Show your relations with other web sites directly on your Blog using Talk Digger and Grazr

 

 

What about showing the relationship your blog, or web page, has with other websites? Why not using the power of Talk Digger and the beauty of Grazr to let your readers discovering people that talks about you, and the people you are talking about?

This is what Talk Digger and Grazr are proposing you to do.

 

What is Grazr?

Grazr is a OPML and RSS outliner: it lets you browse these type of file in a simple and beautiful user interface directly from a web site.

 


 

You have three view modes: slider, outliner and three panes. It is simple, fast and it integrates beautifully in any blog or web page.

 

What are Talk Digger relations?

Talk Digger not only tracks conversations evolving on the Web. No, it also explicit relations between conversations (so relations between web pages).

Three type of relations are make explicit by Talk Digger:

  1. Web pages that are talking about the current Web page.
  2. Web pages, from the same domain name, that are talking about the current Web page.
  3. Web pages that the current Web page is referring to.

 

Talk Digger and Grazr

If you put Talk Digger and Grazr together, you will be able to browse effortlessly Web sites by their relationship.

 

Why adding Talk Digger’s Grazr widget on your blog or Web site?

Blog readers like reading blogs not only because they like what the blog author writes, but also because they can discover new things of interests and new people by the links created by the author.

This is why putting Talk Digger’s Grazr widget on your blog is really interesting: it helps your blog readers to discover who links to your blog, and to whom you are linking to. In both cases, these links are of interest to your readers and it will helps them to discover new and interesting things on the Web.

What is also important in the Digital World is your online reputation and trust people have in you. Their readers can trust people if they write with their real name, if they put their photo, if they write about them in a personal way, if they write about their job, etc. But the online reputation also grows when other people start to talk about you, when they start to link to your personal web site. Showing these relations between you (your blog or personal web site) can help you to create your online persona and increase your online reputation and the trust people have in you.

 

How to get your Talk Digger – Grazr widget for your blog?

It is simple. You only have to go to the Talk Digger – Grazr widget generator page.

From that web page, you only have to:

  1. Put the URL of your blog or web page in that box: “To create your own TalkDigger Grazr enter your site URL here:” and then pressing the “update” button.
  2. Going to step #2 and customizing the look-and-feel of the widget.
  3. Finalizing with the step #3 and putting the generated code in your blog or web page.

 

Technorati: | | | | | | | | | | | |

Talk Digger now serialize its SIOC and FOAF RDF documents using N3

 

   

A couple of weeks ago I make Ping the Semantic Web detecting and indexing RDF documents serialized using N3. Now I took a part of yesterday to serialize Talk Digger’s content using N3 as well.

So Talk Digger now export most of the relations it knows in RDF using 10 ontologies: SIOC, FOAF, GEO, BIO, DC, CONTENT, DCTERMS, DC, ADMIN, RSS and serialized with two languages: XML and N3.

Check at the bottom of each conversation page, or user page, and you will see SIOC and FOAF RDF documents serialized in both XML and N3.

   

I started to play with N3 serialization when I implemented it in Ping the Semantic Web. At first I was telling me: why another serialization method, why confusing users and developers with yet another way to write things?

Then I found my answer: N3 is basically a simplified teaching language used to express RDF documents (so, to serialize) developed by Sir Tim Berners-Lee. Once you get the basis of the language, you can easily read and write RDF documents in an elegant way. The parsing of N3 documents is much easier than its counter part (XML).

This serialization language gain to get know and its adoption would certainly encourage the usage of RDF by the fact that developers could concentrate their efforts on the RDF documents instead of the way they are serialized (there are so many ways to serialize something in RDF using XML; sometime I wonder if it is bounded and boundless…).

