When the Nobel Prize winners for 2013 are announced in the fall, perhaps there also will be some challenges issued to the worldwide community of data enthusiasts to see what they can do with open Linked Data about the prizes that have been awarded since the beginning of the 20^th century.

Right now that’s just on the wish lists of Matthias Palmér and Hannes Ebner, co-founders of MetaSolutions AB, a spin-off from the Royal Institute of Technology in Stockholm and Uppsala University focused on semantic and scalable web apps. But a solid start has been made through their work with Nobel Media AB, which develops and manages programs, productions and media rights of the Nobel Prize within the areas of digital and broadcast media, including the Nobelprize.org domain, on the Nobel Prize Linked Data set.

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OWL, 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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RainVac has just launched a new web site, which they claim is the most advanced site on the Internet, utilizing fully compliant Semantic technologies and displaying on all devices. Vertex Worldwide, Inc. announced today that their RainVac division’s new web site has been launched, incorporating all the latest technologies to provide users with an ideal experience. The site makes extensive use of XHTML+RDFa technology, making it state-of-the-art in terms of rapidly developing semantic search capabilities. Read more

Ivan Herman of the W3C reports, “The W3C RDF Working Group has published a Candidate Recommendation of Turtle – A Terse RDF Triple Language. This document defines a textual syntax for RDF called Turtle that allows an RDF graph to be completely written in a compact and natural text form, with abbreviations for common usage patterns and datatypes. Turtle provides levels of compatibility with the existing N-Triples format as well as the triple pattern syntax of the SPARQL W3C Recommendation.” Read more

There’s more than one way to get a taxonomy. A company can go out and buy one for its industry, for instance, but the risk is that the terms may not relate to how it talks about content in its own organization, and the hierarchy may not be the right fit either. That sets up two potential outcomes, says Chris Riley, VP of marketing at Pingar: You wind up having to customize it, or with users who just ignore it.

It’s possible to build one, but that’s a big job and a costly one, too – especially for many enterprises, where there hasn’t traditionally been a focus on structuring content and so the skills to do it aren’t necessarily there. While industries like publishing, oil and gas, life sciences, and pharma have that bent, many other verticals do not. In fact, Riley notes, they may realize they have a content organization problem, but not that what they’d benefit from to address it even goes by the name ‘taxonomy.’

Pingar’s looking to help out those enterprises that want to bring organization to their content, whether or not they’re familiar with the concept of a taxonomy. It just launched its automated Taxonomy Generator Service that uses an organization’s own content to build a taxonomy that mirrors its own way of talking about things and its understanding of relationships between child and parent terms.

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It shouldn’t be surprising that Entagen, which makes the semantically-enabled Big Data analytics and collaboration engine TripleMap, has had its sights set on the life sciences space. CEO Christopher Bouton has his Ph.D in molecular neurobiology and has worked at a number of bio tech firms, as well as been the head of integrative data mining at Pfizer – a company that’s using TripleMap for visualized knowledge maps of associations between domain-specific entities (see our story here).

“We see some really compelling and exciting applications of this type of technology in the life sciences space,” says Bouton. But TripleMap can be applied to any scenario where Big Data dots must be connected so that users can collaborate around the understanding of the associations between entities – health care, legal, retail and finance all come to mind.

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A new article on R Bloggers explains how to get “up and running on the Semantic Web” using SPARQL with R in under five minutes. The article states, “We’ll use data at the Data.gov endpoint for this example. Data.gov has a wide array of public data available, making this example generalizable to many other datasets. One of the key challenges of querying a Semantic Web resource is knowing what data is accessible. Sometimes the best way to find this out is to run a simple query with no filters that returns only a few results or to directly view the RDF. Fortunately, information on the data available via Data.gov has been cataloged on a wiki hosted by Rensselaer. We’ll use Dataset 1187 for this example. It’s simple and has interesting data – the total number of wildfires and acres burned per year, 1960-2008.” Read more

Gregg Turner of Blue Claw Search recently discussed the impact of RDFa format data and why developers should implement it. Turner writes, “Rich snippets have become a lot more prominent within the SERPS over the past couple of years, with appealing, feature-rich listings becoming a more and more commonplace. Google refers to these enhanced search listings as “Rich Snippets”, and from a search marketing perspective they are often more appealing to users and increase Click Through Rates (CTR).” Read more

Ivan Herman of the W3C reports, “The W3C RDF Working Group has published a Working Draft of RDF 1.1 Concepts and Abstract Syntax. RDF 1.1 Concepts and Abstract Syntax defines an abstract syntax (a data model) which serves to link all RDF-based languages and specifications. The abstract syntax has two key data structures: RDF graphs are sets of subject-predicate-object triples, where the elements may be IRIs, blank nodes, or datatyped literals. They are used to express descriptions of resources. RDF datasets are used to organize collections of RDF graphs, and comprise a default graph and zero or more named graphs. This document also introduces key concepts and terminology, and discusses datatyping and the handling of fragment identifiers in IRIs within RDF graphs.” Read more

Courtesy: Flickr/LadyDragonflyCC <3

Yesterday we began our look back at the year in semantic technology here. Today we continue with more expert commentary on the year in review:

Ivan Herman, W3C Semantic Web Activity Lead:

I would mention two things (among many, of course).

•  Schema.org had an important effect on semantic technologies. Of course, it is controversial (role of one major vocabulary and its relations to others, the community discussions on the syntax, etc.), but I would rather concentrate on the positive aspects. A few years ago the topic of discussion was whether having ‘structured data’, as it is referred to (I would simply say having RDF in some syntax or other), as part of a Web page makes sense or not. There were fairly passionate discussions about this and many were convinced that doing that would not make any sense, there is no use case for it, authors would not use it and could not deal with it, etc. Well, this discussion is over. Structured data in Web sites is here to stay, it is important, and has become part of the Web landscape. Schema.org’s contribution in this respect is very important; the discussions and disagreements I referred to are minor and transient compared to the success. And 2012 was the year when this issue was finally closed.
•  On a very different aspect (and motivated by my own personal interest) I see exciting moves in the library and the digital publishing world. Many libraries recognize the power of linked data as adopted by libraries, of the value of standard cataloging techniques well adapted to linked data, of the role of metadata, in the form of linked data, adopted by journals and soon by electronic books… All these will have a profound influence bringing a huge amount of very valuable data onto the Web of Data, linking to sources of accumulated human knowledge. I have witnessed different aspects of this evolution coming to the fore in 2012, and I think this will become very important in the years to come.

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