Zitgist’s RDF Browser: Browse the Semantic Web

Frederick Giasson

I am pleased to announce the pre-release of the Zitgist RDF Browser. This new tool from Zitgist will help users to browse the information available on the Semantic Web. As you will see bellow, this tool is a sort of information shape-shifter. Depending on the data available for a given Thing (a resource), it will shapes its user interface so that the data is best displayed for a better understanding of its semantic and for a better browsing experience.

This pre-release version is usable by anybody, however I would appreciate that you report any bug, issues or suggestions to me so that I can enhance the browser to meet people’s expectations.

Introducing Zitgist’s RDF Browser

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The Templating system

The core of this new RDF browser is its templating system. This system will enhance the RDF browsing experience of users along with their understand of the information displayed to them. People can see it as a typical web browser such as Internet Explorer or FireFox, but instead of reading and displaying HTML, it display RDF data. Users only have to put the URI of a resource (it can be a URL where the browser can find RDF information about this Thing), then pressing the “browse” button.

Then, depending on the information available about this Thing, the RDF browser will shape its interface to optimize users’ browsing experience with the data.

Sources of data

Data displayed in the Zitgist RDF Browser can come from many different data sources:

  • Zitgist’s internal RDF datastore
  • URI dereferencing
  • On-the-fly conversation of data sources such as:
    • Microformats
    • RDFa
    • eRDF
    • HTML meta tags
    • API data source such as: Amazon.com, Google Base, etc.

So, depending on what information is available for a given URI, the browser will mesh-up these data sources and displays the information to the user.

First example of the templating system

first_example_madonna.jpg

This first example shows how the browser will create a web page out of a RDF data source. In this case, the data source is a URI where Madonna’s latest album “Confession on a Dance Floor” is described.

  1. The browser will check for that URI: http://zitgist.com/music/record/d7929b28-5812-4b8f-a99f-1800983c71fb
  2. No information is available in its data store, so it will dereference the URI to get the RDF triples describing the album.
  3. All in all, 15 different URIs will be dereferenced to create the web page.
  4. The browser will detect that the type of the entity related to this URI is a mo:Album; so it will triggers the “moAlbum” template to skin the data source so that the user can easily see and understand the information we have about this resource (music album).
  5. Then the skinned information is displayed to the user.

The templating system in action

Now we will see the templating system in action. In fact, the RDF browser does much more than skinning a single data source.

embedded_templates_1.jpg

If you put that URI in the browser, you will see Sebastian’s profile. The browser will fire the foafPerson template, and his profile will be skinned according to this template.

However, what is interesting in that example is not only Sebastian’s profile, but the entities it links to. In fact, if you take a closer look and go down the page a little bit, you will notice the “Current projects” section of his profile. Then you will see a list of projects.

embedded_templates_2.jpg

The first project is a musical group described as a foaf:Group. So, the browser will check the URI Sebastian’s profile link to, get information about it, skin it accordingly to the foafGroup template, and embed the result within Sebastian’s profile page.

Since we could embed such entities at infinitum, the browser restricts this automatic browsing to 3 deep levels in the graph.

Finally, we can “lookup” an individual embedded item by clicking on the lookup icon at the upper right corner of each entity.

Sidebar Navigator

In some cases some generated web page can be quite large, so a navigation widget has been developed to help users to navigate generated documents. The navigation of a document is based on the entities displayed in it.

For example, if we run the Zitgist RDF Browser for that URI: http://www.macosxhints.com, we will notice that information displayed is many pages long. So, to help us navigating this long document, we will use the entity navigator widget.

navigator.jpg

 

All the types available in that web page are listed in the sidebar, and for each type you have all the instances available.

In that example, you can easily browse the web feed of that web page. In a click, you can see all Posts, Feeds and Authors.

Interesting examples

There is a list of starting points to see the Zitgist RDF Browser in action:

  • And all the examples above.

Bookmarklet

The Zitgist RDF Browser can process any URI. So, from any web page, a user can launch the browser to see what semantic web information is available for that URI. Then, all the information the browser can find/generate out of that data source will be displayed to the user.

