Karen Coyle recently analyzed a new release of OCLC metadata records. She writes, “OCLC recently released a file of 1.2 million metadata records for the most widely held items in its catalog. These are all items with 250 library holdings or more. I created a list on WorldCat of the top 50, mostly out of curiosity. I was quite surprised at the results, however. Here’s how it breaks down: 16 periodicals, with Time and Newsweek being numbers 1 and 2, respectively; 29 kid and YA books, four of which (and very high even in this small list) from the Diary of a Wimpy Kid series; 5 adult books.”

Coyle goes on, “The five adult books are: (1) McCullough, D. G. (1992). Truman. New York: Simon & Schuster. (2) Brown, D. (2003). The Da Vinci code: A novel. New York: Doubleday. (3) Johnson, S. (1998). Who moved my cheese?: An a-mazing way to deal with change in your work and in your life. New York: Putnam.  (4) Haley, A. (1976). Roots. Garden City, N.Y: Doubleday.  (5) Peters, T. J., & Waterman, R. H. (1982). In search of excellence: Lessons from America’s best-run companies. New York: Harper & Row. This small set gives me many ideas of things to investigate in the full set.”

Read more here.

Image: Courtesy OCLC

The Conductrics blog has shared a list of data science and machine learning resources. The introduction states, “Every now and then I get asked for some help or for some pointers on a machine learning/data science topic.  I tend respond with links to resources by folks that I consider to be experts in the topic area.   Over time my list has gotten a little larger so I decided to put it all together in a blog post. Since it is based mostly on the questions I have received, it is by no means complete, or even close to a complete list, but hopefully it will be of some use.  Perhaps I will keep it updated, or even better yet, feel free to comment with anything you think might be of help. Also, when I think of data science, I tend to focus on Machine Learning rather than the hardware or coding aspects. If you are looking for stuff on Hadoop, or R, or Python, sorry, there really isn’t anything here.” 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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Courtesy: Flickr/zoetnet

As we close out 2012, we’ve asked some semantic tech experts to give us their take on the year that was. Was Big Data a boon for the semantic web, or is the opportunity to capitalize on the connection still pending? Is structured data on the web not just the future but the present? What sector is taking a strong lead in the semantic web space?

We begin with Part 1, with our experts listed in alphabetical order:

John Breslin, lecturer at NUI Galway, researcher and unit leader at DERI, creator of SIOC, and co-founder of Technology Voice and StreamGlider:
I think the schema.org initiative really gaining community support and a broader range of terms has been fantastic. It’s been great to see an easily understandable set of terms for describing the objects in web pages, but also leveraging the experience of work like GoodRelations rather than ignoring what has gone before. It’s also been encouraging to see the growth of Drupal 7 (which produces RDFa data) in the government sector: Estimates are that 24 percent of .gov CMS sites are now powered by Drupal.

Martin Böhringer, CEO & Co-Founder Hojoki:

For us it was very important to see Jena, our Semantic Web framework, becoming an Apache top-level project in April 2012. We see a lot of development pace in this project recently and see a chance to build an open source Semantic Web foundation which can handle cutting-edge requirements.

Still disappointing is the missing link between Semantic Web and the “cool” technologies and buzzwords. From what we see Semantic Web gives answers to some of the industry’s most challenging problems, but it still doesn’t seem to really find its place in relation to the cloud or big data (Hadoop).

Christine Connors, Chief Ontologist, Knowledgent:

One trend that I have seen is increased interest in the broader spectrum of semantic technologies in the enterprise. Graph stores, NoSQL, schema-less and more flexible systems, ontologies (& ontologists!) and integration with legacy systems. I believe the Big Data movement has had a positive impact on this field. We are hearing more and more about “Big Data Analytics” from our clients, partners and friends. The analytical power brought to bear by the semantic technology stack is sparking curiosity – what is it really? How can these models help me mitigate risk, more accurately predict outcomes, identify hidden intellectual assets, and streamline business processes? Real questions, tough questions: fun challenges!

