Hypernotation.orgHypernotation is a new method of publishing structured data on the Web, that results in browsable atomic data with machine-readable and hackable URLs.

To see what it looks like in practice, check out the DBpedia dataset published using Hypernotation. Before you start browsing the data it’s good idea to read through the examples.

more on Hypernotation.org

The Semantic Web is often described as an extension of the current Web. The idea of what extending the Web should look like can be seen in Linked Data.

In order to better understand the importance of Linked Data, one has to understand the context in which it emerged, i.e. the problem it has been trying to solve.

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The second post of the Problems of Linked Data series is about the problems regarding the concept of Linked Data:

In the Linked Data context, a node of the Web of data is redirected to the document containing its description. “Data” (or “datum”, if you’re pedantic) as the basic unit of this new Web of data, represents a new paradigm that needs to take over the role that the “document” had before. However, this idea is not fully elaborated, and documents still exist as data containers. In other words, the data structure is “glued” onto the (2D) document instead of being implemented via (3D) HTTP URIs.

Creating the Web of data is a challenge because an RDF graph and the Web graph are two different types of graphs. Arcs (links) in an RDF graph have names, while hyperlinks on the Web have only direction. Another problem is the fact that in an RDF graph, out of three types of nodes only URI references are identified by an URI. How to follow the idea of ​​Web documents and assign each “data” on the Web of data a URI, when blank nodes and literals have no URI? On the Web of documents, every document has a URI, there are no “blank documents” and “literal documents”.

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Stay tuned, more to come soon!

Check out the first post of the Problems of Linked Data series. The subject of the post is the identity of Linked Data:

In mid-2009 Paul Miller asked the question Does Linked Data need RDF?. He stated that the idea that Linked Data can only be Linked Data if expressed in RDF is a dogmatism that makes him „deeply uncomfortable“. A big debate questioning (once basic) assumptions of Linked Data began, and there is still no consensus today.

The problem arose because of the imprecise definition of the Linked Data rules that can be interpreted in different ways. The document that defines Linked Data and its rules is a personal note by Tim Berners-Lee and hasn’t been formally approved by the W3C. Even the term “Linked Data” itself is controversial and contributes to the confusion in the sense that the exact concept of “Linked Data” is conflated with the general idea of linking (any) data. Anyway, the third rule for publishing Linked Data has led to the most confusion and debate:

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Stay tuned, more to come soon!

Check out the new blog post Problems of the RDF syntax:

An RDF syntax (notation) is a concrete syntax for writing (serializing) RDF triples. There are many different notations, some of which are based on existing formats (XML, (X)HTML, JSON), while others use special formats (Turtle).

The problems of the RDF model, discussed in the previous posts, are inherited by RDF notations. Various special cases require special support in a syntax, which makes it more complex. However, RDF notations contain a number of their own problems, which can be divided into two categories:

  • various problems in RDF notations
  • the lack of a single dominant notation
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Check out the new blog post The Ultimate Problem of RDF and the Semantic Web on milicicvuk.com/blog.

In the previous posts I’ve covered two important problems of the RDF model, related to blank nodes and literals. Here, I’m going to focus on what I think is the key problem of RDF – the problem of the node of an RDF graph.

In the RDF: Concepts and Abstract Syntax, a node is defined as follows:

“The set of nodes of an RDF graph is the set of subjects and objects of triples in the graph.”

It then states that a node can be a URI reference, a literal or a blank node. However, the concept of a node itself is not clearly defined. What is it that is common to all different types of nodes? What requirements does a node need to meet in order to be a node?

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Check out the new blog post on my new (personal) blog. It’s the first post of the series on the results of my recent research, regarding the realisation of the Web of data/the Semantic Web. The first part is about the problems of the RDF model and the subject of this post are blank nodes:

Nodes without a name represent a special kind of nodes called blank nodes (bNode). These nodes simply indicate the existence of a thing, without using, or saying anything about, the name of that thing. Therefore, they are referred to as existential variables of an RDF graph.

Due to the absence of a name (URI), manipulating data containing blank nodes is much harder – they make otherwise trivial operations far more complex. They complicate the lives of data consumers, especially if data changes in the future. Blank nodes add a lot of complexity to the standards built upon them, and the implementations consuming them. They are poorly understood and difficult for beginners.