 

There are some links to getting started with N3:

Primer: Getting into RDF & Semantic Web using N3
Notation 3: An readable language for data on the Web
Turtle – Terse RDF Triple Language

Technorati: | | | | | | | | | | |

How Talk Digger fit in the second Web dimension: the Services-Web

 

    To know how Talk Digger fit into the Services-Web dimension, we have to know how user and systems can interact with Talk Digger functionalities. We have to remember that the Services-Web dimension is the Web of functionalities: how human and machines can play with the functionalities of a system?

 
Talk Digger web services

At the time I write this article, no web services are available for Talk Digger. There is only an interface users can use to play (add, modify and remove) their data in the system.

Talk Digger users doesn’t have the freedom of choice when come the time to manage the data they put in the system. They are bound to the existing user interface.

Right now, all the data created by a user is publicly available (if wanted by the user) in many ways: RDF documents supported by the use of ontologies like FOAF, SIOC etc., via RSS feeds and OPML files. However, all these things belong to the next Web: the Data-Web.

So, what about the Services-Web? When Talk Digger users will have the freedom to choose the user interface they wish to interact with the system?

Soon.

In a near future, web services will be available to developers to let them create other web services or software to interact with Talk Digger system. Such web services will let them:

 

  • Manage users profile (FOAF) hosted on Talk Digger
  • Retrieve tracking list with new in-bound links and new comments for each item
  • Add new tracks to users tracking list
  • Monitoring what a user’s friends are tracking and commenting in the system
  • Etc.

 

Then users will have the entire freedom to play with the data they create with the tools they want.

In the next article, we will see how Talk Digger will fit into the third dimension of the Web: the Data-Web.

 

Series of articles about ZitGist, Talk Digger, Ping the Semantic Web and the Semantic Web:

Article 1: Talk Digger and Ping the Semantic Web became ZitGist
Article 2: The first three dimensions of the Web: Interactive-Web, Service-Web and Data-Web
Article 3: How Talk Digger fit in the first Web dimension: the Interactive-Web

Technorati: | | | | | |

How Talk Digger fit in the first Web dimension: the Interactive-Web

 

To know how Talk Digger fit into the Interactive-Web dimension, we have to know how users interact with the system. We have to remember that the Interactive-Web dimension is the Web of humans: document formatted for humans understanding (HTML, DOC, PDF etc.). So, how people are interacting Talk Digger? How people are using Talk Digger? How people are interpreting its information? Etc.

 


Talk Digger finds links between websites and create conversations according these relations.

So users will use this list of links to discover web pages (articles, blog posts, forum threads, etc.) that link (so that is talking) about a specific web page.

 



 

Then it lets people tracking the evolution of these conversations

Users will use this functionality to track a conversation evolving around a specific web page: so they track what are the new web pages that create link to that specific web page.

 



 

People can search for conversations tracked by Talk Digger

Users can search inside Talk Digger as they would in a normal search engine. If they search for «Windows », they will get results of web pages that talk about « Windows ».

 



 

It explicit relationship between conversations

Users have the possibility to see the relationship between web pages tracked (indexed) by Talk Digger. They will use this feature to find other web pages that are in relation with the current one. If we take a look at the image bellow, you will find that the results at the left are blogs that talk about Web 2.0 services. If you check at the right, you will see a list of Web 2.0 services. It is how Talk Digger can help users to find web pages that are in relations.

 



 

It aggregates people around Web conversations to create communities

The premise here is: people that are tracking the same conversation probably have personal interests in common. That said, Talk Digger users use this feature to find people which whom they could make in contact.

 



 

It lets people expressing their thoughts vis-à-vis a conversation

Users can express themselves and converse with other users in relation to a conversation.

 



 


It connects people

Users can explicit their relationship with other Talk Digger users, or with other people having a virtual profile on the Web. Social groups are shown and help users to get in contact with people of interest.

Talk Digger users can also create their online Web profile that could be use in Talk Digger to interact with other users or anywhere else on the Web (more information about that possibility in a future article of this series).

 



 

It lets users following the activity of their social network

Another way to discover new stuff is by following what your Talk Digger friends are tracking and what they have to say about some conversations.

