• Bookmarks
  • All bookmarks
• Books
  • All books
• Audio
  • All audio files
• Video
  • All video files
• Feeds
  • All news feeds
• Events
  • Upcomming events
• Tags
  • All tags
  • Tag mapper
  • Graph visualization
• People
  • All members
• Governance
  • Elections
  • Members of parliament
  • Voluntary task list

About

fuzzzy is the social bookmarking and networking site for web professionals, academics in the field of web and web enthusiasts. If you plan, develop, maintain, do research on, or run websites, Intranets, portals, web applications, web services then this is the site for you.

Fuzzy you say?

Yes indeed. fuzzzy is a revolutionary social and democratic bookmarking system. The system is developed as a Web 2.0 organic folktology collaborative socio-semantic knowledge federating polyscopic web research project at the University of Oslo. :) Still fuzzy? Ok, it's a community platform for building the best collection of knowledge resources for web enthusiasts.

Why 3 times z in fuzzzy?

With 3 z's because knowledge is really fuzzy. Knowledge is fuzzy and that is why we strive to develop new socio-semantic technologies that give members access to the collective wisdom of the web.

What is all the fuzzz about

Why is it different from del.icio.us and other social bookmarking sites? Fuzzzy is not only social but also semantic. In fuzzzy Tags as well as their relations have more meaning. When tags are assigned a meaning using a standard like the ISO 13250 Topic Map then people as well as other computer systems can make use of the embedded knowledge in a more meaningful way. More on Topic Maps at Wikipedia. This way of categorising content is a middle way between the top-down monolithic taxonomy approach like the Yahoo directory and the more recent social tagging (folksonomy) approaches. It is also more collaborative and will help to build a consensus language that can improve communication and support knowledge sharing.

Messy or just fuzzzy?

We call the mesh of tags a simple fuzzy common ontology (folktology) or a semantic tag cloud. Our folktology has a set of interrelated tags where each tag has a list of synonyms or aliases, a short description and relations to other tags. This makes the semantic tags suitable for categorization and can be used by various applications. The name fuzzzy comes from fuzzy logic in Artificial Intelligence. On fuzzzy.com we do not use the simple plain text tags which are common to many other web2.0 sites on the other side we do neither adhere to more formal ontologies or description logic languages. Instead we employ a pragmatic middle way approach where we use Topic Maps and a simple model where users create a semantic network of tags that may overlap end even look a bit messy. The word fuzzy is here used to describe how tags can be inaccurate. Human knowledge and language are fuzzy, so creating an accurate tag set that makes sense to everyone of the world is impossible. Instead we let people create semantic tags as they like in a bottom up fashion. The resulting tag set will be a bit fuzzy but tags still have much more meaning than plain text tags. fuzzzy tags will lower the amount of noise and there is a much greater chance you will be able to make sense of the tags and you might even learn something in the process of browsing tags. One of the things we are working on is to present tags using user-centric relevance algorithms that present tags and their relationships in away that make sense to the user. The tag graph (how tags are related) should look different depending on who’s looking.

How is it different from Wikipedia?

Some people notice a similarity between fuzzzy and wikipedia. While Wikipedia is a single site containing the defacto agreed upon knowledge, fuzzzy is a hub of links to various knowledge resources especially suited for learning. Fuzzzy is not limited to text and images as Wikipedia but consist of pointers to audio, video, events and persons that can provide you with more knowledge.

To use some metaphors; Wikipedia can be seen as a gigantic book (encyclopedia), fuzzzy can be seen as a librarian who points you to resources. The librarian (fuzzzy) knows where to find stuff. To help him, the librarian uses a cabinet filled with yellow card tags (fuzzzy semantic tags) that were used in pre-computerized libraries.

The goal of Wikipedia is to create a free encyclopedia. The goal of the fuzzzy project is to make global knowledge sharing more effective and valuable through the creation of a free and democratic community platform.

How is it different from other social bookmarking services?

fuzzzy is not just social but also semantic, collaborative and to an extent democratic. Users collaborate on creating tags, linking resources and connecting tags and knowledge resources together. Tags can also have relations between them. The underlying semantic Topic Maps system enables global distributed tagging. This makes fuzzzy unique.

Why Topic Maps?

Why do we use Topic Maps and not the RDF/OWL standards? We believe that Topic Maps is better for our purpose. Tagging is all about subjects. The Topic Maps standard evolved around this notion of subject centricity. While RDF is all about resources and statements, Topic Maps is instead all about subjects and their meaning. With Topic Maps we can establish knowledge layer a part from the resource layer. For more information on this please read Ten Theses on Topic Maps and RDF.

Who's fuzzzy?

The system was founded by Roy Lachica. The first aim of the project was to investigate human computer interaction issues related to the use of collaborative socio-semantic solutions. The second aim was to evolve knowledge in the field of socio-semantic collaborative knowledge federation and interchange systems and development.

fuzzzy future

The system is developed in tandem with academic research in the fields of Information Retrieval, HCI, Semantic Web, Knowledge Organization, Knowledge Management and Knowledge Federation. We are continuously developing the system and we plan to do so the years to come.

Our research is in stage one of three. Stage one consist of getting the portal up and running and establishing a community. Stage two will consist of tuning, developing democratic features and evolving the system in accord with the community. Stage three is all about hooking on the Semantic Web, integrating knowledge and making the knowledge within fuzzzy available to other Semantic services.