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Edamam, which has built a food ontology for its food knowledge site (which The Semantic Web Blog initially covered here), is adding an iPad version of its app to its existing iPhone and Android versions. The company also did a full relaunch of its web site to optimize the experience for desktop users, as well, with improved browsing and search.

Originally, the web site app mirrored the mobile versions. But, says co-founder and CEO Victor Penev, “We realized that people wanted to be able to access recipes and search on the desktop, and they should have a holistic experience from anywhere.” While the company had been more focused on the mobile arena, Penev says building traffic for the website is going to be a priority too. Among the capabilities users should see in the near future are functions like one that will let people save recipes on their iPhone or Android mobile devices and then access them on their iPads or desktops, or vice verse.

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Richard Wallis of DataLiberate recently wrote, “Back in September I formed a W3C Group – Schema Bib Extend.  To quote an old friend of mine ‘Why did you go and do that then?‘  Well, as I have mentioned before Schema.org has become a bit of a success story for structured data on the web.  I would have no hesitation in recommending it as a starting point for anyone, in any sector, wanting to share structured data on the web.  This is what OCLC did in the initial exercise to publish the 270+ million resources in WorldCat.org as Linked Data. At the same time, I believe that summer 2012 was a bit of a watershed for Linked Data in the library world.  Over the preceding few years we have had various national libraries publishing linked data (British Library, Bibliothèque nationale de France, Deutsche National Bibliothek, National Library of Sweden, to name just a few).  Read more

One of the exciting things about being a semantic technologist is the opportunity to be in on the ground floor of things as companies revamp, revise, and renew their infrastructures for the Web 3.0 world.

That’s the position that Keith DeWeese finds himself in. DeWeese recently moved from The Tribune Company, where he led efforts in applying semantic technology to the publisher’s content (see story here), to Ascend Learning, a company that provides technology-based education products with a focus on the healthcare sector.

There, as principal content architect he is again championing the power of semantic technology for online content. “What’s cool is that Ascend is in a state of redefining what it does, how it works, its whole platform,” DeWeese says. Ascend wants to be able to take people from the beginning stages of their career, when they’re learning the basics, and work with them throughout their life, so that as they progress in their careers and become more knowledgeable about their profession or specialization and work toward different exams, it’s got the tools to engage with them at that part of their lifecycle.

“It’s really great because there’s an openness and willingness to try different approaches to making content available to end users.”

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Dave Mccomb of Semantic Arts recently discussed how inspiration plays a part in designing ontologies. He writes, “It seems that there are three ways that ontologies are or can be related to applications. They are: (1) Inspiration. (2) Transformation. (3) Extension. To put this conversation in context, let’s go back to the ‘tic tac toe’ board [above]. What it is attempting to convey is that there are levels of abstraction and differences in perspective that we should consider when we are modeling. An application is in the lower middle cell. Data models are in the middle square. Ontologies could be anywhere. An ontology is a formal way of representing a model. And so we could have an ontology that describes an application, an ontology of a logical model, even ontologies of data or meta meta data.” Read more

According to the team at MakoLab SA, the company has published a new ontology that supports precise descriptions of used cars. The Used Cars Ontology (UCO) was created in cooperation with Professor Martin Hepp (Hepp Research GmbH), creator of the GoodRelations ontology. The Used Cars Ontology “represents knowledge concerning used cars regardless of their manufacturer. The notions included in it cover properties which are significant in the used cars market and characterize the basic state of a given car, such as car modifications, damages, additions, information about the owner, as well as more detailed data, such as whether the owner of the car smoked cigarettes, what kinds of animals were transported in the car, etc.” Read more

David S. Read of Information Week recently discussed the benefits of semantic databases. He writes, “Don’t buy into the idea that semantic database technologies are just for consumer-facing services such as BBC Online or the semantic Web initiatives embraced by the likes of Best Buy and Cisco. In much the same way that consumerization drives innovation in end user computing, semantic database technologies deliver benefits that businesses of all stripes should be exploiting. At a high level, semantic databases offer five main benefits: They work with your existing relational databases. They align with Web technologies. Their underlying technology speeds integration of multiple databases. They’re based on data structures that are flexible by design. And thus they can help enterprises tackle big data challenges.” Read more