SWiM is a semantic wiki for collaboratively building, editing and browsing a mathematical knowledge base. Its pages, containing mathematical theories, are stored in OMDoc, a markup format for mathematical knowledge. Our long-term objective is to develop a software that facilitates the creation of a shared, public collection of mathematical knowledge (e.g. for education) and serves work groups of mathematicians as a tool for collaborative development of new theories.

Proceedings of the 3rd Semantic Wiki Workshop (SemWiki 2008) at the 5th European Semantic Web Conference (ESWC 2008) Tenerife, Spain, June 2nd, 2008

IkeWiki is a new kind of Wiki (a Semantic Wiki ) developed by SalzburgResearch that allows users to annotate pages and links between pages with semantic annotations. Such annotations are useful because they give machines a certain amount of "understanding" of the content that goes beyond merely displaying the page. This information can then e.g. be used for context-specific presentation of pages, advanced querying, consistency verification or drawing conclusions. Currently, IkeWiki can make use of some of the knowledge represented in RDFS and OWL schemas to display enhanced navigation tools. Furthermore, we implemented a sample "biology ontology" that automatically displays a taxonomy box for biological objects. Although IkeWiki looks and behaves like Wikipedia/MediaWiki in many aspects, it is a complete rewrite, and the system design significantly differs from other Wikis. IkeWiki makes full use of Semantic Web technologies like RDF(S) and OWL using the Jena RDF store, and is implemented as an AJAX-based Rich Internet Application, based on the Dojo Toolkit

The project KiWi is concerned with knowledge management in Semantic Wikis and funded by the European Commission under the Project Number 211932 in the EU Seventh Framework Programme (FP7). KiWi's objective is to investigate how knowledge management in highly dynamic environments can be supported using Semantic Wiki technologies, and how Semantic Wikis can be improved to satisfy the requirements of knowledge management. For this purpose, KiWi will * implement an advanced knowledge management system based on the Semantic Wiki IkeWiki and extend it by improved, rule-based reasoning support, information extraction, personalisation, and advanced visualisations and editors * verify the system on two use cases in the areas of project knowledge management and software knowledge management, with flexible workflow models and specific support for the respective application areas.

Over 10 billion pieces of reusable information can already be found across 100 million web pages which embed RDF and Microformats. Start consuming this data today with Sindice Data Web services.

Ned.com is a global, all-volunteer, member-governed, online social network (in combination with real-world locations) that is made up of social entrepreneurs, activists, artists, social purpose enterprises, grassroots nonprofit, non-governmental, and community-based organizations, and is collaborating and taking action locally, nationally & globally, in order to make the world a better place.

TechCrunch50 is broadcasting the conference live with their partner UStream which means our fans and supporters can watch our presentation live this morning during the 10:30 Pacific time session on gaming. We've included the live broadcast of the event here. Wish us luck and we look forward to welcoming you into the Akoha community of players soon. Updated 14:39. Our presentation went really well. If you missed it, you can watch the recorded version below.

Reality-based play-it-forward games Karma points are like experience points. Before launching in 2009, we'll be adding new game features including badges, rewards, and virtual currency. We'll also be improving our scoring system. So beta players should be prepared to see some changes as the game evolves. We appreciate your help in making sure the game is lots of fun.

The DBpedia community uses a flexible and extensible framework to extract different kinds of structured information from Wikipedia. The DBpedia information extraction framework is written using PHP 5. The framework is available from the DBpedia SVN (GNU GPL License).

Welcome to Faviki Wiki

Faviki is a social bookmarking tool which allows you to tag webpages you want to remember with Wikipedia terms. This means that everybody uses the same names for tags from the world's largest collection of knowledge. Thanks to DBpedia, which extracts structured information from Wikipedia and represents it in a flexible data model, these tags are reference to objects which are categorized automatically, keeping your and your friend's bookmarks and interests well organized.

The W3C OWL 2 Web Ontology Language (OWL) is a Semantic Web language designed to represent ontologies - information about how individuals are grouped and fit together in a particular domain. OWL can represent rich and complex information about classes of individuals and their properties. OWL is a logical language, where every construct has a well-defined meaning, meanings that fit together to support exact and useful representation of many different kinds of information. OWL groups information into ontologies in the form of documents that can be stored and transmitted across the World Wide Web in the same way that data and other kinds of information are and that can be completely and effectively processed by tools that extract the information implicit in an ontology.

Welcome to unparalleled insight into news and current events! Get more from the stories of the day with Silobreaker's contextual and graphical search results.

Silobreaker is a search and aggregation service for news and current affairs that looks at the data it finds like a person does. It recognizes things - companies, people, topics, places - and puts them in context. By filtering out the noise and building up a meaningful picture from the information that matters, Silobreaker enables its users to spend more time learning from the web, and less time searching it.

tagCare lets you to maintain all your tags jointly in one place, which is especially useful if you normally use several of these different platforms. Many users apply a variety of different tags within different platforms - and finally get lost among them. For example, it is hard to keep track of consistent spelling variants (e.g. not using "science_fiction" in one case and "scienceFiction" in the other) or of preferred terms (e.g. not using "bike" in one case and "bicycle" in the other). Some documents may be tagged with the general term "dog", others more specifically with "greyhound" or "border_collie". tagCare will help you to apply some structure to your tagging vocabulary so that you will more easily navigate through vocabulary choices and use tags more consistently. In tagCare, a user can assemble all tags which he has used within different systems and may then create his own vocabulary hierarchy, synonym collections and cross-references to related terms to establish some lightweight form of controlled vocabulary. This process is also called "tag gardening". Edited and structured tags will then be used to browse document collections in other platforms and to directly tag documents out of tagCare. tagCare is still under development, a first demo version will be available soon and more features will then be added step by step. tagCare will first support Flickr, Bibsonomy and del.icio.us.

Andreas Hotho's talk more specifically addressed the search for methods to identify tags which describe the same concept (or a more specific / a more general concept respectively) within a folksonomy. He suggested two approaches: 1. Applying measures directly to folksonomy statistics, allowing to describe tags as a vector; e.g. co-occurrence frequency and FolkRank could serve as a similarity measure (with these two having a tendency towards high-frequency tags) or a cosine method (which is more likely to produce "siblings") 2. Looking up tags in an external thesaurus/vocabulary (for instance achieving semantic grounding by mapping a tag and its most similar tags with Wordnet Synsets)

Perhaps this is a meme worth exploring more generally but I thought others might be interested in my story, partly because it illustrates how funding drives scientists, and partly because it shows how the combination of opportunism and serendipity can make for successful bedfellows.

You've arrived at the most complete and current source of information about the WebQuest Model. Whether you're an education student new to the topic or an experienced teacher educator looking for materials, you'll find something here to meet your needs.