 



 

It explicit relationship between people

 



 

This article explains how Talk Digger fit into the Interaction-Web dimension. It explains how users interact with the system and how they analyze the information that is presented to them. So, this is how Talk Digger fit into the Web of human.

In the next article, we will see how Talk Digger will fit into the second dimension of the Web: the Services-Web.

Series of articles about ZitGist, Talk Digger, Ping the Semantic Web and the Semantic Web:

Article 1: Talk Digger and Ping the Semantic Web became ZitGist
Article 2: The first three dimensions of the Web: Interactive-Web, Service-Web and Data-Web

Technorati: | | | | | | |

The first three dimensions of the Web: Interactive-Web, Service-Web and Data-Web

My colleague Kingsley introduced the concepts of a multi-dimensional Web (compared to the multi-dimensional universe). He described the first four dimensions as:

 

Dimension 1 = Interactive Web (Visual Web of HTML based Sites aka Web 1.0)

Dimension 2 = Services Web (Presence based Web of Services; a usage pattern commonly referred to as Web 2.0)

Dimension 3 = Data Web (Presence and Open Data Access based Web of Databases aka Semantic Web layer 1)

Dimension 4 = Ontology Web (Intelligent Agent palatable Web aka Semantic Web layer 2)

 

So, the Web as we know it today would have three dimensions:

  1. Interactive-Web
  2. Services-Web
  3. Data-Web

 

Personally I would define them as (without talking about Web 1.0 or Web 2.0 or Web X.0):

 

The Interactive-Web dimension is the Web of humans: document formatted for humans understanding (HTML, DOC, PDF etc.).

The Services-Web dimension is the Web of functionalities: how humans and machines can play with functionalities of a system.

The Data-Web dimension is the Web of data presence: availability of open and meaningful data. How machines can play with the data of a system.

 

The Interactive-Web

The Interactive-Web is the Web of humans: a Web where all documents (HTML, PDF, DOC, etc.) are formatted at the intention of the humans with visual markers (headers, footers, bold characters, bigger fonts etc.) to help them scanning and quickly finding the right information.

But the problem with the Interactive-Web is that it is only intended to humans, so machines (software agents for example) have real difficulty to analyze and interpret this type of documents.

 

The Services-Web

The Services-Web also exists in the current landscape of the Web: a Web where protocols exist to let people and machines (web services, software, etc) playing with the functionalities of a system.

With this Web, one can manipulate the information within a system (web service) without using the primary user interface developed for this purpose. That way, the power is gave back to the users letting them manipulating (in most cases) their data using the user interface they like.

The Services-Web dimension already exists and is extensively used to publish information on the Web. Fewer web services will use the Services-Web to let people adding, modifying and deleting data (their own) in the system.

 

The Data-Web

The Data-Web dimension also exist in the current Web, but it is much more marginal than the two firsts dimensions. This dimension belongs to the idea of the Semantic Web: developing standards to let machines (software) communicating together in a meaningful way. The idea here is to publish structured data at the intention of machines (and not human) to help them communicate (and the communication is assured by the use of standards).

 

A switch from Services-Web to the Data-Web

What I think that will happen is that the Services-Web dimension will not be used to publish information from a system to another as it is today. In fact, the Services-Web will only let users trigger functionalities of a system to add, modify and delete data in the system, and the Data-Web will publish (the communication of the data will be assured by the use of standards such as the one of the Semantic Web) data in a meaningful way from a system to another system.

So the way we use the Services-Web today is not the way we will use it tomorrow.

 

Final word

Yesterday I started to write a series of articles to explain the creation of ZitGist and to explain how Talk Digger and Ping the Semantic Web will evolve in the next months and years.

This article is the foundation of my explanation. This is the basic framework I’ll use to explain how Talk Digger and Ping the Semantic Web work and how they interact together and with the Web.

In the next few articles, I’ll explain how these two systems fit in this framework.

 

Technorati: | | | | | | | | | | |