Jennifer Zaino
SemanticWeb.com Contributor

Semantic tags are in, free text tags are out. That’s what social bookmarking tool Faviki is advocating. Semantic tags will be a core building block of the next-generation web — and it’s leveraging the popular Wikipedia as a vast source of a universal controlled vocabulary to connect web pages to uniquely defined concepts.

“Wikipedia can serve as a great controlled vocabulary for tags because of its features,” says Vuk Milicic, the founder of Faviki who’s based in Serbia. “Every concept is unique, has a unique URI, and the concepts are well-defined. And DBpedia did a very good job of extracting the structure or semi-structure from Wikipedia and expressing it in RDF or a machine readable way.”

Milicic thinks the semantic web and the web of linked data remain somewhat complex concepts to much of the population, yet they are very comfortable with Web 2.0 concepts such as tagging and Web 2.0 creations such as Wikipedia. So, put a semantic spin on the tagging concept, leveraging the ‘central source of knowledge for mankind’ as Wikipedia is known, and now you’re building a more solid foundation for the next-generation web.

“Semantic tags are like words in a language,” he says, and you need the words before you can start creating a grammatical context around them.

By using the controlled vocabulary of Wikipedia as the basis for tags, Faviki helps users remove the ambiguity otherwise surrounding free text tags’ meaning. “You can use some concrete concepts as tags — for example, you can use yourself as the author as a tag and you can use specific organizations or companies or people or specific ideas as tags,” he says. With DBpedia’s linking between the various language versions of Wikipedia, Faviki also is able to let users tag in 14 different languages. It uses English as the universal reference, so a resource tagged by different users in Japanese, French, and German tags can be still found by using tags in Russian, he explains. Faviki currently uses 5.6 million DBpedia concepts — 2.7 million English titles and 2.9 million titles from other 13 languages.

Faviki also was involved in the development of the Common Tag Format, and has implemented it as the next logical step to the idea of semantic tags. In its most recent release last month, Faviki added the ability for users to use their own keywords or tags in a freeform way, much like classic tagging, and map them to semantic tags — connecting tagging with searching to accomplish this.

“So the tag is basically a Google keyword search which returns some relevant URL for that keyword,” that is restricted to Wikipedia’s domain, Milicic says. Additionally, the new release lets users create new tags outside of Wikipedia, using Google returns from the whole world of web pages and letting users collaborate on which URLs are the best candidates for new concepts.

He agrees that URL tags are not so clear as dbpedia: “They are a bit more messy and they are a bit more dynamic,” he says, “but the idea was to make it semi-automatic. People make them and disambiguate them while adding tags–it can’t be totally ideal but that is some kind of compromise.”

Next steps for Faviki are around connecting with other services such as del.i.cious, Twitter, and Facebook, to make it easier for users to try it out.

“Some longer-term plans would be to publish data from Faviki in linked data, to connect to the rest of inked data,” he says, as well as making that data queryable to developers via SPARQL. “We can make it as much a platform as an application by opening the data, because that’s the idea of the semantic web, to make the data open and connect easily to various sources,” he says. “And I think that in the future mappings between free tags’ association and some uniquely identified concepts will be very important, so I think that kind of data will be interesting to developers.”

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