Posts Tagged ‘OWL’

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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Introduction to: SKOS

Nametag: "Hello, my name is SKOS"SKOS, which stands for Simple Knowledge Organization System, is a W3C standard, based on other Semantic Web standards (RDF and OWL), that provides a way to represent controlled vocabularies, taxonomies and thesauri. Specifically, SKOS itself is an OWL ontology and it can be written out in any RDF syntax.

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

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.

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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The Evolution of Semantic Technology In Publishing

“The idea of the Big S Semantic Web seems to have fallen off by the wayside in publishing as people are just trying to structure their data,” says Barbara McGlamery, taxonomist at Martha Stewart Living Omnimedia.

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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Introduction to: RDF vs XML

 There has always been a misconception between the relationship of RDF and XML. The main difference: XML is a syntax while RDF is a data model.

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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EQL: What Happens When SPARQL Meets SQL

Querying semantic databases isn’t necessarily the most user-friendly thing to do on the planet. Consultancy ABComputing is trying to change that, with its EQL (Entity Query Language) technology.

“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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New Tutorials at Semantic University

Cambridge Semantics has added a number of new lessons to their Semantic University. Some of the latest topics include the following:

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.” Read more

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