To help users, I developed this really simple bookmarklet that get the URI of the current web page, send it to the browser, and then redirect the user to the browser’s generated page.

Zitgist RDF Browser’s Bookmarklet

 

Conclusion

As you noticed above, this new RDF browser is a sort of information shape-shifter. Depending on the information available for a given URI, it will skin it to make it easier to browse and understand for users.

My Personal Library and the Semantic Web

Frederick Giasson

Since the last couple of years, I was constantly reminding myself to put all the titles, authors and ISBN of my library in a database so that I could say to my insurances: there is a the list of books I had prior this thing that happen in my apartment that destroyed all of them. Considering the time that it would have taken, I always pushed this work for later.

Then recently this thought restarted the haunt me, so I asked to my girlfriend: would you like to do this for me before we move to the other apartment? So naturally, she said yes 🙂 So I explained her how we would proceed to save some time and to archive the maximum number of information about these books.

I told her: “take this laptop and open FireFox. You notice the small “Z” icon in the lower right corner of the screen? This is Zotero; this software will save you much time to get the work done.” Naturally, she was dubious.

So I told her to go to Amazon.com, to get the ISBN of each book, to get to the Amazon web page of the book, and to click on the Zotero icon to save the information about the book. So, in 2 clicks, we were saving all the information describing each book: its title, its authors, its ISBN, its publisher, etc. It was taking about 30 seconds per book.

With that procedure, we archived all the information about the books in my library in about 5 hours.

Then I told me: fantastic, now I even have all this information in RDF, thanks to Zotero! I had to do something with that, so I put the Zotero RDF exportation file into a Virtuoso triple store. In less than a minute I had all the information about my books inside a triples store, ready to be queried with SPARQL.

Querying and browsing my book library

Linking books authors’ quotes to each book of the library

Then I wanted to know what the authors that wrote the books in my library already said. So I took the QuotationsBook.com quotes database and I linked it to the information I have about my library.

It is why you can read some quotes of Nietzsche at that web page. (note that I created the totally random “foaf:quote” property to add the quotes into the Zotero’s author resource)

Getting more information about the authors

Then, I needed to get more information about the authors I read. To get that additional information, I linked the information I have about the authors in the library with the dbpedia (rdf version of wikipedia) database.

The result is quite impressive. Go to the books/authors page. Then, click on the Nietzsches’s URI (rdf:#$kajXe; it’s the first line in the result table). Then click on the “Explore” link once the contextual window appears. From there, you will see a “sameAs” property, so click on the http://dbpedia.org… link. Then click on the “Get Data Set (Dereference)” link once the contextual window appears. That is it; you get all the information, available on Wikipedia, related to this author in my library.

Then, I know that Nietzsche is born 1844 and died in 1900, etc. So now, I can browse this new and enhanced dataset to know facts about authors I read in the past.

The idea here is to say that the author described by Zotero (in the exportation RDF file created by the software) is the same as the one in dbpedia. So, knowing that the entity defined in Zotero is the same as the one defined in dbpedia, tell us that the facts about the first and the later are true for both entities (because the reality is that both entities (different URIs) are the same).

Geographical data

From there, we can think about integrating the current data with any other type of datasets. One of them could be a geographical dataset such as Geonames.org.

In fact, we know that Nietzsche is death in the city of Weinar. So, if we link the goenames dataset with the dbpedia dataset (it is supposed to be done, but it seems that some things changed in the dbpedia dataset and that the links are no longer available; anyway, it can easily be done), we could have much more information about the place where Nietzsche is dead.

Conclusion

So, as you can see, in a couple of hours, I have been able to digitalize my library. Then, I have been able to get quotes by the author of each of my book. Then, I have also been able to get more information about each author I read.

This is really fantastic. That way, I only have to browse this new dataset to find new facts about authors and books that I didn’t know before, and that would have took me days to find (for my entire library). Thanks to the semantic web, everything has been possible in only a couple of hours.

We could push the experience even further and displaying on a map where the authors of my books are born. So, I could find where most of the authors I read in my life are born. Do I mostly read books wrote in Europe, United-States or Canada? Where a part of my knowledge came from? From where part of the World I have been influenced? Etc.