Mining for Social Serendipity

A common social problem at an event in which people do not personally know all of the other participants is the natural tendency for cliques to form and for discussions to mainly happen between people who already know each other. This limits the possibility for people to make interesting new acquaintances and acts as a retarding force in the creation of new links in the social web. Encouraging users to socialize with people they don't know by revealing to them hidden surprising links could help to improve the diversity of interactions at an event. The goal of this paper is to propose a method for detecting "surprising" relationships between people attending an event. By "surprising" relationship we mean those relationships that are not known a priori, and that imply shared information not directly related with the local context of the event (location, interests, contacts) at which the meeting takes place. To demonstrate and test our concept we used the Flickr community. We focused on a community of users associated with a social event (a computer science conference) and represented in Flickr by means of a photo pool devoted to the event. We use Flickr metadata (tags) to mine for user similarity not related to the context of the event, as represented in the corresponding Flickr group. For example, we look for two group members who have been in the same highly specific place (identified by means of geo-tagged photos), but are not friends of each other and share no other common interests or, social neighborhood

Lessons learnt from the deployment of a semantic virtual research environment

The ourSpaces Virtual Research Environment makes use of Semantic Web technologies to create a platform to support multi-disciplinary research groups. This paper introduces the main semantic components of the system: a framework to capture the provenance of the research process, a collection of services to create and visualise metadata and a policy reasoning service. We also describe different approaches to authoring and accessing metadata within the VRE. Using evidence gathered from data provided by the users of the system we discuss the lessons learnt from deployment with three case study groups

How to Publish Linked Data on the Web -Proposal for a Half-day Tutorial at ISWC2008

Abstract. The Web is increasingly understood as a global information space consisting not just of linked documents, but also of Linked Data. The Linked Data principles provide a basis for realizing this Web of Data, or Semantic Web. Since early 2007 numerous data sets have been published on the Web according to these principles, in domains as broad as music, books, geographical information, films, people, events, reviews and photos. In combination these data sets consist of over 2 billion RDF triples, interlinked by more than 3 million triples that cross data sets. As this Web of Linked Data continues to grow, and an increasing number of applications are developed that exploit these data sets, there is a growing need for data publishers, researchers, developers and Web practitioners to understand Linked Data principles and practice. Run by some of the leading members of the Linked Data community, this tutorial will address those needs, and provide participants with a solid foundation from which to begin publishing Linked Data on the Web, as well as to implement applications that consume Linked Data from the Web

Media meets semantic web – How the BBC uses DBpedia and linked data to make connections

Abstract. In this paper, we describe how the BBC is working to inte-grate data and linking documents across BBC domains by using Semantic Web technology, in particular Linked Data, MusicBrainz and DBpedia. We cover the work of BBC Programmes and BBC Music building Linked Data sites for all music and programmes related brands, and we describe existing projects, ongoing development, and further research we are doing in a joint collaboration between the BBC, Freie Universität Berlin and Rattle Research in order to use DBpedia as the controlled vocabulary and semantic backbone for the whole BBC.