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New blog posts on Faviki

January 14, 2010

Henry Story wrote a great post titled Faviki: social bookmarking for 2010. He wrote about how Faviki is different from other bookmarking services and explained the benefit users gain from using Wikipedia concepts for tagging. In addition, he discusses the potential of integrating Faviki with Linked data and Wikipedia:

Imagine you tag a page with http://dbpedia.org/resource/Munich (the user does not see this URL of course!). Then by using the growing linked data cloud Faviki or other services will be able to start doing some very interesting inferencing on this data. So since the above resource is known to be a town, a capital, to be in Germany which is in Europe, to have more than half a million inhabitants, to be along a certain river, that contains certain museums, to have different names in a number of other languages, to be related in certain ways to certain famous people (such as the current Pope)… it will be possible to improve the service to allow you to search for things you tagged with some European town (if you can’t remember where you were exactly when you took that photo).

Read the whole post here.

Also, Faviki has been covered on MakeUseOf.com. An insightful post is titled Auto-Tag Delicious Bookmarks and Share Them Easily On Twitter With Faviki. Its author, Mahendra Palsule, explains in great detail how Faviki is used, describing the usage of bookmarklet, tagging process, auto-posting to Delicious and Twitter and the import from Delicious. Here are some arguments on why Mahendra recommends Faviki:

  • Faviki uses universal, common tags, that have Wikipedia-defined meanings. Your world of knowledge captured in your bookmarks is universally connected and discoverable to your friends via these semantic tags.
  • Tagging is simple – Faviki suggests tags automatically, also allowing you to clarify exactly what you mean.
  • You do not need to switch from Delicious. You can import all your bookmarks from Delicious. Bookmarks with semantic-rich information saved in Faviki will automatically be saved in Delicious as well.
  • Automatically share your bookmarks via Twitter.
  • Multi-language Support: Faviki is the world’s first and only bookmarking service that supports tagging in 15 languages.

Highly recommend read, especially for newcomers. Click here to read the post.

Auto-Tag Delicious Bookmarks and Share Them Easily On Twitter With FavikiAuto-Tag Delicious Bookmarks and Share Them Easily On Twitter With Faviki

We are happy to announce the new import feature that will allow Faviki users to import their bookmarks from Delicious and convert free-word tags to Common tags!

The import process is semi-automatic. Before the import begins, the most frequently used Delicious tags are shown with their suggested Common tag equivalents. Users can confirm appropriate suggestions and make corrections – the more tags are reviewed, the better.

During the import process, remaining tags are either converted automatically or left unresolved. Unresolved tags will be colored red. They can be used for search but they will not be shown in the tag cloud. Unresolved tags don’t have to be defined right away: they can be defined the next time they are used for tagging but there is also an option to define them explicitly.

To import tags or turn on automatic posting to Delicious or Twitter, you have to add your service accounts to Faviki:

To add a Delicious account, go to the “Edit profile” page and click on “Delicious account settings“. After you have entered your account information, if you want all your bookmarks from Faviki to be saved to Delicious, you can turn on the “Save my bookmarks to Delicious” option and adjust tag options.

To import bookmarks from Delicious, click on the “Import Bookmarks” link. You will be able to review suggestions for most frequently used tags before the import begins.

To add a Twitter account, go to the “Edit profile” page and click on the “Twitter account settings” link. Upon entering your account information, you can turn on the “Save my bookmarks to Twitter” option and adjust your tag options. This way, all your public bookmarks will be automatically posted to your Twitter account.

In the previous release of Faviki, Common tagging has become easier by giving users the possibility to map freely labeled tags to Common tags. Today’s feature is another step toward the same goal – making Faviki easier to integrate with other services. After the import, Faviki users can keep on bookmarking using the tags they are already used to – now mapped to semantically enriched Common tags. By turning on automatic posting to Delicious and Twitter, they don’t even have to leave behind their old services.

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today announced a new import feature. It allows users to import their bookmarks from Delicious bookmarking service and convert their free-word tags to Common tags.

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I had a very interesting conversation with Jenny Zaino from SemanticWeb.com a few days ago. We were talking about the idea of semantic tagging, our participation in creating CommonTag format, the role of Wikipedia and Google in developing the Semantic Web, as well as about future plans for Faviki.

We were also chatting about new features from the Faviki last release – the possibility for users to use their own names of tags and map them to semantic tags, as well as letting them to create new tags outside of Wikipedia with help of Google search.

You can read the article here.