Wikipedia |The Semantic Puzzle

Jury Award for Semantic Wikis in eGovernment, and: Semantic MediaWiki for Wikipedia?

September 24, 2008 by Jana Herwig, Category: Collective Intelligence, Internet & Media

An implementation of Semantic MediaWiki in public administration reiceved a jury award yesterday in the final ceremony of the highly coveted multimedia state award (Staatspreis Multimedia) 2008 in Vienna: Centre for Public Administration KDZ‘s platform for the cooperation of administrations (Plattform Verwaltungskooperation) in Austria, Germany, Italy and Switzerland received praise for its use of open, semantic technologies in their effort to further the collaboration between administrations and administrative staff. Those of you who can read German: read the response from Bernhard Krabina, KDZ, here or contact him here, if you’d like to learn more. The top state award itself went to HPC Dual, a combination of electronic and physical mail delivery.

Also published yesterday was an interview with Matthias Schindler, former member of board of Wikimedia Germany, at the occasion of the publication of a physical Wikipedia, i.e. a one-volume encyclopedia in print (publisher: Wissen Media, a Bertelsmann division). According to the English Wikipedia, “the volume is planned to include abbreviated entries for the 50,000 most commonly used search terms of the prior two years. The book is to be priced at 19.95 euros, with one euro from every sale going to the German chapter of the Wikimedia Foundation.”

The interviewers also asked Schindler for his “encyclopedic Wikipedia dream” – I hope his response will catch on in the Wikimedia chapters worldwide:

I would one day like to see a large edition of Wikipedia (including a German language edition), which makes use of the Semantic MediaWiki extension. The dream in a nutshell, without consideration of the current state of research and development: A wikipedia that can be read not only by humans, but also by computers, a Wikipedia that can offer concrete answers to concrete questions and that creates content individually for users, something that they can make use of; great if Wikipedia played the role of the first, mainstream Semantic Web application. While this is still in the process of coming together, there are enough other things for us to do.

(btw, my translation).

Concrete answers to concrete questions, a personalized Wikipedia – I am not even aiming that high at the moment.

Just consider the absurd amount of lists in Wikipedia, all of which are maintained manually. Take for instance the list of hardcore punk bands, the list of fictional countries (to be distinguished from the list of European fictional countries) or the list of military operations.

How often do you think these need an update? And if a new hardcore punk band is added – will the creators of the new article think about adding it to the list? What about articles which make make a reference to or mention things that are or should be on a particular list?

As a list has the inherent claim of being complete, it shouldn’t be left to humans to create and maintain them – leave that to the machines! Vote Semantic MediaWiki for Wikipedia!

Author: Jana Herwig

Semantic Tagging with Faviki

June 11, 2008 by Jana Herwig, Category: Tools & Software

In May, a new bookmarking service, Faviki, started which, unlike other bookmarking services, comes to the public semantically enhanced. ReadWriteWeb already had a first look at it and described it as follows:

Faviki is a new social bookmarking tool that offers something that services like Ma.gnolia, del.icio.us, and Diigo do not – semantic tagging capabilities. What this means is that instead of having users haphazardly entering in tags to describe the links they save, Faviki will suggest tags to be used instead. However, unlike other services, Faviki’s suggestions don’t just come from a community of users and their tagging history, but from structured information extracted straight out of the Wikipedia database. Faviki’s backend uses DBpedia, a community-maintained database created by extracting structured info from Wikipedia and turning that into a database which you can query.

What Faviki does, from a user’s perspective, is to suggest tags based on Wikipedia/DBpedia terms – one of the side effects of this procedure being that e.g. “Safety (disambiguation)” can also be chosen as a possible tag – I am not so sure yet whether this is an option that makes sense (although one can probably argue that it neither does any harm, because people should be smart enough not to use such tags). And as the above screen shot of Faviki’s tag cloud reveals, it currently seems to be mainly used by people who are interested in the semantic web and search engines (with semantic search being the most promising area of application of semantic technologies). It’s probably going to take a while (if ever) before Faviki is going to reach such a diverse user-base as can be guessed from del.icio.us’ tag cloud – but then again: Maybe Faviki isn’t going to need that, as it doesn’t rely on collective tagging, but already benefits from Wikipedia’s diversity of entries!

As was also regretted by ReadWriteWeb: It’s a pity that there is currently no opportunity to import tags from del.icio.us or other services to Faviki. Who is going to win the bookmarking race? Del.icio.us has the advantage of a broad user-base, and many users already have their networks of fellow bookmarkers which they probably wouldn’t want to give up (I personally wouldn’t). Bibsonomy has the advantage of an extra feature that allows to bookmark publications and later export them as a uniformly formatted bibliography. If I could make a wish, I’d rather have a service that brings together the best of Faviki, Bibsonomy AND del.icio.us!

Video: Links to DBpedia in TopBraid

April 30, 2008 by Jana Herwig, Category: Tools & Software

Two weeks ago (but still worthwhile mentioning) Holger Knublauch from Topquadrant made a little video for his blog, highlighting how DBpedia can be used to link different domain models with each other, a feature that’s now incorporated in TopBraid Composer 2.5.3. He explains DBpedia as

an RDF repository based on Wikipedia. DBpedia provides machine-readable RDF data for each of the pages in Wikipedia. Each Wikipedia page is represented by a corresponding RDF resource, and these resources are associated with RDF property values to provide descriptions, images, cross-references and tons of useful background knowledge. For example, the DBpedia pages for cities (e.g., Canberra) contain geographical information, the number of inhabitants, population density, links to famous inhabitants and average temperatures, all in machine-processable form. While these property values may not be totally stable and reliable, they are at least a good start.

However, the main benefit of DBpedia is that it provides relatively stable URIs for all relevant real-world concepts. This makes it a natural place to connect specific domain models with each other. If I publish my RDF files with links to DBpedia and you do the same, then we can automatically find cross-references and might more easily find mappings between our domain models. All I need to do is to add links such as { my:Canberra owl:sameAs dbpedia:Canberra }.

Here’s the link to the blogpost, and here the direct link to the video (*.wmv, 10,8 MB)

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