Informatics Teams to enhance Healthline’s medical ontology. Healthline is a web health technology company, employing tools for the future.” The Responsibilities include: “Design and implement algorithms for integrating medical standard dictionaries into Healthline ontology; Develop data mining processes to create our Semantic Network; Work on an authoring tool that allows Medical Informatics Specialists to successfully and easily edit our ontology; Read more

A Look Into Learning SPARQL With Author Bob DuCharme

Cover of Learning SPARQL - Second Edition, by Bob DuCharmeThe second edition of Bob DuCharme’s Learning SPARQL debuted this summer. The Semantic Web Blog connected with DuCharme – who is director of digital media solutions at TopQuadrant, the author of other works including XML: The Annotated Specification, and also a welcome speaker both at the Semantic Technology & Business Conference and our Semantic Web Blog podcasts – to learn more about the latest version of the book.

Semantic Web Blog: In what I believe has been two years since the first edition was published, what have been the most significant changes in the ‘SPARQL space’ – or the semantic web world at large — that make this the right time for an expanded edition of Learning SPARQL?

DuCharme: The key thing is that SPARQL 1.1 is now an actual W3C Recommendation. It was great to see it so widely implemented so early in its development process, which justified the release of the book’s first edition so long before 1.1 was set in stone, but now that it’s a Recommendation we can release an edition of the book that is no longer describing a moving target. Not much in SPARQL has changed since the first edition – the VALUES keyword replaced BINDINGS, with some tweaks, and some property path syntax details changed – but it’s good to know that nothing in 1.1 can change now.

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The Business Value of Reasoning with Ontologies

[Editor's note: this guest post was co-written by Héctor Pérez-Urbina (Clark & Parsia) and Juan Sequeda (Capsenta)]

Image of a human brain with computer data overlay.Important enterprise business logic is often buried deep within a complex ecosystem of applications. Domain constraints and assumptions, as well as the main actors and the relations with one another, exist only implicitly in thousands of lines of code distributed across the enterprise.

Sure, there might be some complex UML diagrams somewhere accompanied by hundreds of pages of use case descriptions; but there is no common global representation of the domain that can be effectively shared by enterprise applications. When the domain inevitably evolves, applications must be updated one by one, forcing developers to dive into long-forgotten code to try to make sense of what needs to be done. Maintenance in this kind of environment is time-consuming, error-prone, and expensive.

The suite of semantic technologies, including OWL, allows the creation of rich domain models (a.k.a., ontologies) where business logic can be captured and maintained. Crucially, unlike UML diagrams, OWL ontologies are machine-processable so they can be directly exploited by applications.

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Introduction to: Reasoners

Name Tag: Hello, we are ReasonersReasoning is the task of deriving implicit facts from a set of given explicit facts. These facts can be expressed in OWL 2 ontologies and stored RDF triplestores. For example, the following fact: “a Student is a Person,” can be expressed in an ontology, while the fact: “Bob is a Student,” can be stored in a triplestore. A reasoner is a software application that is able to reason. For example, a reasoner is able to infer the following implicit fact: “Bob is a Person.”

Reasoning Tasks

Reasoning tasks considered in OWL 2 are: ontology consistency, class satisfiability, classification, instance checking, and conjunctive query answering.

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SemTechBiz Puts Spotlight On Financial Industry Business Ontology

Image Courtesy: Flickr/Patrick Hoesly

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. Read more

For The Enterprise IT Set: Steps To Success With Semantic Tech

Courtesy: Flickr/ clbean

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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Gartner Names Semantic Technologies To Its Top Technology Trends Impacting Information Infrastructure in 2013

Semantic technologies have made it to Gartner’s list of the top technology trends that will impact information infrastructure this year.

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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Introduction to: OWL Profiles

Name Tag: Hello, we are the OWL familyOWL, the Web Ontology Language has been standardized by W3C as a powerful language to represent knowledge (i.e. ontologies) on the Web. OWL has two functionalities. The first functionality is to express knowledge in an unambiguous way. This is accomplished by representing knowledge as set of concepts within a particular domain and the relationship between these concepts. If we only take into account this functionality, then the goal is very similar to that of UML or Entity-Relationship diagrams. The second functionality is to be able to draw conclusions from the knowledge that has been expressed. In other words, be able to infer implicit knowledge from the explicit knowledge. We call this reasoning and this is what distinguishes OWL from UML or other modeling languages.

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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Clinical Studies And The Road To Linked Data

Clinical studies aren’t what they used to be. In the past, the process was one-off: You conducted a study, gathered a lot of data, analyzed it, wrote a report, and submitted it to the authorities. But, says long-time Linked Data advocate Kerstin Forsberg, an information architect at AstraZeneca, that’s all changed in the last few years.

“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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Semantic Tech Outlook: 2013

Photo Courtesy: Flickr/Lars Plougmann

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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